CN117852927A - Source network charge storage integrated planning production simulation method, system and storage medium - Google Patents
Source network charge storage integrated planning production simulation method, system and storage medium Download PDFInfo
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Abstract
The invention discloses a source network charge storage integrated planning production simulation method, a system and a storage medium, and belongs to the technical field of new energy power system production simulation. The invention considers the load, power supply and adjustable resource characteristics of the source network load storage system in the input parameters, adds the limit of peak-valley difference in the constraint condition, adds the judgment of whether the peak-valley difference meets the standard in the production simulation process, and gives the values of the load inherent peak-valley difference, daily external net load peak-valley difference, power rejection rate and the like of the source network load storage system in the obtained key indexes. Therefore, the load, the power supply and the adjustable resource characteristics of the source network load storage system can be covered, the power supply scale and the proportion are measured and calculated under the constraint condition of ensuring peak-valley difference, the project power and electricity balance and new energy consumption are ensured, and the integral planning of the source network load storage integrated project is supported. The method solves the technical problem that the existing new energy power system production simulation method cannot be directly applied to the source network charge storage integrated project.
Description
Technical Field
The invention relates to the technical field of production simulation of new energy power systems, in particular to a source network charge storage integrated planning production simulation method, a system and a storage medium.
Background
The traditional power system production simulation is calculated based on the operation characteristics of conventional power stations such as thermal power stations, hydroelectric power stations and nuclear power stations, and cannot adapt to the actual scene of large-scale new energy power supply access, the calculation result cannot reflect the actual operation condition of a power grid, and the problem of the increase of the operation cost of conventional units occurs. In a power system with large-scale access of new energy, research on power system production simulation is divided into two situations of power system random production simulation and power system time sequence production simulation.
The random production simulation of the electric power system refers to that in the running process of the electric power system, factors such as random outage, random fluctuation of load, random fluctuation of new energy output and the like exist in the running process of the unit, simulation calculation is carried out, reliability indexes and running plans of the system are obtained, and common methods include an analysis method, a Monte Carlo simulation method and a sequence operation method. The random production simulation only needs the system to run the output probability index of the unit, and the calculation speed is high, but the constraint of the unit and time is not fully considered in the power system accessed by new energy sources such as large-scale wind power, photovoltaic power generation and the like. The continuous load curve is adopted for operation, time sequence information is ignored, the specific operation condition of each type of unit at each moment in specific operation cannot be determined, and the operation condition of a large-scale new energy access system cannot be evaluated. Therefore, there is a need for a time series production simulation employing time series information in a high-proportion new energy power system.
The time sequence production simulation of the electric power system fully considers the time sequence characteristics of new energy output such as wind power, photovoltaic and the like, considers the new energy output, system load and the output of a conventional unit as time-varying sequences, and considers factors such as power and electricity balance of the system, system standby, peak shaving, climbing of the unit, start-stop operation of the unit, conveying capacity of a power grid and the like, so that the time-period simulation is performed, and an optimal power balance result is achieved. The basic method for the production simulation of the new energy power system mainly comprises the steps of establishing an objective function, setting conditions such as system constraint, unit output constraint and other constraints, and selecting an optimization algorithm for solving. For example, the invention patent CN108847661a discloses a annual production simulation operation method and system of a regional power system, and the method comprises the following steps: dividing the regional power system into a plurality of subsystems according to the limited tie lines, taking the minimum sum of the total power generation cost of the system and the electricity limiting penalty of the renewable energy source as an objective function, establishing an annual time sequence production simulation operation model of the regional power system, decomposing the operation model into M time periods for parallel calculation, setting overlapping periods between adjacent time periods, adopting automatic rollback solution without solution in the time periods, and combining the M time period results into an annual time sequence production simulation result.
However, when the existing new energy power system production simulation method is directly applied to the source network load storage integrated project, the problem that the method is difficult to adapt to is existed in terms of boundary conditions, control characteristics, key indexes and the like, specifically, the requirement of the source network load storage integrated project on not increasing peak-valley differences is not met, the load characteristics do not fully reflect the adjustment capability of various types of loads, and the key indexes obtained by production simulation cannot reflect whether the peak-valley differences of the source network load storage integrated project do not exceed the limit of the original load inherent peak-valley differences. Therefore, a proprietary integrated production simulation method for the source network and the charge storage is needed.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a source network charge storage integrated planning production simulation method, a system and a storage medium.
According to one aspect of the invention, there is provided a source network load storage integrated planning production simulation method, comprising:
step 1: setting basic constraint conditions and peak-valley-difference constraint conditions of a source network load storage system; the basic constraint condition is that reverse power is not transmitted to the power grid, and the peak-valley difference constraint condition is that the peak-valley difference of daily external net load of the source network load storage system is not higher than the peak-valley difference inherent to load;
Step 2: inputting basic parameters considering the load, the power supply and the adjustable resource characteristics of the source network charge storage system and the constraint conditions set in the step 1, carrying out production simulation on the source network charge storage system every moment by every day by taking the day as a unit, ensuring that the generated power and the power consumption of the source network charge storage system reach power balance at every moment, recording the power balance result of the source network charge storage system at every moment every day, and counting the daily electric quantity result and key indexes; wherein the power balance result comprises new energy power generation powerP Generating electricity Electric power for loadP Load of Stored energy charging powerP Storage and filling device Energy storage discharge powerP Storage and placement Electric power for outsourcingP Outsourcing Electric power discardingP Discarding The electricity quantity result comprises the load electricity consumptionS Load of Generating capacity of new energyS Generating electricity New energy source for absorbing electric quantityS Absorption by Electric quantity of outsourcingS Outsourcing Electric quantity of abandoningS Discarding Key index packageElectrical rate of scrapingR Discarding Peak-to-valley difference inherent to loadD Inherent to load Daily peak-to-peak-valley difference of external net load of source network load storage systemD Source network charge storage Number of times of energy storage and chargingN Storage and filling device Number of times of energy storage dischargeN Storage and placement Number of hours of wind power generationH Wind power Hours of photovoltaic power generationH Light source ；
Step 3: and (3) carrying out daily production simulation on the source network charge storage system according to the method in the step (2), carrying out statistics on power balance results, annual electric quantity results and key indexes of the source network charge storage system at all times of the year, evaluating the key indexes according to the statistics results, ensuring that the power rejection rate of the source network charge storage system is smaller than a preset threshold value, and ensuring that the peak-valley difference of the daily external payload of the source network charge storage system is not higher than the peak-valley difference of the inherent load.
