CN117557033A - Mixed energy system site selection and volume determination planning method and device - Google Patents
Mixed energy system site selection and volume determination planning method and device Download PDFInfo
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Abstract
The invention provides a method and a device for planning a mixed energy system by site selection and volume fixation, wherein the method is characterized in that iterative computation is carried out on the basis of a double-layer model comprising a planning layer model and an operation layer model, under the condition that the iteration is confirmed to meet the iteration ending condition, the evaluation index value of a target power distribution network is obtained by computation on the basis of the position information and the capacity information of a target distributed power supply and the position information and the capacity information of a target energy storage device output by the iteration planning layer model, and under the condition that the evaluation index value is not larger than a preset value, the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iteration planning layer model are determined to be a site selection and volume fixation planning result. The invention provides a method and a device for planning the site selection and the volume determination of a hybrid energy system, which can perform more reasonable site selection and volume determination planning on a distributed power supply and multiple types of energy storage devices which are connected into a power distribution network, and can improve the operation safety and the economy of the power distribution network.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a method and a device for planning site selection and volume fixation of a hybrid energy system.
Background
In recent years, mixed energy systems including distributed power sources and energy storage devices have increased in duty in distribution networks. And a high proportion of hybrid energy systems access the distribution network, which can lead to a higher complexity and greater uncertainty of the distribution network.
The installation positions and the capacities of the distributed power sources and the energy storage devices in the mixed energy system are reasonably configured, so that the electric energy quality of the power distribution network can be effectively improved, the active loss of the power distribution network can be reduced, and the economical efficiency, the safety and the reliability of the operation of the power distribution network can be improved.
However, it is difficult to reasonably configure the installation locations and capacities of distributed power sources and various types of energy storage devices that are connected to the power distribution network in the related art, resulting in low operational safety and economy of the power distribution network. Therefore, how to perform more reasonable site-specific volume planning on a distributed power supply and multiple types of energy storage devices in an access power distribution network, so as to improve the running safety and economy of the power distribution network is a technical problem to be solved in the field.
Disclosure of Invention
The invention provides a method and a device for planning the site selection and the volume setting of a hybrid energy system, which are used for solving the defects that the installation positions and the capacities of a distributed power supply and a plurality of types of energy storage devices which are connected into a power distribution network are difficult to carry out reasonable configuration in the prior art, so that the operation safety and the economy of the power distribution network are lower, and realizing more reasonable site selection and volume setting planning of the distributed power supply and the plurality of types of energy storage devices which are connected into the power distribution network, thereby improving the operation safety and the economy of the power distribution network.
The invention provides a method for planning site selection and volume fixation of a hybrid energy system, wherein the hybrid energy system comprises a distributed power supply and an energy storage device, and the energy storage device comprises a virtual energy storage device;
the method comprises the following steps:
in the iteration, outputting data of a target distributed power supply, energy storage data of a target energy storage device and a value of a first target parameter output by a last iteration operation layer model are input into a planning layer model, position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and a value of a second target parameter output by the planning layer model in the iteration are obtained, the position information and capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device output by the planning layer model in the iteration are input into the operation layer model, and outputting data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the operation layer model in the iteration are obtained;
and performing the next iteration under the condition that the iteration does not meet the iteration ending condition based on the value of the second target parameter output by the planning layer model of the iteration, the value of the first target parameter output by the operation layer model of the iteration or the accumulated iteration times,
Under the condition that the iteration meets the iteration ending condition based on the value of the second target parameter output by the planning layer model of the iteration and the value of the first target parameter output by the operation layer model of the iteration or the accumulated iteration times, calculating to obtain an evaluation index value of the target power distribution network based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the planning layer model of the iteration;
under the condition that the evaluation index value of the target power distribution network is not greater than a preset value, determining the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device which are output by the planning layer model in the iteration at this time as the site selection and volume fixation planning results of the target distributed power supply and the target energy storage device;
the target distributed power supply is a distributed power supply to be connected to a target power distribution network, and the target energy storage device is an energy storage device to be connected to the target power distribution network;
in this iteration, the planning layer model is configured to obtain and output, based on output data of the target distributed power source and energy storage data of the target energy storage device, distribution information of the target power distribution network, target constraint, and a second target function output by the previous iteration of the operation layer model, position information and capacity information of the target distributed power source, position information and capacity information of the target energy storage device, and a value of the second target parameter;
In the iteration, the operation layer model is used for acquiring and outputting output data of the target distributed power supply, energy storage data of the target energy storage device and values of the first target parameters based on the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device, the target constraint and the first target function which are output by the planning layer model in the iteration;
in the first iteration, the planning layer model is further configured to obtain and output, based on only the distribution information of the target distribution network, the target constraint, and the second objective function, the position information and capacity information of the target distribution power source, the position information and capacity information of the target energy storage device, and the value of the second objective parameter.
According to the method for planning the site selection and the volume fixation of the hybrid energy system, the evaluation index is used for evaluating the voltage floating condition in the target power distribution network;
the calculating, based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the planning layer model in the iteration, an evaluation index value of the target power distribution network includes:
Calculating the voltage of each node in the target power distribution network based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device, which are output by the planning layer model in the iteration;
and calculating an evaluation index value of the target power distribution network based on the voltage of each node and the total number of the nodes in the target power distribution network.
According to the method for planning the site selection and volume fixation of the hybrid energy system, in the iteration, output data of a target distributed power supply, energy storage data of a target energy storage device and a value of a first target parameter output by a last iteration operation layer model are input into a planning layer model, and position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and a value of a second target parameter output by the planning layer model are obtained, wherein the method comprises the following steps:
in the iteration, output data of a target distributed power supply, energy storage data of a target energy storage device and a value of a first target parameter output by a last iteration operation layer model are input into a planning layer model, the planning layer model calculates and obtains position information and capacity information of the target distributed power supply and position information and capacity information of the target energy storage device by using a particle swarm algorithm based on the output data of the target distributed power supply, the energy storage data of the target energy storage device and the target constraint output by the operation layer model of the last iteration, and the output data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the operation layer model of the last iteration are brought into the second target function, and the value of the second target parameter is calculated and obtained, so that the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter output by the planning layer model of the current iteration are obtained.
According to the method for planning the site selection and volume fixation of the hybrid energy system, the first target parameter comprises annual operation cost of the target power distribution network.
According to the method for planning the site selection and the volume fixation of the hybrid energy system, the second target parameters comprise the annual cost of the target power distribution network.
According to the method for planning the site selection and the volume fixation of the hybrid energy system, which is provided by the invention, the target constraint comprises the following steps: node voltage constraints, branch current constraints, capacity constraints of the distributed power supply at the to-be-accessed node, load power constraints of the virtual energy storage device, capacity constraints of the distributed power supply, node power flow constraints, and power balance constraints of the power distribution network.