Optionally, the expression of the basic constraint condition and the expression of the peak-valley difference constraint condition in the step 1 are respectively:
P discarding =P Generating electricity -P Load of -P Storage and filling device ；
D Source network charge storage ≤D Inherent to load ；
In the method, in the process of the invention,P discarding In order to discard the electric power,P generating electricity The power generated by the new energy source is used as the power,P load of The electric power is used for the load,P storage and filling device For the purpose of storing the charge power,D source network charge storage The peak-valley difference of the daily external payload for the source network load storage system,D inherent to load Is the load inherent peak-valley difference.
Optionally, the step 2 of inputting considers the load of the source network charge storage system, the power supply, the basic parameters of the adjustable resource characteristics and the constraint conditions set in the step 1, performs production simulation on the source network charge storage system one by one time in a daily unit, ensures that the generated power and the used power of the source network charge storage system reach power balance at each time, then records the power balance result of the source network charge storage system at each time every day, and counts the electric quantity result and key indexes of the source network charge storage system every day, including:
step 21: determining basic operation parameters of the source network charge storage system on the ith day according to an actual load electricity utilization curve, an actual power supply power generation curve and adjustable resource characteristic parameters of the source network charge storage system on the ith day, taking the basic operation parameters as input data of production simulation, and carrying out production simulation calculation of the source network charge storage system based on the constraint conditions set in the step 1; wherein the adjustable resource characteristic parameter comprises a minimum adjustable coefficient of a part of adjustable load in the load K min Maximum adjustable coefficientK max And stored charge-discharge powerP Storage device Number of hoursH Storage device Capacity ofS Storage device The method comprises the steps of carrying out a first treatment on the surface of the Basic operation parameters are the power supply power, fixed load power, energy storage power and the power upper limit of the adjustable load at each momentP Adjustable max Lower power limitP Adjustable min ；
Step 22: counting the power of the non-adjustable resources in the source network load storage system on the ith day one by one; wherein the non-adjustable resource comprises fixed load power which can not participate in adjustmentP Load fixing Wind powerP Wind power generation And photovoltaic powerP Photovoltaic device ；
Step 23: judging whether a source network charge storage system at each moment on the ith day reaches power balance or not according to the power statistics result of the step 22; if there is surplus power at a certain momentδP + I.e.δP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Adjustable min ）>0, the power consumption of the adjustable load at the moment is increasedP Load-adjustable =min（P Adjustable min +δP + ，P Adjustable max ) If the power surplus exists after the adjustable load is lifted to reach the maximum limit, the adjustable load is charged according to the charging powerP Storage and filling device Charging the stored energy; if there is a shortage of power at a certain timeδP - I.e.δP - =P Load fixing +P Adjustable min -（P Wind power generation +P Photovoltaic device ) According to the discharge powerP Storage and placement Discharging the stored energy; when the source network charge storage system does not have surplus power and shortage power, the power balance is achieved;
Step 24: taking the adjustable load and energy storage in the step 23 into consideration, further judging whether the source network load storage system at each moment of the ith day reaches electric power balance or not; if there is surplus power at a certain moment, i.eδP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement ) The outsourcing power is needed, and the maximum outsourcing power requirement of the source network charge storage system on the current day is calculatedP Outsourcing max =P Load max -P Generating electricity min And calculate the load inherent peak-valley differenceD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) Calculating the minimum outsourcing power demand of the source network charge storage system on the current day according to the maximum outsourcing power demand and the load inherent peak-valley differenceP Outsourcing min =P Outsourcing max -D Inherent to load The method comprises the steps of carrying out a first treatment on the surface of the Wherein,P load max At the maximum value of the load power,P generating electricity min The minimum power is generated for the power supply;
step 25: minimum outsourcing power requirements at step 24P Outsourcing min As outsourcing power valuesP Outsourcing Inputting the power source network charge storage system, and judging whether the power source network charge storage system at each moment on the ith day reaches power balance or not again; if there is surplus of electric power, i.e δP + =P Wind power generation +P Photovoltaic device +P Outsourcing -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement +P Outsourcing ) Adding an outsourcing power value and inputting the outsourcing power value into the source network charge storage system until the source network charge storage system reaches power balance;
step 26: on the basis of power balance at each moment of the ith day in the step 25, the peak-valley difference of the external net load of the daily source network load storage system is countedD Source network charge storage =P Outsourcing peak -P Outsourcing cereal Judging whether the peak-valley difference of the external net load of the solar source network load storage system is smaller than or equal to the peak-valley difference of the load inherentD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) The method comprises the steps of carrying out a first treatment on the surface of the If it isD Source network charge storage ≤D Inherent to load Then carrying out production simulation calculation on the (i+1) th day; otherwise, the outsourcing power value at each moment on the ith day is required to be adjusted and input into the source network load storage system again, and the step 25 is repeated until the peak-valley difference of the external net load of the source network load storage system on the ith day is smaller than or equal to the peak-valley difference of the load inherent to the source network load storage system; wherein,P outsourcing peak The actual outsourcing power maximum after the power balance is reached for the daily production simulation, P Outsourcing cereal The actual outsourcing power minimum value after the power balance is achieved for the daily production simulation;
step 27: and recording the power balance result of the source network charge storage system at each time every day, and counting the daily electric quantity result and key indexes.
Optionally, the preset threshold of the power rejection rate in step 3 is 10%.
According to another aspect of the present invention, there is provided a source network load storage integrated planning production simulation system, including:
the constraint condition setting module is used for setting basic constraint conditions and peak-valley difference constraint conditions of the source network charge storage system; the basic constraint condition is that reverse power is not transmitted to the power grid, and the peak-valley difference constraint condition is that the peak-valley difference of daily external net load of the source network load storage system is not higher than the peak-valley difference inherent to load;
the time-by-time production simulation module is used for carrying out time-by-time production simulation on the source network charge storage system by taking a day as a unit based on the constraint condition set by the constraint condition setting module, ensuring that the generated power and the power consumption of each time of the source network charge storage system reach power balance, and then recording the power balance result of each time of the source network charge storage system every day, and counting the daily electric quantity result and key indexes; wherein the power balance result comprises new energy power generation power P Generating electricity Electric power for loadP Load of Stored energy charging powerP Storage and filling device Energy storage discharge powerP Storage and placement Electric power for outsourcingP Outsourcing Electric power discardingP Discarding The electricity quantity result comprises the load electricity consumptionS Load of Generating capacity of new energyS Generating electricity New energy source for absorbing electric quantityS Absorption by Electric quantity of outsourcingS Outsourcing Electric quantity of abandoningS Discarding The key index comprises the power rejection rateR Discarding Peak-to-valley difference inherent to loadD Inherent to load Daily peak-to-peak-valley difference of external net load of source network load storage systemD Source network charge storage Number of times of energy storage and chargingN Storage and filling device Number of times of energy storage dischargeN Storage and placement Number of hours of wind power generationH Wind power Hours of photovoltaic power generationH Light source ；
The daily production simulation module is used for carrying out daily production simulation on the source network charge storage system all the year round according to the operation of the production simulation module all the time, counting the power balance result, the electric quantity result and the key index of the source network charge storage system all the time all the year round, evaluating the key index according to the counting result, ensuring that the power rejection rate of the source network charge storage system is smaller than a preset threshold value, and ensuring that the peak-valley difference of the daily external net load of the source network charge storage system is not higher than the inherent peak-valley difference of the load.
Optionally, the expressions of the basic constraint and the expressions of the peak-valley difference constraint are respectively:
P Discarding =P Generating electricity -P Load of -P Storage and filling device ；
D Source network charge storage ≤D Inherent to load ；
In the method, in the process of the invention,P discarding In order to discard the electric power,P generating electricity The power generated by the new energy source is used as the power,P load of The electric power is used for the load,P storage and filling device For the purpose of storing the charge power,D source network charge storage The peak-valley difference of the daily external payload for the source network load storage system,D inherent to load Is the load inherent peak-valley difference.
Optionally, the simulation module is produced time by time, in particular for:
determining basic operation parameters of the source network charge storage system on the ith day according to an actual load electricity utilization curve, an actual power supply power generation curve and adjustable resource characteristic parameters of the source network charge storage system on the ith day, taking the basic operation parameters as input data of production simulation, and carrying out production simulation calculation of the source network charge storage system based on the constraint conditions set in the step 1; wherein the adjustable resource characteristic parameter comprises a minimum adjustable coefficient of a part of adjustable load in the loadK min Maximum adjustable coefficientK max And stored charge-discharge powerP Storage device Number of hoursH Storage device Capacity ofS Storage device The method comprises the steps of carrying out a first treatment on the surface of the Basic operation parameters are the power supply power, fixed load power, energy storage power and the power upper limit of the adjustable load at each momentP Adjustable max Lower power limitP Adjustable min ；
Counting the power of the non-adjustable resources in the source network load storage system on the ith day one by one; wherein the non-adjustable resource comprises fixed load power which can not participate in adjustment P Load fixing Wind powerP Wind power generation And photovoltaic powerP Photovoltaic device ；
Judging the source of each moment of the ith day according to the power statistical resultWhether the network charge storage system reaches electric power balance or not; if there is surplus power at a certain momentδP + I.e.δP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Adjustable min ）>0, the power consumption of the adjustable load at the moment is increasedP Load-adjustable =min（P Adjustable min +δP + ，P Adjustable max ) If the power surplus exists after the adjustable load is lifted to reach the maximum limit, the adjustable load is charged according to the charging powerP Storage and filling device Charging the stored energy; if there is a shortage of power at a certain timeδP - I.e.δP - =P Load fixing +P Adjustable min -（P Wind power generation +P Photovoltaic device ) According to the discharge powerP Storage and placement Discharging the stored energy; when the source network charge storage system does not have surplus power and shortage power, the power balance is achieved;
after the adjustable load and the energy storage are considered, whether a source network load storage system at each moment on the ith day reaches electric power balance is further judged; if there is surplus power at a certain moment, i.eδP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement ) The outsourcing power is needed, and the maximum outsourcing power requirement of the source network charge storage system on the current day is calculatedP Outsourcing max =P Load max -P Generating electricity min And calculate the load inherent peak-valley differenceD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) According to the maximum outsourcing power demand and loadInherent peak-valley difference calculation method for minimum outsourcing power demand of source network charge storage system on current dayP Outsourcing min =P Outsourcing max -D Inherent to load The method comprises the steps of carrying out a first treatment on the surface of the Wherein,P load max At the maximum value of the load power,P generating electricity min The minimum power is generated for the power supply;
with minimum outsourcing power requirementsP Outsourcing min As outsourcing power valuesP Outsourcing Inputting the power source network charge storage system, and judging whether the power source network charge storage system at each moment on the ith day reaches power balance or not again; if there is surplus of electric power, i.eδP + =P Wind power generation +P Photovoltaic device +P Outsourcing -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement +P Outsourcing ) Adding an outsourcing power value and inputting the outsourcing power value into the source network charge storage system until the source network charge storage system reaches power balance;
based on the power balance at each moment of the ith day, the peak-valley difference of the external payload of the daily source network load storage system is counted D Source network charge storage =P Outsourcing peak -P Outsourcing cereal Judging whether the peak-valley difference of the external net load of the solar source network load storage system is smaller than or equal to the peak-valley difference of the load inherentD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) The method comprises the steps of carrying out a first treatment on the surface of the If it isD Source network charge storage ≤D Inherent to load Then carrying out production simulation calculation on the (i+1) th day; otherwise, the outsourcing power value at each moment on the ith day is required to be adjusted and the outsourcing power value is input into the source network load storage system again, and the step 25 is repeated until the peak-valley difference of the outsourcing net load of the source network load storage system on the ith day is smaller than or equal to the loadIntrinsic peak-valley difference; wherein,P outsourcing peak The actual outsourcing power maximum after the power balance is reached for the daily production simulation,P outsourcing cereal The actual outsourcing power minimum value after the power balance is achieved for the daily production simulation;
and recording the power balance result of the source network charge storage system at each time every day, and counting the daily electric quantity result and key indexes.