The invention also provides a device for planning the site selection and the volume setting of the hybrid energy system, which comprises the following components:
the hybrid energy system comprises a distributed power supply and an energy storage device, wherein the energy storage device comprises a virtual energy storage device;
the device comprises:
the iteration calculation module is used for inputting the output data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the operation layer model of the previous iteration into a planning layer model in the current iteration, acquiring the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter output by the planning layer model of the current iteration, inputting the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device output by the planning layer model of the current iteration into the operation layer model, and acquiring the output data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the operation layer model of the current iteration;
The index calculation module is used for carrying out the next iteration under the condition that the value of the second target parameter output by the planning layer model of the current iteration, the value of the first target parameter output by the operation layer model of the current iteration or the accumulated iteration number is determined to not meet the iteration end condition, and calculating to obtain the evaluation index value of the target power distribution network under the condition that the value of the second target parameter output by the planning layer model of the current iteration and the value of the first target parameter output by the operation layer model of the current iteration or the accumulated iteration number is determined to meet the iteration end condition based on the position information and the capacity information of the target distributed power supply output by the planning layer model of the current iteration and the position information and the capacity information of the target energy storage device;
the result output module is used for determining the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device which are output by the planning layer model in the iteration at this time as the site-selection and volume-fixation planning results of the target distributed power supply and the target energy storage device under the condition that the evaluation index value of the target power distribution network is not greater than a preset value;
The target distributed power supply is a distributed power supply to be connected to a target power distribution network, and the target energy storage device is an energy storage device to be connected to the target power distribution network;
in this iteration, the planning layer model is configured to obtain and output, based on output data of the target distributed power source and energy storage data of the target energy storage device, distribution information of the target power distribution network, target constraint, and a second target function output by the previous iteration of the operation layer model, position information and capacity information of the target distributed power source, position information and capacity information of the target energy storage device, and a value of the second target parameter;
in the iteration, the operation layer model is used for acquiring and outputting output data of the target distributed power supply, energy storage data of the target energy storage device and values of the first target parameters based on the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device, the target constraint and the first target function which are output by the planning layer model in the iteration;
in the first iteration, the planning layer model is further configured to obtain and output, based on only the distribution information of the target distribution network, the target constraint, and the second objective function, the position information and capacity information of the target distribution power source, the position information and capacity information of the target energy storage device, and the value of the second objective parameter.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the method for planning the location and the volume of the hybrid energy system when executing the program.
The invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a hybrid energy system site-specific and volume-specific planning method as described in any one of the above.
The invention also provides a computer program product, which comprises a computer program, wherein the computer program realizes the method for planning the site selection and the volume fixation of the hybrid energy system when being executed by a processor.
According to the hybrid energy system site selection and volume determination planning method and device, iterative calculation is carried out on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device based on the double-layer model comprising the planning layer model and the running layer model, under the condition that the iteration is confirmed to meet the iteration ending condition, the evaluation index value of the target power distribution network is obtained through calculation based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iteration planning layer model, under the condition that the evaluation index value is not greater than a preset value, the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iteration planning layer model are confirmed to be the site selection and volume determination planning result of the target distributed power supply and the target energy storage device, more reasonable site selection and volume determination can be carried out on the distributed power supply and the multiple types of energy storage devices in the power distribution network, further the safety and economical efficiency of the power distribution network running can be improved, more accurate data support can be provided for the virtual energy storage device to the power distribution network, and the clean energy storage device can be accessed into the power distribution network, and the clean energy utilization rate can be improved.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for planning the site selection and volume fixation of a hybrid energy system;
FIG. 2 is a diagram of the interaction relationship between a planning layer model and an operation layer model in the hybrid energy system site selection and volume determination planning method provided by the invention;
fig. 3 is a schematic diagram of a node topology structure of a target power distribution network in the hybrid energy system locating and sizing planning method provided by the invention;
FIG. 4 is a schematic diagram of the addressing results of a target distributed power supply and a target energy storage device in the method for planning the addressing and the volume of the hybrid energy system;
fig. 5 is a schematic diagram of the change of the voltage floating index value of the target power distribution network in different scenes in the method for planning the site selection and the volume fixation of the hybrid energy system;
fig. 6 is a schematic structural diagram of the device for planning the site selection and volume fixation of the hybrid energy system;
Fig. 7 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the invention, it should be noted that, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
In the description of the present application, the terms "first," "second," and the like are used for distinguishing between similar objects and not for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type and not limited to the number of objects, e.g., the first object may be one or more. In addition, in the description of the present application, "and/or" means at least one of the connected objects, and the character "/", generally means a relationship in which the front and rear associated objects are one kind of "or".
The distributed power supply (Distributed Energy Resources, DER) refers to a small-scale renewable and non-renewable energy power generation device dispersed on the user side. Unlike conventional centralized energy systems, distributed power sources can be produced and used by local and personal sources to meet energy demands, which helps to improve energy safety, reliability, and reduce energy transmission losses. The distributed power source may include various types of devices such as solar photovoltaic power generation devices, wind power generation devices, small gas turbine power generation devices, fuel cells, micro hydro power generation devices, and the like. Distributed power sources may be installed in an end user's building, factory, residential area, or community to meet local energy demands.
However, the output power of the distributed power sources such as solar Photovoltaic (PV), wind Turbine (WT) and the like is not stable, and the energy storage device (Energy Storage System, ESS) needs to be configured to buffer the adverse effects caused by the unstable output power of the distributed power sources.
With the ever-decreasing total reserves of non-renewable energy sources such as petroleum, coal, natural gas, etc., and a series of environmental problems caused by the massive use of fossil energy sources, renewable clean energy sources have gradually become key directions for the transformation of global energy systems. Accordingly, in recent years, hybrid energy systems including distributed power sources and energy storage devices have been increasingly used in distribution networks. And a high proportion of hybrid energy systems access the distribution network, which can lead to a higher complexity and greater uncertainty of the distribution network.
The site selection and volume determination planning of the hybrid energy system is to determine the installation positions and configuration capacities of the distributed power sources and the multi-type energy storage in the hybrid energy system on the basis of known load prediction results and the running condition of the power distribution network, so that the economical efficiency and reliability of the power distribution network in the whole planning period are optimal.
The installation positions and the capacities of the distributed power sources and the energy storage devices in the mixed energy system are reasonably configured, so that the electric energy quality of the power distribution network can be effectively improved, the active loss of the power distribution network can be reduced, and the economical efficiency, the safety and the reliability of the operation of the power distribution network can be improved. Otherwise, the electric energy loss, the tide distribution, the electric energy quality, the switch equipment protection and the like of the power distribution network can be influenced, and the operation safety and the economy of the power distribution network are threatened.
However, for a power distribution network with a higher access proportion of a hybrid energy system, in the related art, when a distributed power supply and an energy storage device in the hybrid energy system are subjected to site selection and volume planning, only optimization and configuration of limited resources are generally considered, and the energy storage potential of resources such as a virtual energy storage device is not considered, so that the installation positions and capacities of the distributed power supply and the multi-type energy storage device which are accessed into the power distribution network are difficult to reasonably configure, and the operation safety and the economy of the power distribution network are lower.
In this regard, the invention provides a method for planning the site selection and volume fixation of a hybrid energy system. The method for planning the site selection and the volume fixation of the hybrid energy system can reasonably conduct site selection and volume fixation planning on the distributed power supply and the multi-type energy storage devices which are connected into the power distribution network, further can improve the running safety and economy of the power distribution network, and can improve more accurate data support for the wide application of renewable clean energy.
Fig. 1 is a flow chart of the method for planning the site selection and volume fixation of the hybrid energy system. The method for planning the site selection and the volume fixation of the hybrid energy system is described below with reference to fig. 1. The hybrid energy system includes a distributed power source and an energy storage device, the energy storage device including a virtual energy storage device. As shown in fig. 1, the method includes: step 101, in the iteration, inputting output data of a target distributed power supply, energy storage data of a target energy storage device and a value of a first target parameter output by a last iteration operation layer model into a planning layer model, acquiring position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and a value of a second target parameter output by the iteration planning layer model, inputting the position information and capacity information of the target distributed power supply, the position information and capacity information of the target energy storage device output by the iteration planning layer model into the operation layer model, and acquiring output data of the target distributed power supply, energy storage data of the target energy storage device and a value of the first target parameter output by the iteration operation layer model;
The target distributed power supply is a distributed power supply to be connected to a target power distribution network, and the target energy storage device is an energy storage device to be connected to the target power distribution network;
in the iteration, the planning layer model is used for acquiring and outputting position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and values of second target parameters based on output data of the target distributed power supply, energy storage data of the target energy storage device, distribution information of the target power distribution network, target constraint and a second target function which are output by the previous iteration operation layer model;
in the iteration, the operation layer model is used for acquiring and outputting output data of the target distributed power supply, energy storage data of the target energy storage device and values of first target parameters based on the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device, the target constraint and the first target function which are output by the iteration planning layer model;
in the first iteration, the planning layer model is further used for acquiring and outputting the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter based on the distribution information, the target constraint and the second target function of the target power distribution network.