Optionally, the preset threshold of the reject rate is 10%.
According to a further aspect of the present invention there is provided a computer readable storage medium storing a computer program for performing the method according to any one of the above aspects of the present invention.
According to still another aspect of the present invention, there is provided an electronic device including: a processor; a memory for storing the processor-executable instructions; the processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the method according to any one of the above aspects of the present invention.
The invention firstly considers the load, power supply and adjustable resource characteristics of the source network charge storage system in the input parameters, secondly adds the limit of peak-valley difference in the constraint condition, namely the peak-valley difference of the daily external net load of the source network charge storage system is not higher than the peak-valley difference of the load inherent in the source network charge storage system, and finally adds the judgment of whether the peak-valley difference reaches the standard in the production simulation process, and finally gives the peak-valley difference of the load inherent in the source network charge storage system in the obtained key indexD Inherent to load Peak-valley difference of daily external net loadD Source network charge storage Electric power rejection rateR Discarding Equal values. The invention can cover the load, power supply and adjustable resource characteristics of the source network load storage system, can adjust various types of load adjustment capacity, calculates the power supply scale and the proportion under the constraint condition of ensuring peak-valley difference, ensures the balance of project power and electric quantity and new energy consumption, and supports the integral planning of the source network load storage integrated project. Therefore, the technical problem that the existing new energy power system production simulation method cannot be directly applied to the source network charge storage integrated project is solved.
Drawings
Exemplary embodiments of the present invention may be more completely understood in consideration of the following drawings:
FIG. 1 is a schematic flow chart of a source network load storage integrated planning production simulation method according to an exemplary embodiment of the present invention;
fig. 2 is a schematic structural diagram of a source network load storage integrated planning production simulation system according to an embodiment of the present invention;
fig. 3 is a structure of an electronic device provided in an exemplary embodiment of the present invention.
Detailed Description
Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present invention and not all embodiments of the present invention, and it should be understood that the present invention is not limited by the example embodiments described herein.
It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.
It will be appreciated by those of skill in the art that the terms "first," "second," etc. in embodiments of the present invention are used merely to distinguish between different steps, devices or modules, etc., and do not represent any particular technical meaning nor necessarily logical order between them.
It should also be understood that in embodiments of the present invention, "plurality" may refer to two or more, and "at least one" may refer to one, two or more.
It should also be appreciated that any component, data, or structure referred to in an embodiment of the invention may be generally understood as one or more without explicit limitation or the contrary in the context.
In addition, the term "and/or" in the present invention is merely an association relationship describing the association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist together, and B exists alone. In the present invention, the character "/" generally indicates that the front and rear related objects are an or relationship.
It should also be understood that the description of the embodiments of the present invention emphasizes the differences between the embodiments, and that the same or similar features may be referred to each other, and for brevity, will not be described in detail.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the techniques, methods, and apparatus should be considered part of the specification.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Embodiments of the invention are operational with numerous other general purpose or special purpose computing system environments or configurations with electronic devices, such as communications terminals, computer systems, servers, etc. Examples of well known communication terminals, computing systems, environments, and/or configurations that may be suitable for use with electronic devices, such as communication terminals, computer systems, servers, and the like, include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the foregoing, and the like.
Electronic devices such as communication terminals, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
Key term interpretation:
power system production simulation (Power System Production Simulation): a method for determining system production indexes such as generating capacity, production cost and marginal price of each power plant in an optimal operation mode by optimizing the production condition of a generator set and simulating the scheduling operation of a system and meeting load requirements.
Source network load-store integration (Source-network-load-storage Integration): the running mode and technology capable of realizing the maximum utilization of energy resources are based on the technologies of energy Internet, modern information communication, big data, artificial intelligence, energy storage and the like, and various energy storage is reasonably configured by optimizing and integrating local power source side, power grid side and load side resources, so that coordinated interaction among links of the power source network and the load storage is realized, and the power dynamic balance capacity of the power system is improved more economically, efficiently and safely.
Electric power and electric quantity balance: (Power and Energy Balance): the supply and demand balance of electric power and electric quantity in the electric power system is essentially the adequacy problem of system installation capacity planning, and when new energy is abandoned due to insufficient system peak regulation, a proper amount of pumping and storing and energy storage are required to be configured.
Peak-to-valley difference (Peak-valley Difference): the difference between the highest load and the lowest load is counted in the statistical time interval.
Peak Gu Chalv (Rate of Peak-valley Difference): peak to valley difference to peak load ratio.
The invention provides a source network charge storage integrated planning production simulation method, a system and a storage medium. Fig. 1 is a schematic flow chart of a source network load storage integrated planning production simulation method according to an exemplary embodiment of the present invention. As shown in fig. 1, the source network load storage integrated planning production simulation method includes:
step 1: setting basic constraint conditions and peak-valley-difference constraint conditions of a source network load storage system; the basic constraint condition is that reverse power is not transmitted to the power grid, and the peak-valley difference constraint condition is that the peak-valley difference of daily external net load of the source network load storage system is not higher than the peak-valley difference inherent to load;
optionally, the expression of the basic constraint condition and the expression of the peak-valley difference constraint condition in the step 1 are respectively:
P Discarding =P Generating electricity -P Load of -P Storage and filling device ；
D Source network charge storage ≤D Inherent to load ；
In the method, in the process of the invention,P discarding In order to discard the electric power,P generating electricity The power generated by the new energy source is used as the power,P load of The electric power is used for the load,P storage and filling device For the purpose of storing the charge power,D source network charge storage The peak-valley difference of the daily external payload for the source network load storage system,D inherent to load Is the load inherent peak-valley difference.
According to the remarkable characteristics that the peak-valley difference rate of the source network load-storage integrated project is not higher than the natural peak-valley difference rate of the load, the source network load-storage integrated planning production simulation method considering peak-valley difference constraint is provided, namely, the daily external net load peak-valley difference of a source network load storage system is not higher than the inherent peak-valley difference of the load, under the constraint condition, the production simulation calculation process can fully mobilize the power load regulation capacity, promote the energy utilization efficiency and promote the new energy consumption and utilization by means of regulating and optimizing the production plan, excavating the production equipment regulation capacity, adding a storage device to a heat supply and cold supply system, arranging multiple power customers to coordinate electricity and the like.
Step 2: inputting basic parameters considering the load, power supply and adjustable resource characteristics of the source network charge storage system and the constraint conditions set in the step 1, carrying out production simulation on the source network charge storage system every moment by taking a day as a unit, and ensuring each moment of the source network charge storage system The generated power and the used power reach the power balance, then the power balance result of the source network charge storage system at each time every day is recorded, and the electric quantity result and key indexes of the day are counted; wherein the power balance result comprises new energy power generation powerP Generating electricity Electric power for loadP Load of Stored energy charging powerP Storage and filling device Energy storage discharge powerP Storage and placement Electric power for outsourcingP Outsourcing Electric power discardingP Discarding The electricity quantity result comprises the load electricity consumptionS Load of Generating capacity of new energyS Generating electricity New energy source for absorbing electric quantityS Absorption by Electric quantity of outsourcingS Outsourcing Electric quantity of abandoningS Discarding The key index comprises the power rejection rateR Discarding Peak-to-valley difference inherent to loadD Inherent to load Daily peak-to-peak-valley difference of external net load of source network load storage systemD Source network charge storage Number of times of energy storage and chargingN Storage and filling device Number of times of energy storage dischargeN Storage and placement Number of hours of wind power generationH Wind power Hours of photovoltaic power generationH Light source 。
In the embodiment of the invention, the adjustment capability and the adjustment characteristic of various types of loads are reflected in the input parameters, namely, the various types of loads such as polysilicon, big data, chemical industry, electrolytic aluminum, hydrogen production and the like at present are realized by setting the respective maximum adjustment coefficientsKmax, minimum adjustment coefficient Kmin, adjust timingTi. Adjusting rateSEtc.
Optionally, the step 2 of inputting considers the load of the source network charge storage system, the power supply, the basic parameters of the adjustable resource characteristics and the constraint conditions set in the step 1, performs production simulation on the source network charge storage system one by one time in a daily unit, ensures that the generated power and the used power of the source network charge storage system reach power balance at each time, then records the power balance result of the source network charge storage system at each time every day, and counts the electric quantity result and key indexes of the source network charge storage system every day, including:
step 21: according to the actual load electricity utilization curve of the ith day of the source network charge storage system, the actual power supply power generation curve,The method comprises the steps of adjusting resource characteristic parameters, determining basic operation parameters of a source network charge storage system on the ith day, taking the basic operation parameters as input data of production simulation, and carrying out production simulation calculation of the source network charge storage system based on constraint conditions set in the step 1; wherein the adjustable resource characteristic parameter comprises a minimum adjustable coefficient of a part of adjustable load in the loadK min Maximum adjustable coefficientK max And stored charge-discharge powerP Storage device Number of hoursH Storage device Capacity ofS Storage device The method comprises the steps of carrying out a first treatment on the surface of the Basic operation parameters are the power supply power, fixed load power, energy storage power and the power upper limit of the adjustable load at each moment P Adjustable max Lower power limitP Adjustable min ；
Step 22: counting the power of the non-adjustable resources in the source network load storage system on the ith day one by one; wherein the non-adjustable resource comprises fixed load power which can not participate in adjustmentP Load fixing Wind powerP Wind power generation And photovoltaic powerP Photovoltaic device ；
Step 23: judging whether a source network charge storage system at each moment on the ith day reaches power balance or not according to the power statistics result of the step 22; if there is surplus power at a certain momentδP + I.e.δP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Adjustable min ）>0, the power consumption of the adjustable load at the moment is increasedP Load-adjustable =min（P Adjustable min +δP + ，P Adjustable max ) If the power surplus exists after the adjustable load is lifted to reach the maximum limit, the adjustable load is charged according to the charging powerP Storage and filling device Charging the stored energy; if there is a shortage of power at a certain timeδP - I.e.δP - =P Load fixing +P Adjustable min -（P Wind power generation +P Photovoltaic device ) According to the discharge powerP Storage and placement Discharging the stored energy; wherein the achievement is indicated when the source network charge storage system has no surplus power and no shortage powerBalancing electric power;
step 24: taking the adjustable load and energy storage in the step 23 into consideration, further judging whether the source network load storage system at each moment of the ith day reaches electric power balance or not; if there is surplus power at a certain moment, i.e δP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement ) The outsourcing power is needed, and the maximum outsourcing power requirement of the source network charge storage system on the current day is calculatedP Outsourcing max =P Load max -P Generating electricity min And calculate the load inherent peak-valley differenceD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) Calculating the minimum outsourcing power demand of the source network charge storage system on the current day according to the maximum outsourcing power demand and the load inherent peak-valley differenceP Outsourcing min =P Outsourcing max -D Inherent to load The method comprises the steps of carrying out a first treatment on the surface of the Wherein,P load max At the maximum value of the load power,P generating electricity min The minimum power is generated for the power supply;
step 25: minimum outsourcing power requirements at step 24P Outsourcing min As outsourcing power valuesP Outsourcing Inputting the power source network charge storage system, and judging whether the power source network charge storage system at each moment on the ith day reaches power balance or not again; if there is surplus of electric power, i.eδP + =P Wind power generation +P Photovoltaic device +P Outsourcing -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded power P Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement +P Outsourcing ) Adding an outsourcing power value and inputting the outsourcing power value into the source network charge storage system until the source network charge storage system reaches power balance;
step 26: on the basis of power balance at each moment of the ith day in the step 25, the peak-valley difference of the external net load of the daily source network load storage system is countedD Source network charge storage =P Outsourcing peak -P Outsourcing cereal Judging whether the peak-valley difference of the external net load of the solar source network load storage system is smaller than or equal to the peak-valley difference of the load inherentD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) The method comprises the steps of carrying out a first treatment on the surface of the If it isD Source network charge storage ≤D Inherent to load Then carrying out production simulation calculation on the (i+1) th day; otherwise, the outsourcing power value at each moment on the ith day is required to be adjusted and input into the source network load storage system again, and the step 25 is repeated until the peak-valley difference of the external net load of the source network load storage system on the ith day is smaller than or equal to the peak-valley difference of the load inherent to the source network load storage system; wherein,P outsourcing peak The actual outsourcing power maximum after the power balance is reached for the daily production simulation,P outsourcing cereal The actual outsourcing power minimum value after the power balance is achieved for the daily production simulation;
Step 27: and recording the power balance result of the source network charge storage system at each time every day, and counting the daily electric quantity result and key indexes.