It should be noted that, the execution body of the embodiment of the invention is a device for planning the site selection and volume determination of the hybrid energy system.
Specifically, the method for locating and sizing the mixed energy system provided by the invention can be used for locating and sizing the target distributed power supply and the target energy storage device which are to be connected into the target power distribution network.
It should be noted that, in the embodiment of the present invention, the target power distribution network, the target distributed power source, and the target energy storage device may be determined based on actual requirements. In the embodiment of the invention, the target power distribution network, the target distributed power supply and the target energy storage device are not particularly limited.
Optionally, the target distributed power source in the embodiment of the present invention may include a solar photovoltaic power generation device and/or a wind power generation device, and the target distributed power source may further include at least one of a gas turbine power generation device, a fuel cell, and a hydroelectric power generation device.
It should be noted that the target energy storage device in the embodiment of the present invention may include a virtual energy storage device, or the target energy storage device may include a virtual energy storage device and an electrochemical energy storage device.
Wherein the virtual energy storage device may be used to convert a flexible load into electrical energy for storage, the flexible compliance may include, but is not limited to, some or all of translatable loads (SL), translatable loads (Transferable load, TL), and load shedding (RL); the electrochemical energy storage device may include a battery or the like.
It should be noted that the flexible loads have energy storage properties, so that the transfer of electric energy consumption can be realized. In the embodiment of the invention, the energy storage data of the virtual energy storage device can be calculated based on the controllable load virtual energy storage model.
The controllable load virtual energy storage model can regard the instantaneous power value of the flexible load as the charge and discharge power value of the virtual energy storage device, when the flexible load shifts time, the running power of the flexible load in the current interval is reduced, the flexibility in the current interval accords with the total load reduction in the power distribution network where the flexible load is positioned, and the operation is equivalent to the discharge operation of the virtual energy storage device. After the flexible load time shifting is completed, the running power of the flexible load in the next time shifting interval is increased, and the total load in the power distribution network in the next time shifting interval is increased, which is equivalent to the charging operation of the virtual energy storage device.
For the translatable load, the translatable load is constrained by the production flow, only translation of the complete electricity utilization time period can be realized, when the load curve moves forward, the translatable load is equivalent to that of the virtual energy storage device to charge first and then discharge, and otherwise, the translatable load is equivalent to that of the virtual energy storage device to charge first and then discharge.
Common translatable loads may include industrial pipelining, fixed flow household appliances, and the like.
The response characteristic model and the excitation strategy of the translatable load are shown in the formulas (1) to (4). The regulation and control of translatable load needs to meet scheduling continuity, scheduling time period constraint and the like.
The unit scheduling period is set to 1h for translatable load L shift Power distribution situation before participation in demand responseThe following is shown:
wherein t is S Representing a load translation initiation period; t is t D Indicating the load translation duration.
Translatable segment arrangementIs [ t ] sh- ,t sh+ ]The translatable load needs to be translated integrally, the initial period and duration of the load translation are considered, L shift The translational state during period τ is characterized by the variable α. In the case of α (τ) =1, this indicates that the period L is τ shift Translation occurs; in the case of α (τ) =0, this indicates that no shift occurs during τ. Start period set S shift Can be expressed as:
S shift ＝[t sh- ,t sh+ -t D +1]∪{t S } (2)
if τ=t S Indicating that the translatable load is not translated; if tau e t sh- ,t sh+ -t D +1]And τ+.t S Then the translatable load is translated, from a starting time period of t S A kind of electronic deviceTransition to L with onset period τ shift Power L of translatable load shift The following is shown:
L shift ＝(0,...,P shift (τ),P shift (τ+1),...,P shift (τ+t D -t S ),...,0) (3)
Cost F available to user after translatable load translation shift Expressed as:
for a translatable load, the translatable load has some similarity to the translatable load, but is more flexible in comparison to the translatable load. Because of no limitations of continuity and timing, translatable loads can be flexibly accommodated within a time interval of acceptable transition. The difference between the transferred curve and the original curve is positive to represent the charging part of the virtual energy storage device, and is negative to represent the discharging part of the virtual energy storage device.
Common transferable loads include ice storage air conditioners, electric vehicle battery replacement stations, part of industrial and commercial loads and the like.
The response characteristic model and the excitation strategy of the transferable loads are shown in the formulas (5) to (7). The regulation and control of the transferable load are required to meet the power constraint, the scheduling time period constraint, the total power consumption constraint and the like.
The transferable segment is set to [ t ] tr- ,t tr+ ]，L tran The transition state during period τ is characterized by the variable β, where β (τ) =0, representing the transition state during period τ L tran No transfer occurs; when β (τ) =1, this indicates that the period L is τ tran Transfer power P at which load can be transferred occurs tran The upper and lower limit constraints of (t) are as follows:
wherein,the maximum and minimum power values of the transferable loads, respectively.
If the load transfer duration of the transferable load is not limited, the phenomenon that the load is transferred to a plurality of time periods occurs, and the equipment is frequently started and stopped, so that the minimum continuous operation time of the transferable load needs to be limited:
wherein,representing the minimum continuous run time for which load transfer can be performed by transferring load.
Transferable fee F available to user after load transfer tran Can be expressed as:
wherein,the compensation price for load transfer of transferable load of unit power is represented.
For a load that may be cut, the load may be cut or interrupted by analyzing user comfort and responding to user intent. The reduced power capable of reducing the load corresponds to the discharge of the virtual energy storage device, and meanwhile, the advanced cold accumulation and heat accumulation can be utilized for charging the virtual energy storage device.
Common load shedding may include a large number of temperature controlled loads, building lighting loads, and the like.
The response characteristic model and the excitation strategy that can cut down the load are shown in the formulas (8) to (11). The load shedding requirements meet load shedding duration constraints, etc. The load-reducible incentive compensation generally includes both a fixed capacity cost and a variable price cost, since the load-reducible situation causes inconvenience to the user.
The load-shedding load is significantly different from the translatable load and the transferable load, and the total amount of electricity used in a certain period of time can be reduced.
Load L can be reduced cut The clipping state during period τ can be characterized by the variable γ. In the case of γ (τ) =0, it means that the load L can be cut down in τ period cut No curtailment occurs; in the case of γ (τ) =1, it means that the load L can be cut down in τ period cut The load L can be reduced by reducing cut The curtailed power P generated in the τ period cut (τ) is as follows:
wherein θ (τ) represents a load shedding coefficient of τ period, θ (τ) ∈ [0,1 ]]；Representing load-reducible responsePower for the pre-demand τ period.
In view of user comfort and satisfaction, there is a need to limit the continuous cut time and the number of cuts.
The maximum and minimum continuous cut-down time constraints that can cut down the load are as follows:
the cut-down times constraint is as follows:
wherein T is cut Representing a cut-down period;representing a minimum continuous cut-down time; />Representing a maximum continuous reduction time; n (N) max Indicating the maximum number of cuts.
Cost F available to the user after load shedding can be reduced cut Expressed as:
wherein,the compensation price for load transfer is reduced for unit power.
For an electrochemical energy storage device, the response characteristic model of the electrochemical energy storage device is shown in equation (12). The electrochemical energy storage device needs to meet the energy storage charging and discharging power constraint, the charging and discharging capacity constraint, the full scheduling period electric quantity balance constraint and the like.
Wherein,representing the charge/discharge power value of the ith electrochemical energy storage device in the t period, wherein the discharge is positive and the charge is negative; />And->Respectively representing upper and lower limits of charge/discharge power of the ith electrochemical energy storage device; SOC (State of Charge) t Representing the initial energy storage charge state of the electrochemical energy storage device at the time t; e (E) ESS Representing the capacity of the electrochemical energy storage device; d (D) ESS Representing the self-loss coefficient of the electrochemical energy storage device; p (P) char,t And P dis,t Respectively representing the charge and discharge power of the electrochemical energy storage device in the t period; η (eta) char And eta dis Respectively representing the charge and discharge efficiency of the electrochemical energy storage device; h char,t And H dis,t Respectively representing the charge and discharge states of the electrochemical energy storage device, and the value is 0 or 1.
In addition, the electrochemical energy storage device also meets the constraint of charge state and the constraint of charge and discharge power, ensures that the energy storage of the electrochemical energy storage device works in a normal state, and avoids overcharge and overdischarge.And->The upper and lower limits of the state of charge of the electrochemical energy storage device are indicated, respectively.
Fig. 2 is a diagram of the interaction relationship between a planning layer model and an operation layer model in the hybrid energy system site selection and volume determination planning method provided by the invention. As shown in fig. 2, in the case that the current iteration is the x-th iteration (x is a positive integer greater than 1), after the output data of the target distributed power source and the energy storage data of the target energy storage device output by the x-1-th iteration operation layer model are input into the planning layer model, the planning layer model may acquire and output, by means of numerical calculation, the position information and the capacity information of the target distributed power source, the position information and the capacity information of the target energy storage device, and the value of the second target parameter based on the output data of the target distributed power source and the energy storage data of the target energy storage device output by the x-1-th iteration operation layer model, the distribution information of the target distribution network, the value of the first target parameter, and the target constraint.
It should be noted that, the distribution information of the target power distribution network may include the number of nodes, the number of branches, the number of nodes on each branch, and the like in the target power distribution network.
It should be noted that, in the embodiments of the present invention, the target constraint may be predefined according to a priori knowledge and/or actual conditions. The target constraint in the embodiment of the present invention is not particularly limited.
It should be noted that, under the condition that the iteration is the first iteration, the planning layer model may only acquire and output, by means of numerical calculation, the position information and the capacity information of the target distributed power source, the position information and the capacity information of the target energy storage device, and the value of the second target parameter based on the distribution information of the target power distribution network and the target constraint.
It should be noted that, in the embodiment of the present invention, the location information may include identification information of the to-be-accessed node.
As an optional embodiment, in the iteration, output data of the target distributed power source, energy storage data of the target energy storage device and a value of the first target parameter output by the previous iteration operation layer model are input into the planning layer model, and position information and capacity information of the target distributed power source, position information and capacity information of the target energy storage device and a value of the second target parameter output by the iteration planning layer model are obtained, including: in the iteration, the output data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the last iteration operation layer model are input into the planning layer model, the planning layer model calculates and obtains the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device by utilizing a particle swarm algorithm based on the output data of the target distributed power supply, the energy storage data of the target energy storage device and the target constraint output by the last iteration operation layer model, and the output data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the last iteration operation layer model are brought into a second target function to calculate and obtain the value of the second target parameter, and then the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter output by the iteration planning layer model are obtained.
Specifically, in the case that the current iteration is the x-th iteration (x is a positive integer greater than 1), after the output data of the target distributed power source and the energy storage data of the target energy storage device output by the x-1-th iteration operation layer model are input into the planning layer model, the planning layer model may update the position and the speed of the particles in the particle swarm algorithm based on the output data of the target distributed power source and the energy storage data of the target energy storage device output by the x-1-th iteration operation layer model and the target constraint, and further may calculate the position information and the capacity information of the target distributed power source and the position information and the capacity information of the target energy storage device by using the particle swarm algorithm.
After the output data of the target distributed power supply and the energy storage data of the target energy storage device output by the x-1 th iteration operation layer model are input into the planning layer model, the planning layer model can also bring the output data of the target distributed power supply and the energy storage data of the target energy storage device output by the x-1 th iteration operation layer model into a second objective function, and further, the value of the second objective parameter can be calculated in a numerical calculation mode.
As an alternative embodiment, the target constraint includes: node voltage constraints, branch current constraints, capacity constraints of the distributed power supply at the to-be-accessed node, load power constraints of the virtual energy storage device, capacity constraints of the distributed power supply, node power flow constraints, and power balance constraints of the power distribution network.
Specifically, the node voltage constraint may be expressed by the following formula:
U i,min ≤U i ≤U i，max ,i∈N (13)
wherein U is i,min And U i，max Voltage U representing node i in a target power distribution network i Upper and lower limits of (2); n represents the total number of nodes in the target distribution network.
The branch current constraint may be expressed by the following formula:
I j ≤I j，max ,j∈L (14)
wherein I is j，max Representing the current I of a branch L in a target distribution network j Upper limit of (2); z represents the total number of branches in the target distribution network.
The capacity constraint of the distributed power supply at the intended access node can be expressed by the following formula:
S[i]≤S[i] max ,i∈N DG (15)
wherein S [ i ]]Representing the total amount of the target distributed power source connected to the target power distribution network under the condition that the target distributed power source is connected to the node i in the target power distribution network; s [ i ]] max Representing an upper limit of the total installed capacity of the target distributed power supply in the case that the target distributed power supply is connected to a node i in the target power distribution network; n (N) DG Representing a set of target distributed power supply intended access nodes in a target distribution network.
The load power constraint of the virtual energy storage device may be expressed by the following formula:
wherein: p (P) load,t Representing the real-time load of a user in a target power distribution network, wherein the unit is as follows: kW; alpha min 、α max 、β min 、β max 、γ min 、γ max Representing the response of the target distribution network respectivelyMinimum and maximum values of response coefficients of load shedding, load transferability and load translation within a segment, alpha in the embodiment of the invention min ＝0、α max ＝0.5、β min ＝0、β max ＝0.5、γ min ＝0、γ max ＝0.5；P cut,t Representing the power of the target power distribution network which can reduce the load; p (P) tran,t Representing power of transferable loads in the target power distribution network; p (P) shift,t Representing the power of the translatable load.
The capacity constraint of a distributed power supply can be expressed by the following formula:
wherein,the node i in the target power distribution network can be connected into the maximum capacity of solar photovoltaic power generation equipment, hydroelectric power generation equipment and a target energy storage device, and the unit is as follows: kW.
The node power flow constraint may be expressed by the following formula:
wherein P is i 、Q i Respectively representing active power and reactive power of a node i in a target power distribution network; u (U) j Representing the voltage of a node j in the target power distribution network; g ij 、B ij Respectively representing the conductance and susceptance between a node i and a node j in a target power distribution network; θ ij Representing the voltage phase angle between node i and node in the target distribution network.
The power balance constraint of the distribution network can be expressed by the following formula:
Σ(P buy +P pv +P wt +P ESS )＝Σ(P shift +P trans +P cut +P load ) (19)
wherein P is load Representing power of generally non-schedulable load, P cut A power indicating a load that can be reduced; p (P) tran Power representing transferable loads; p (P) shift Representing the power of the translatable load.
As an alternative embodiment, the second target parameter comprises an annual cost of the target distribution network.
Specifically, the planning layer model in the embodiment of the invention can take the lowest annual cost of the target power distribution network as an optimization target.
In the case where the second objective parameter comprises the annual cost of the objective power distribution network, the second objective function may be expressed by the following formula:
minF 2 ＝F 1 ′+C inv (20)
wherein F is 2 Representing the value of a second target parameter output by the x-th planning layer model; f, F 1 ' value of first target parameter and equipment investment cost C representing output of x-1 th iteration operation layer model inv 。
Cost of equipment investment C inv Cost of equipment investment C inv The method can be calculated by the following formula:
wherein c inv,pv 、c inv,wt 、c inv,ESS Representing the investment cost per unit capacity of the solar photovoltaic power generation equipment, the hydroelectric power generation equipment and the target energy storage device in the target distributed power supply, wherein the investment cost per unit capacity is Yuan/kw; p (P) i,pv 、P i,wt 、E i,ESS Representing the installable capacity of solar photovoltaic power generation equipment, hydroelectric power generation equipment and a target energy storage device corresponding to an ith node in a target power distribution network, and kW; npv, N wt ，N ESS Representing the number of solar photovoltaic power generation equipment, hydroelectric power generation equipment and target energy storage devices to be installed; n represents the service life; r represents the discount rate.