Step 3: and (3) carrying out daily production simulation on the source network charge storage system according to the method in the step (2), carrying out statistics on power balance results, annual electric quantity results and key indexes of the source network charge storage system at all times of the year, evaluating the key indexes according to the statistics results, ensuring that the power rejection rate of the source network charge storage system is smaller than a preset threshold value, and ensuring that the peak-valley difference of the daily external payload of the source network charge storage system is not higher than the peak-valley difference of the inherent load.
Optionally, the preset threshold of the power rejection rate in step 3 is 10%.
In the following, a certain source network load storage integrated project is taken as an example, and the electric load mainly comprises a rack load, an air conditioner load, a building load and a charging load, and part of the loads have adjustable capacity. The new energy is matched for power generation and energy storage, wind power, photovoltaic and novel energy storage are utilized for providing green power for loads, the deep excavation load adjusting capability participates in system peak regulation, and project carbon emission is effectively reduced.
The calculation conditions were set as follows:
(1) Scale of each element: the load comprises a 22.65 kilowatt fixed load and a 7.5 kilowatt adjustable load, and the adjustable range is 0-100%; 20 kilowatts of wind power generation and 10 kilowatts of photovoltaic power generation; the matched energy storage is 9 ten thousand kilowatts/2 hours.
(2) The constraint condition is that power is not reversely transmitted to the power grid, peak-valley difference is not increased, peak Gu Chalv is set to be 35%, and the energy storage strategy is peak regulation.
(3) The target requirement on the comprehensive utilization rate of new energy is not lower than 90%, and the electricity rejection rate is not more than 10%.
And inputting data and carrying out production simulation based on the conditions to obtain an electric power and electric quantity balance result. The new energy, load, power conditions of the off-grid electricity and other key indexes are listed through the power balance table, and are shown in table 1. The new energy electricity rejection rate of the project is 7.78%, the peak Gu Chalv is not higher than the inherent peak Gu Chalv% of load, and the requirements of the source network load storage integrated project on the comprehensive utilization rate and peak-valley difference of the new energy are met.
TABLE 1
| Project | Numerical value |
| Wind power scale (ten thousands kW) | 20 |
| Photovoltaic scale (ten thousands kW) | 10 |
| Energy storage scale (ten thousands kW) | 9 |
| Load electric quantity (Yi kWh) | 21.00 |
| Wind power generation capacity (Yi kWh) | 6.88 |
| Photovoltaic power generation (Yi kWh) | 1.66 |
| New energy generating capacity (Yi kWh) | 8.54 |
| New energy consumption electric quantity (Yi kWh) | 7.89 |
| Electric quantity of lower net (Yi kWh) | 14.01 |
| Electric quantity (Yi kWh) | 0.66 |
| Yield of electricity discarded (%) | 7.78 |
| Load inherent peak-valley difference (ten thousands kW) | 10.55 |
| System and method for controlling a systemDaily net load peak valley difference (ten thousands kW) | 7.28 |
| Number of times of energy storage and charging | 124 |
| Number of times of energy storage discharge | 156 |
| Wind power generation hours | 3442 |
In summary, the invention firstly considers the load, power supply and adjustable resource characteristics of the source network charge storage system in the input parameters, secondly adds the limit of peak-valley difference in the constraint condition, namely the peak-valley difference of the daily external net load of the source network charge storage system is not higher than the peak-valley difference of the load inherent in the source network charge storage system, and then adds the judgment of whether the peak-valley difference reaches the standard in the production simulation process, finally gives the peak-valley difference of the load inherent in the source network charge storage system in the obtained key index D Inherent to load Peak-valley difference of daily external net loadD Source network charge storage Electric power rejection rateR Discarding Equal values. The invention can cover the load, power supply and adjustable resource characteristics of the source network load storage system, can adjust various types of load adjustment capacity, calculates the power supply scale and the proportion under the constraint condition of ensuring peak-valley difference, ensures the balance of project power and electric quantity and new energy consumption, and supports the integral planning of the source network load storage integrated project. Therefore, the technical problem that the existing new energy power system production simulation method cannot be directly applied to the source network charge storage integrated project is solved.
Exemplary System
The invention also provides a source network charge storage integrated planning production simulation system, which comprises:
the constraint condition setting module is used for setting basic constraint conditions and peak-valley difference constraint conditions of the source network charge storage system; the basic constraint condition is that reverse power is not transmitted to the power grid, and the peak-valley difference constraint condition is that the peak-valley difference of daily external net load of the source network load storage system is not higher than the peak-valley difference inherent to load;
the time-by-time production simulation module is used for carrying out time-by-time production simulation on the source network charge storage system by taking a day as a unit based on the constraint condition set by the constraint condition setting module, ensuring that the generated power and the power consumption of each time of the source network charge storage system reach power balance, and then recording the power balance result of each time of the source network charge storage system every day, and counting the daily electric quantity result and key indexes; wherein the power balance result comprises new energy power generation power P Generating electricity Electric power for loadP Load of Stored energy charging powerP Storage and filling device Energy storage discharge powerP Storage and placement Electric power for outsourcingP Outsourcing Electric power discardingP Discarding The electricity quantity result comprises the load electricity consumptionS Load of Generating capacity of new energyS Generating electricity New energy source for absorbing electric quantityS Absorption by Electric quantity of outsourcingS Outsourcing Electric quantity of abandoningS Discarding The key index comprises the power rejection rateR Discarding Peak-to-valley difference inherent to loadD Inherent to load Daily peak-to-peak-valley difference of external net load of source network load storage systemD Source network charge storage Number of times of energy storage and chargingN Storage and filling device Number of times of energy storage dischargeN Storage and placement Number of hours of wind power generationH Wind power Hours of photovoltaic power generationH Light source ；
The daily production simulation module is used for carrying out daily production simulation on the source network charge storage system all the year round according to the operation of the production simulation module all the time, counting the power balance result, the electric quantity result and the key index of the source network charge storage system all the time all the year round, evaluating the key index according to the counting result, ensuring that the power rejection rate of the source network charge storage system is smaller than a preset threshold value, and ensuring that the peak-valley difference of the daily external net load of the source network charge storage system is not higher than the inherent peak-valley difference of the load.
Optionally, the expressions of the basic constraint and the expressions of the peak-valley difference constraint are respectively:
P Discarding =P Generating electricity -P Load of -P Storage and filling device ；
D Source network charge storage ≤D Inherent to load ；
In the method, in the process of the invention,P discarding In order to discard the electric power,P generating electricity The power generated by the new energy source is used as the power,P load of The electric power is used for the load,P storage and filling device For the purpose of storing the charge power,D source network charge storage The peak-valley difference of the daily external payload for the source network load storage system,D inherent to load Is the load inherent peak-valley difference.
Optionally, the simulation module is produced time by time, in particular for:
determining basic operation parameters of the source network charge storage system on the ith day according to an actual load electricity utilization curve, an actual power supply power generation curve and adjustable resource characteristic parameters of the source network charge storage system on the ith day, taking the basic operation parameters as input data of production simulation, and carrying out production simulation calculation of the source network charge storage system based on the constraint conditions set in the step 1; wherein the adjustable resource characteristic parameter comprises a minimum adjustable coefficient of a part of adjustable load in the loadK min Maximum adjustable coefficientK max And stored charge-discharge powerP Storage device Number of hoursH Storage device Capacity ofS Storage device The method comprises the steps of carrying out a first treatment on the surface of the Basic operation parameters are the power supply power, fixed load power, energy storage power and the power upper limit of the adjustable load at each momentP Adjustable max Lower power limitP Adjustable min ；
Counting the power of the non-adjustable resources in the source network load storage system on the ith day one by one; wherein the non-adjustable resource comprises fixed load power which can not participate in adjustment P Load fixing Wind powerP Wind power generation And photovoltaic powerP Photovoltaic device ；
Judging whether a source network charge storage system at each moment of the ith day reaches electric power balance or not according to the power statistical result; if there is surplus power at a certain momentδP + I.e.δP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Adjustable min ）>0, the power consumption of the adjustable load at the moment is increasedP Load-adjustable =min（P Adjustable min +δP + ，P Adjustable max ) If the power surplus exists after the adjustable load is lifted to reach the maximum limit, the adjustable load is charged according to the charging powerP Storage and filling device Charging the stored energy; if there is a shortage of power at a certain timeδP - I.e.δP - =P Load fixing +P Adjustable min -（P Wind power generation +P Photovoltaic device ) According to the discharge powerP Storage and placement Discharging the stored energy; when the source network charge storage system does not have surplus power and shortage power, the power balance is achieved;
after the adjustable load and the energy storage are considered, whether a source network load storage system at each moment on the ith day reaches electric power balance is further judged; if there is surplus power at a certain moment, i.eδP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement ) The outsourcing power is needed, and the maximum outsourcing power requirement of the source network charge storage system on the current day is calculatedP Outsourcing max =P Load max -P Generating electricity min And calculate the load inherent peak-valley differenceD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) Calculating the minimum outsourcing power demand of the source network charge storage system on the current day according to the maximum outsourcing power demand and the load inherent peak-valley differenceP Outsourcing min =P Outsourcing max -D Inherent to load The method comprises the steps of carrying out a first treatment on the surface of the Wherein,P load max At the maximum value of the load power,P generating electricity min The minimum power is generated for the power supply;
with minimum outsourcing power requirementsP Outsourcing min As outsourcing power valuesP Outsourcing Inputting the power source network charge storage system, and judging whether the power source network charge storage system at each moment on the ith day reaches power balance or not again; if there is surplus of electric power, i.eδP + =P Wind power generation +P Photovoltaic device +P Outsourcing -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement +P Outsourcing ) Adding an outsourcing power value and inputting the outsourcing power value into the source network charge storage system until the source network charge storage system reaches power balance;
based on the power balance at each moment of the ith day, the peak-valley difference of the external payload of the daily source network load storage system is counted D Source network charge storage =P Outsourcing peak -P Outsourcing cereal Judging whether the peak-valley difference of the external net load of the solar source network load storage system is smaller than or equal to the peak-valley difference of the load inherentD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) The method comprises the steps of carrying out a first treatment on the surface of the If it isD Source network charge storage ≤D Inherent to load Then carrying out production simulation calculation on the (i+1) th day; otherwise, the outsourcing power value at each moment on the ith day is required to be adjusted and input into the source network load storage system again, and the step 25 is repeated until the peak-valley difference of the external net load of the source network load storage system on the ith day is smaller than or equal to the peak-valley difference of the load inherent to the source network load storage system; wherein,P outsourcing peak For the daily warp production mouldThe actual outsourcing power maximum after power balance is intended to be reached,P outsourcing cereal The actual outsourcing power minimum value after the power balance is achieved for the daily production simulation;
and recording the power balance result of the source network charge storage system at each time every day, and counting the daily electric quantity result and key indexes.