After the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter which are output by the x-th iterative planning layer model are obtained, the position information and the capacity information of the target distributed power supply, and the position information and the capacity information of the target energy storage device which are output by the x-th iterative planning layer model can be input into the operation layer model.
The operation layer model can acquire output data of the target distributed power supply and energy storage information of the target energy storage device in a numerical calculation mode based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the x-th iteration planning layer model, and can bring the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device into a first objective function, so that the value of the first objective parameter can be calculated through a numerical calculation method.
As an alternative embodiment, the first target parameter comprises an annual operating cost of the target power distribution network.
Specifically, the operational layer model in the embodiment of the invention can take the lowest annual operational cost of the target power distribution network as an optimization target.
In the case where the first objective parameter comprises an annual running cost of the objective power distribution network, the first objective function may be expressed by the following formula:
minF 1 ＝C t,cur,WT +C t,cur,PV +C y +C t,buy +C Loss +C LA (22)
C y ＝365×(μC inv +k renew,BESS c inv,ESS E i,ESS ) (26)
C LA ＝365×P t,CL ×e t (27)
wherein C is t,cur,PV The method comprises the steps of representing the light discarding cost of a target power distribution network; c (C) t,cur,WT The wind discarding cost of the target power distribution network is represented; c (C) y Representing the operation and maintenance cost of the target power distribution network; c (C) t,buy Representing the purchase cost of a target power distribution network; c (C) Loss Representing the network loss cost of the target power distribution network; c t,buy Representing the time-sharing electricity purchase price of a main network of a target power distribution network; c (C) Loss Representing annual loss costs of the target distribution network; c l The value of (2) is 0.4/yuan kWh -1 ；ζ cur,WT 、ζ cur,PV The unit wind discarding and light discarding cost of the target power distribution network is respectively represented; p (P) t,f,WT 、P t,WT Respectively representing a wind power predicted value and an actual power value of a target power distribution network in a t period; p (P) t,f,PV 、P t,PV Respectively representing a t-period photovoltaic predicted value and an actual power value of a target power distribution network; c buy The time-sharing electricity price of the target power distribution network is represented; p (P) t,buy The interaction power of the t-period power distribution network and the upper power grid of the target power distribution network is represented; mu represents the conversion ratio of the operation and maintenance cost of the target power distribution network, and the value of mu in the embodiment of the invention is 10%;indicating a replacement rate of the electrochemical energy storage device; c inv,ESS 、E i,ESS Respectively representing the unit capacity investment cost and the grid-connected capacity of the target energy storage device; p (P) t,CL Representing the response power of the virtual energy storage device in the target energy storage device at the time t, e t Representing the incentive price of the virtual energy storage device in the target energy storage device for participating in scheduling in a t period; t represents the number of the running time period in the day, T represents the total time period number in the day, I i The current on the ith line in the target power distribution network is expressed as KA; r is (r) i And the resistance on the ith line in the target power distribution network is expressed as omega.
Step 102, under the condition that the value of the second target parameter output by the current iteration planning layer model, the value of the first target parameter output by the current iteration running layer model or the accumulated iteration times are determined, the next iteration is performed, under the condition that the current iteration does not meet the iteration end condition, and under the condition that the value of the second target parameter output by the current iteration planning layer model and the value of the first target parameter output by the current iteration running layer model or the accumulated iteration times are determined, the evaluation index value of the target power distribution network is calculated based on the position information and the capacity information of the target distributed power supply output by the current iteration planning layer model and the position information and the capacity information of the target energy storage device.
Specifically, the value F of a second target parameter output by the x-th iteration planning layer model is obtained 2 And the value F of the first target parameter output by the xth iteration operation layer model 1 And then, judging whether the value of the second target parameter output by the x-th iteration planning layer model and the value of the first target parameter output by the x-th iteration running layer model are converged or not.
If the value of the second target parameter output by the x-th iteration planning layer model or the value of the first target parameter output by the x-th iteration running layer model is not converged, whether x is larger than the preset iteration times or not can be judged.
If the value of the second target parameter output by the x-th iteration planning layer model or the value of the first target parameter output by the x-th iteration running layer model is not converged and x is smaller than the preset iteration times, it can be determined that the x-th iteration does not meet the iteration ending condition, x can be increased by 1, and the iteration process is repeated.
If the value of the second target parameter output by the x-th iteration planning layer model and the value of the first target parameter output by the x-th iteration running layer model are converged, it can be determined that the x-th iteration meets the iteration ending condition, and then the evaluation index value of the target power distribution network can be calculated and obtained in a numerical calculation mode based on the position information and the capacity information of the target distributed power supply output by the x-th iteration planning layer model and the position information and the capacity information of the target energy storage device.
If the value of the second target parameter output by the x-th iteration planning layer model or the value of the first target parameter output by the x-th iteration running layer model is not converged, but x is not smaller than the preset iteration times, it can also be determined that the x-th iteration meets the iteration ending condition, and further, the evaluation index value of the target power distribution network can be calculated and obtained in a numerical calculation mode based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the x-th iteration planning layer model.
As an alternative embodiment, the evaluation index is used to evaluate the voltage floating condition in the target distribution network; based on the position information and capacity information of the target distributed power supply and the position information and capacity information of the target energy storage device output by the iterative planning layer model, calculating to obtain an evaluation index value of the target power distribution network, wherein the evaluation index value comprises the following components: calculating to obtain the voltage of each node in the target power distribution network based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device which are output by the iterative planning layer model;
and calculating to obtain an evaluation index value of the target power distribution network based on the voltage of each node and the total number of the nodes in the target power distribution network.
Specifically, the voltage is a main parameter of the power distribution network, and the up-down floating value of the node voltage in the power distribution network affects the stable and normal operation of the power distribution network. The voltage fluctuation in the power distribution network exceeds the normal value range, so that the normal operation of the electric equipment can be damaged, even the electric equipment is damaged, and accidents are caused. The node voltage in the power distribution network is accurately monitored and controlled, and the node voltage monitoring method is very important for keeping the power distribution network to operate normally and stably.
And, with the access of high-proportion hybrid energy systems, the voltage fluctuation of the distribution network is necessarily aggravated. Therefore, the embodiment of the invention constructs the voltage floating index as the evaluation index for evaluating the voltage fluctuation condition in the target power distribution network, and the voltage floating index of the target power distribution network can be calculated by the following formula:
Wherein U is system The voltage floating index of the target power distribution network is represented; u (U) i Representing the voltage of a node i in the target power distribution network; n represents the total node number in the target power distribution network.
It should be noted that, in the case that it is determined that the x-th iteration satisfies the iteration end condition, the voltage U of the node i in the target power distribution network i The method is obtained by calculating the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device based on the x-th iterative planning layer model.
And step 103, under the condition that the evaluation index value of the target power distribution network is not greater than a preset value, determining the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iterative planning layer model as the site selection and volume determination planning results of the target distributed power supply and the target energy storage device.
Specifically, under the condition that the x-th iteration meets the iteration ending condition, outputting the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device based on the x-th iteration planning layer model to calculate and obtain an evaluation index value U of the target power distribution network system Then, the evaluation index value U of the target power distribution network can be compared system And the magnitude of the preset value.
If the evaluation index value U of the target power distribution network system If the voltage fluctuation in the target power distribution network exceeds the normal value range, the normal operation of damaging the electric equipment is caused after the target distributed power supply and the target energy storage device output the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device are accessed into the target power distribution network according to the x-th iteration planning layer modelRisk of rows.
If the evaluation index value U of the target power distribution network system And if the voltage fluctuation in the target power distribution network does not exceed the normal value range after the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device are output by the target distributed power supply and the target energy storage device according to the x-th iteration planning layer model, the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device can be determined as the site selection and volume fixation planning results of the target distributed power supply and the target energy storage device.
It should be noted that, in the embodiment of the present invention, the preset value may be determined according to priori knowledge and/or actual situations. The specific values of the preset values in the embodiment of the present invention are not particularly limited.
According to the embodiment of the invention, iterative computation is carried out on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device based on the double-layer model comprising the planning layer model and the running layer model, and under the condition that the iteration is confirmed to meet the iteration ending condition, the evaluation index value of the target power distribution network is obtained by computation based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iteration planning layer model, and under the condition that the evaluation index value is not greater than a preset value, the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iteration planning layer model are confirmed to be the site-specific capacity planning result of the target distributed power supply and the target energy storage device, so that more reasonable site-specific capacity planning can be carried out on the distributed power supply and the multi-type energy storage device in the power distribution network, the running safety and economical efficiency of the power distribution network can be improved, more accurate data support can be provided for the virtual energy storage device to the power distribution network, and the laughing rate of renewable clean energy can be improved, and the utilization rate of renewable clean energy can be improved.
In order to facilitate understanding of the method for planning the site selection and the volume fixation of the hybrid energy system provided by the invention, the method for planning the site selection and the volume fixation of the hybrid energy system provided by the invention is explained by an example.
Fig. 3 is a schematic diagram of a node topology structure of a target power distribution network in the hybrid energy system site selection and volume determination planning method provided by the invention. The node topology of the target distribution network in this example is shown in fig. 3.
As shown in fig. 3, the target power distribution network in this example includes 33 nodes and 3 branches.
It should be noted that, in this example, the rated voltage of the bus of the target power distribution network is 10kV, the allowable range of the node power supply is 0.9-1.1 (per unit value), the reference value of the three-phase power is 10MVA, and the total active load of the target power distribution network is 3715KW.
The electricity prices of the target distribution network in this example are shown in tables 1 and 2.
TABLE 1 tariff for target distribution network
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Table 2 time-of-use tariff for a target distribution network
| Time division | Type(s) | Electricity price (/ yuan kWh) -1 ) |
| (07:00-9:00 and 17:00-23:00) | Peak segment | 0.6564 |
| (23:00-00:00 and 00:00-7:00) | Flat section | 0.4389 |
| (9:00～17:00) | Cereal section | 0.2215 |
In this example, 3 scenarios are included, in scenario 1, the target distributed power source includes a solar photovoltaic power generation device and a wind power generation device, and the target energy storage device includes only an electrochemical energy storage device; the target distributed power supply in the scene 2 comprises solar photovoltaic power generation equipment and wind power generation equipment, and the target energy storage device only comprises a virtual energy storage device; the target distributed power supply in the scene 3 comprises solar photovoltaic power generation equipment and wind power generation equipment, and the target energy storage device comprises a virtual energy storage device and an electrochemical energy storage device.
It should be noted that, in the embodiment of the present invention, the economic applicable years of the solar photovoltaic power generation device and the wind power generation device in the target distributed power supply are 10 years. The charge and discharge efficiency of the target energy storage device is 90%, the maximum value of the charge state is 0.9, and the minimum value of the charge state is 0.1. The response time period of the virtual energy storage device corresponding to the transferable load and the load-reducible in the target energy storage device is 24h.
The method for planning the site selection and the volume fixation of the hybrid energy system provided by the invention is used for planning the site selection and the volume fixation of the target distributed power supply and the target energy storage device in different scenes, and can obtain the site selection and the volume fixation planning results of the target distributed power supply and the target energy storage device in different scenes.
It should be noted that, in this example, the parameter settings of the particle swarm optimization algorithm are as follows: the particle population size is 200, the maximum iteration number is 200, and the learning factor is 1.5.
Table 3 is a schematic table of the results of the site selection and volume determination planning of the target distributed power supply and the target energy storage device in different scenes. The result of the site selection and volume determination planning of the target distributed power supply and the target energy storage device under each scene obtained by the site selection and volume determination planning method of the hybrid energy system is shown in table 3.
TABLE 3 schematic tables of the results of site-specific and volume-specific planning of target distributed power and target energy storage devices in different scenarios
Table 4 is a cost schematic representation of the target distribution network in different scenarios. The cost of the target distribution network in different scenarios is shown in table 4.
Table 4 cost schematic table of target distribution network in different scenarios
Table 5 is a schematic table of evaluation index values of the target distribution network in different scenes. The evaluation index values of the target distribution network under different scenes are shown in table 5.
TABLE 5 Voltage Floating index values of target Power distribution network in different scenarios
| Scene(s) | Voltage floating index value of target power distribution network |
| 1 | 0.014 |
| 2 | 0.024 |
| 3 | 0.009 |
As can be seen from table 4, by comparing scenario 1 and scenario 2, the cost of the target distribution network in scenario 2 is reduced by 2.15%, because the input cost of electrochemical energy storage is higher, and the cost performance of virtual energy storage is better than that of electrochemical energy storage.
The comparison result of the scene 2 and the scene 3 shows that the cooperative planning of the electrochemical energy storage device and the virtual energy storage device can improve the wind and light discarding problem of the target power distribution network, proves that the cooperative planning of the electrochemical energy storage device and the virtual energy storage device can improve the absorption rate of the target power distribution network to renewable clean energy sources.
Comparing the electricity purchase costs in table 4, the electricity purchase costs in scenario 3 are reduced by 1.79% and 2.44% compared to scenario 1 and scenario 2, respectively, which effectively reduces the electricity purchase costs. And the overall cost of scenario 3 is reduced by 1.44% compared to scenario 2. Namely, the scene 3 can effectively improve the economy of the system through the optimal configuration of various resources, and the realized effect is optimal.
Fig. 4 is a schematic diagram of the addressing results of the target distributed power supply and the target energy storage device in the method for planning the addressing and the volume-fixing of the hybrid energy system. The result of addressing the target distributed power source and the target energy storage device in scenario 3 is shown in fig. 4.
Fig. 5 is a schematic diagram of the change of the voltage floating index value of the target power distribution network in different scenes in the method for planning the site selection and the volume fixation of the hybrid energy system. As shown in fig. 5, the voltage floating index value of the target power distribution network in the scenario 3 is smoother than that of the target power distribution network in the scenario 1 and the scenario 2, so that the voltage fluctuation is stabilized, and the reliability of the electric energy is ensured.
Fig. 6 is a schematic structural diagram of the device for planning the site selection and volume fixation of the hybrid energy system. The apparatus for planning the location and the volume of the hybrid energy system provided by the invention is described below with reference to fig. 6, and the apparatus for planning the location and the volume of the hybrid energy system described below and the method for planning the location and the volume of the hybrid energy system provided by the invention described above can be referred to correspondingly. The hybrid energy system comprises a distributed power supply and an energy storage device, wherein the energy storage device comprises a virtual energy storage device. As shown in fig. 6, the apparatus for planning the site selection and volume fixation of the hybrid energy system comprises: an iterative calculation module 601, an index calculation module 602, and a result output module 603.
The iteration calculation module 601 is configured to input, in the current iteration, output data of a target distributed power source, energy storage data of a target energy storage device, and a value of a first target parameter output by a previous iteration operation layer model into a planning layer model, obtain position information and capacity information of the target distributed power source, position information and capacity information of the target energy storage device, and a value of a second target parameter output by the planning layer model, input the position information and capacity information of the target distributed power source, the position information and capacity information of the target energy storage device, and the value of the first target parameter output by the operation layer model, and obtain output data of the target distributed power source, energy storage data of the target energy storage device, and the value of the first target parameter output by the operation layer model;
the index calculation module 602 is configured to perform a next iteration when determining that the current iteration does not meet an iteration end condition based on the value of the second target parameter output by the planning layer model of the current iteration, the value of the first target parameter output by the operation layer model of the current iteration, or the accumulated iteration number, and calculate to obtain an evaluation index value of the target power distribution network based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the planning layer model of the current iteration when determining that the current iteration meets the iteration end condition based on the value of the second target parameter output by the planning layer model of the current iteration and the value of the first target parameter output by the operation layer model of the current iteration, or the accumulated iteration number;
The result output module 603 is configured to determine, as a location and volume determining planning result of the target distributed power supply and the target energy storage device, the location information and the volume information of the target distributed power supply and the location information and the volume information of the target energy storage device output by the planning layer model in the iteration at this time when the evaluation index value of the target power distribution network is not greater than a preset value;
the target distributed power supply is a distributed power supply to be connected to a target power distribution network, and the target energy storage device is an energy storage device to be connected to the target power distribution network;
in this iteration, the planning layer model is configured to obtain and output, based on output data of the target distributed power source and energy storage data of the target energy storage device, distribution information of the target power distribution network, target constraint, and a second target function output by the previous iteration of the operation layer model, position information and capacity information of the target distributed power source, position information and capacity information of the target energy storage device, and a value of the second target parameter;
in the iteration, the operation layer model is used for acquiring and outputting output data of the target distributed power supply, energy storage data of the target energy storage device and values of the first target parameters based on the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device, the target constraint and the first target function which are output by the planning layer model in the iteration;
In the first iteration, the planning layer model is further configured to obtain and output, based on only the distribution information of the target distribution network, the target constraint, and the second objective function, the position information and capacity information of the target distribution power source, the position information and capacity information of the target energy storage device, and the value of the second objective parameter.
Specifically, the iterative calculation module 601, the index calculation module 602, and the result output module 603 are electrically connected.
According to the hybrid energy system site selection and volume determination planning device, iterative calculation is carried out on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device based on the double-layer model comprising the planning layer model and the running layer model, under the condition that the iteration is confirmed to meet the iteration ending condition, the evaluation index value of the target power distribution network is obtained through calculation based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iteration planning layer model, under the condition that the evaluation index value is not greater than a preset value, the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iteration planning layer model are confirmed to be site selection and volume determination planning results of the target distributed power supply and the target energy storage device, more reasonable site selection and volume determination can be carried out on the distributed power supply and the multiple types of the energy storage devices in the power distribution network, further the safety and economical efficiency of the power distribution network running can be improved, more accurate data support can be provided for the virtual energy storage device to the power distribution network, and the clean energy storage device can be accessed into the power distribution network, and the clean energy utilization rate can be improved.
Fig. 7 illustrates a physical schematic diagram of an electronic device, as shown in fig. 7, which may include: processor 710, communication interface (Communications Interface) 720, memory 730, and communication bus 740, wherein processor 710, communication interface 720, memory 730 communicate with each other via communication bus 740. Processor 710 may invoke logic instructions in memory 730 to perform a hybrid energy system sizing approach, the approach comprising: in the iteration, outputting data of a target distributed power supply, energy storage data of a target energy storage device and a value of a first target parameter output by a last iteration operation layer model are input into a planning layer model, position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and a value of a second target parameter output by the iteration planning layer model are obtained, the position information and capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device output by the iteration planning layer model are input into the operation layer model, and outputting data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the iteration operation layer model are obtained; under the condition that the iteration does not meet the iteration ending condition, the next iteration is carried out, under the condition that the iteration meets the iteration ending condition based on the value of the second target parameter output by the iteration planning layer model and the value of the first target parameter output by the iteration running layer model, or the accumulated iteration number, the index value of the target power distribution network is calculated and obtained based on the position information and the capacity information of the target distributed power supply output by the iteration planning layer model and the position information and the capacity information of the target energy storage device; under the condition that the evaluation index value of the target power distribution network is not greater than a preset value, determining the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iterative planning layer model as the site selection and volume determination planning results of the target distributed power supply and the target energy storage device; the target distributed power supply is a distributed power supply to be connected to a target power distribution network, and the target energy storage device is an energy storage device to be connected to the target power distribution network; in the iteration, the planning layer model is used for acquiring and outputting position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and values of second target parameters based on output data of the target distributed power supply, energy storage data of the target energy storage device, distribution information of the target power distribution network, target constraint and a second target function which are output by the previous iteration operation layer model; in the iteration, the operation layer model is used for acquiring and outputting output data of the target distributed power supply, energy storage data of the target energy storage device and values of first target parameters based on the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device, the target constraint and the first target function which are output by the iteration planning layer model; in the first iteration, the planning layer model is further used for acquiring and outputting the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter based on the distribution information, the target constraint and the second target function of the target power distribution network.
Further, the logic instructions in the memory 730 described above may be implemented in the form of software functional units and may be stored in a computer readable storage medium when sold or used as a stand alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, where the computer program product includes a computer program, where the computer program can be stored on a non-transitory computer readable storage medium, and when the computer program is executed by a processor, the computer can execute the method for locating and sizing the hybrid energy system provided by the above methods, and the method includes: in the iteration, outputting data of a target distributed power supply, energy storage data of a target energy storage device and a value of a first target parameter output by a last iteration operation layer model are input into a planning layer model, position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and a value of a second target parameter output by the iteration planning layer model are obtained, the position information and capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device output by the iteration planning layer model are input into the operation layer model, and outputting data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the iteration operation layer model are obtained; under the condition that the iteration does not meet the iteration ending condition, the next iteration is carried out, under the condition that the iteration meets the iteration ending condition based on the value of the second target parameter output by the iteration planning layer model and the value of the first target parameter output by the iteration running layer model, or the accumulated iteration number, the index value of the target power distribution network is calculated and obtained based on the position information and the capacity information of the target distributed power supply output by the iteration planning layer model and the position information and the capacity information of the target energy storage device; under the condition that the evaluation index value of the target power distribution network is not greater than a preset value, determining the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iterative planning layer model as the site selection and volume determination planning results of the target distributed power supply and the target energy storage device; the target distributed power supply is a distributed power supply to be connected to a target power distribution network, and the target energy storage device is an energy storage device to be connected to the target power distribution network; in the iteration, the planning layer model is used for acquiring and outputting position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and values of second target parameters based on output data of the target distributed power supply, energy storage data of the target energy storage device, distribution information of the target power distribution network, target constraint and a second target function which are output by the previous iteration operation layer model; in the iteration, the operation layer model is used for acquiring and outputting output data of the target distributed power supply, energy storage data of the target energy storage device and values of first target parameters based on the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device, the target constraint and the first target function which are output by the iteration planning layer model; in the first iteration, the planning layer model is further used for acquiring and outputting the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter based on the distribution information, the target constraint and the second target function of the target power distribution network.
In yet another aspect, the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the method for hybrid energy system site selection and volume sizing provided by the above methods, the method comprising: in the iteration, outputting data of a target distributed power supply, energy storage data of a target energy storage device and a value of a first target parameter output by a last iteration operation layer model are input into a planning layer model, position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and a value of a second target parameter output by the iteration planning layer model are obtained, the position information and capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device output by the iteration planning layer model are input into the operation layer model, and outputting data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the iteration operation layer model are obtained; under the condition that the iteration does not meet the iteration ending condition, the next iteration is carried out, under the condition that the iteration meets the iteration ending condition based on the value of the second target parameter output by the iteration planning layer model and the value of the first target parameter output by the iteration running layer model, or the accumulated iteration number, the index value of the target power distribution network is calculated and obtained based on the position information and the capacity information of the target distributed power supply output by the iteration planning layer model and the position information and the capacity information of the target energy storage device; under the condition that the evaluation index value of the target power distribution network is not greater than a preset value, determining the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the iterative planning layer model as the site selection and volume determination planning results of the target distributed power supply and the target energy storage device; the target distributed power supply is a distributed power supply to be connected to a target power distribution network, and the target energy storage device is an energy storage device to be connected to the target power distribution network; in the iteration, the planning layer model is used for acquiring and outputting position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and values of second target parameters based on output data of the target distributed power supply, energy storage data of the target energy storage device, distribution information of the target power distribution network, target constraint and a second target function which are output by the previous iteration operation layer model; in the iteration, the operation layer model is used for acquiring and outputting output data of the target distributed power supply, energy storage data of the target energy storage device and values of first target parameters based on the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device, the target constraint and the first target function which are output by the iteration planning layer model; in the first iteration, the planning layer model is further used for acquiring and outputting the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter based on the distribution information, the target constraint and the second target function of the target power distribution network.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. The method is characterized in that the hybrid energy system comprises a distributed power supply and an energy storage device, and the energy storage device comprises a virtual energy storage device;
the method comprises the following steps:
in the iteration, outputting data of a target distributed power supply, energy storage data of a target energy storage device and a value of a first target parameter output by a last iteration operation layer model are input into a planning layer model, position information and capacity information of the target distributed power supply, position information and capacity information of the target energy storage device and a value of a second target parameter output by the planning layer model in the iteration are obtained, the position information and capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device output by the planning layer model in the iteration are input into the operation layer model, and outputting data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the operation layer model in the iteration are obtained;
And performing the next iteration under the condition that the iteration does not meet the iteration ending condition based on the value of the second target parameter output by the planning layer model of the iteration, the value of the first target parameter output by the operation layer model of the iteration or the accumulated iteration times,
under the condition that the iteration meets the iteration ending condition based on the value of the second target parameter output by the planning layer model of the iteration and the value of the first target parameter output by the operation layer model of the iteration or the accumulated iteration times, calculating to obtain an evaluation index value of the target power distribution network based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the planning layer model of the iteration;
under the condition that the evaluation index value of the target power distribution network is not greater than a preset value, determining the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device which are output by the planning layer model in the iteration at this time as the site selection and volume fixation planning results of the target distributed power supply and the target energy storage device;
The target distributed power supply is a distributed power supply to be connected to a target power distribution network, and the target energy storage device is an energy storage device to be connected to the target power distribution network;
in this iteration, the planning layer model is configured to obtain and output, based on output data of the target distributed power source and energy storage data of the target energy storage device, distribution information of the target power distribution network, target constraint, and a second target function output by the previous iteration of the operation layer model, position information and capacity information of the target distributed power source, position information and capacity information of the target energy storage device, and a value of the second target parameter;
in the iteration, the operation layer model is used for acquiring and outputting output data of the target distributed power supply, energy storage data of the target energy storage device and values of the first target parameters based on the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device, the target constraint and the first target function which are output by the planning layer model in the iteration;
in the first iteration, the planning layer model is further configured to obtain and output, based on only the distribution information of the target distribution network, the target constraint, and the second objective function, the position information and capacity information of the target distribution power source, the position information and capacity information of the target energy storage device, and the value of the second objective parameter.
2. The hybrid energy system site selection and volume sizing method according to claim 1, wherein the evaluation index is used for evaluating voltage floating conditions in the target power distribution network;
the calculating, based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device output by the planning layer model in the iteration, an evaluation index value of the target power distribution network includes:
calculating the voltage of each node in the target power distribution network based on the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device, which are output by the planning layer model in the iteration;
and calculating an evaluation index value of the target power distribution network based on the voltage of each node and the total number of the nodes in the target power distribution network.
3. The method for planning the location and the volume of the hybrid energy system according to claim 1, wherein in the iteration, the output data of the target distributed power source, the energy storage data of the target energy storage device and the value of the first target parameter output by the previous iteration operation layer model are input into the planning layer model, and the position information and the capacity information of the target distributed power source, the position information and the capacity information of the target energy storage device and the value of the second target parameter output by the planning layer model in the iteration are obtained, which comprises the following steps:
In the iteration, output data of a target distributed power supply, energy storage data of a target energy storage device and a value of a first target parameter output by a last iteration operation layer model are input into a planning layer model, the planning layer model calculates and obtains position information and capacity information of the target distributed power supply and position information and capacity information of the target energy storage device by using a particle swarm algorithm based on the output data of the target distributed power supply, the energy storage data of the target energy storage device and the target constraint output by the operation layer model of the last iteration, and the output data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the operation layer model of the last iteration are brought into the second target function, and the value of the second target parameter is calculated and obtained, so that the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter output by the planning layer model of the current iteration are obtained.
4. The hybrid energy system site selection and volume sizing method of claim 1, wherein the first target parameter comprises an annual operating cost of the target power distribution grid.
5. The hybrid energy system site selection and volume sizing method of claim 1, wherein the second target parameter comprises an annual cost of the target power distribution grid.
6. The hybrid energy system site selection and volume determination planning method according to any one of claims 1 to 5, wherein the target constraint comprises: node voltage constraints, branch current constraints, capacity constraints of the distributed power supply at the to-be-accessed node, load power constraints of the virtual energy storage device, capacity constraints of the distributed power supply, node power flow constraints, and power balance constraints of the power distribution network.
7. The mixed energy system locating and sizing planning device is characterized in that the mixed energy system comprises a distributed power supply and an energy storage device, and the energy storage device comprises a virtual energy storage device;
the device comprises:
the iteration calculation module is used for inputting the output data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the operation layer model of the previous iteration into a planning layer model in the current iteration, acquiring the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device and the value of the second target parameter output by the planning layer model of the current iteration, inputting the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device output by the planning layer model of the current iteration into the operation layer model, and acquiring the output data of the target distributed power supply, the energy storage data of the target energy storage device and the value of the first target parameter output by the operation layer model of the current iteration;
The index calculation module is used for carrying out the next iteration under the condition that the value of the second target parameter output by the planning layer model of the current iteration, the value of the first target parameter output by the operation layer model of the current iteration or the accumulated iteration number is determined to not meet the iteration end condition, and calculating to obtain the evaluation index value of the target power distribution network under the condition that the value of the second target parameter output by the planning layer model of the current iteration and the value of the first target parameter output by the operation layer model of the current iteration or the accumulated iteration number is determined to meet the iteration end condition based on the position information and the capacity information of the target distributed power supply output by the planning layer model of the current iteration and the position information and the capacity information of the target energy storage device;
the result output module is used for determining the position information and the capacity information of the target distributed power supply and the position information and the capacity information of the target energy storage device which are output by the planning layer model in the iteration at this time as the site-selection and volume-fixation planning results of the target distributed power supply and the target energy storage device under the condition that the evaluation index value of the target power distribution network is not greater than a preset value;
The target distributed power supply is a distributed power supply to be connected to a target power distribution network, and the target energy storage device is an energy storage device to be connected to the target power distribution network;
in this iteration, the planning layer model is configured to obtain and output, based on output data of the target distributed power source and energy storage data of the target energy storage device, distribution information of the target power distribution network, target constraint, and a second target function output by the previous iteration of the operation layer model, position information and capacity information of the target distributed power source, position information and capacity information of the target energy storage device, and a value of the second target parameter;
in the iteration, the operation layer model is used for acquiring and outputting output data of the target distributed power supply, energy storage data of the target energy storage device and values of the first target parameters based on the position information and the capacity information of the target distributed power supply, the position information and the capacity information of the target energy storage device, the target constraint and the first target function which are output by the planning layer model in the iteration;
in the first iteration, the planning layer model is further configured to obtain and output, based on only the distribution information of the target distribution network, the target constraint, and the second objective function, the position information and capacity information of the target distribution power source, the position information and capacity information of the target energy storage device, and the value of the second objective parameter.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the hybrid energy system site selection and volume planning method of any one of claims 1 to 6 when the program is executed by the processor.
9. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the hybrid energy system site selection and volume sizing method according to any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the hybrid energy system site-specific volume planning method according to any one of claims 1 to 6.
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