Optionally, the preset threshold of the reject rate is 10%.
The source network charge storage integrated planning production simulation system of the embodiment of the invention corresponds to the source network charge storage integrated planning production simulation method of another embodiment of the invention, and is not described herein.
Exemplary electronic device
Fig. 3 is a structure of an electronic device provided in an exemplary embodiment of the present invention. As shown in fig. 3, the electronic device 30 includes one or more processors 31 and memory 32.
The processor 31 may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.
Memory 32 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on the computer readable storage medium that can be executed by the processor 31 to implement the methods of the software programs of the various embodiments of the present invention described above and/or other desired functions. In one example, the electronic device may further include: an input device 33 and an output device 34, which are interconnected by a bus system and/or other forms of connection mechanisms (not shown).
In addition, the input device 33 may also include, for example, a keyboard, a mouse, and the like.
The output device 34 can output various information to the outside. The output device 34 may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, etc.
Of course, only some of the components of the electronic device that are relevant to the present invention are shown in fig. 3 for simplicity, components such as buses, input/output interfaces, etc. being omitted. In addition, the electronic device may include any other suitable components depending on the particular application.
Exemplary computer program product and computer readable storage Medium
In addition to the methods and apparatus described above, embodiments of the invention may also be a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform steps in a method according to various embodiments of the invention described in the "exemplary methods" section of this specification.
The computer program product may write program code for performing operations of embodiments of the present invention in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the invention may also be a computer-readable storage medium, having stored thereon computer program instructions, which when executed by a processor, cause the processor to perform steps in a method according to various embodiments of the invention described in the "exemplary method" section of the description above.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The basic principles of the present invention have been described above in connection with specific embodiments, however, it should be noted that the advantages, benefits, effects, etc. mentioned in the present invention are merely examples and not intended to be limiting, and these advantages, benefits, effects, etc. are not to be considered as essential to the various embodiments of the present invention. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, as the invention is not necessarily limited to practice with the above described specific details.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For system embodiments, the description is relatively simple as it essentially corresponds to method embodiments, and reference should be made to the description of method embodiments for relevant points.
The block diagrams of the devices, systems, apparatuses, systems according to the present invention are merely illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, systems, apparatuses, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.
The method and system of the present invention may be implemented in a number of ways. For example, the methods and systems of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.
It is also noted that in the systems, devices and methods of the present invention, components or steps may be disassembled and/or assembled. Such decomposition and/or recombination should be considered as equivalent aspects of the present invention. The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the invention. Thus, the present invention is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the invention to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.
Claims (10)
1. The source network and charge storage integrated planning production simulation method is characterized by comprising the following steps of:
step 1: setting basic constraint conditions and peak-valley-difference constraint conditions of a source network load storage system; the basic constraint condition is that reverse power is not transmitted to the power grid, and the peak-valley difference constraint condition is that the peak-valley difference of daily external net load of the source network load storage system is not higher than the peak-valley difference inherent to load;
step 2: inputting basic parameters considering the load, the power supply and the adjustable resource characteristics of the source network charge storage system and the constraint conditions set in the step 1, carrying out production simulation on the source network charge storage system every moment by every day by taking the day as a unit, ensuring that the generated power and the power consumption of the source network charge storage system reach power balance at every moment, recording the power balance result of the source network charge storage system at every moment every day, and counting the daily electric quantity result and key indexes; wherein the power balance result comprises new energy power generation power P Generating electricity Electric power for loadP Load of Stored energy charging powerP Storage and filling device Energy storage discharge powerP Storage and placement Electric power for outsourcingP Outsourcing Electric power discardingP Discarding The electricity quantity result comprises the load electricity consumptionS Load of Generating capacity of new energyS Generating electricity New energy source for absorbing electric quantityS Absorption by Electric quantity of outsourcingS Outsourcing Electric quantity of abandoningS Discarding The key index comprises the power rejection rateR Discarding Peak-to-valley difference inherent to loadD Inherent to load Daily peak-to-peak-valley difference of external net load of source network load storage systemD Source network charge storage Number of times of energy storage and chargingN Storage and filling device Number of times of energy storage dischargeN Storage and placement Number of hours of wind power generationH Wind power Hours of photovoltaic power generationH Light source ；
Step 3: and (3) carrying out daily production simulation on the source network charge storage system according to the method in the step (2), carrying out statistics on power balance results, annual electric quantity results and key indexes of the source network charge storage system at all times of the year, evaluating the key indexes according to the statistics results, ensuring that the power rejection rate of the source network charge storage system is smaller than a preset threshold value, and ensuring that the peak-valley difference of the daily external payload of the source network charge storage system is not higher than the peak-valley difference of the inherent load.
2. The method of claim 1, wherein the expressions for the base constraint and the peak-to-valley constraint in step 1 are:
P Discarding =P Generating electricity -P Load of -P Storage and filling device ；
D Source network charge storage ≤D Inherent to load ；
In the method, in the process of the invention,P discarding In order to discard the electric power,P generating electricity The power generated by the new energy source is used as the power,P load of The electric power is used for the load,P storage and filling device For the purpose of storing the charge power,D source network charge storage For daily peak-to-peak-valley differences of the external payload of the source network payload storage system,D inherent to load Is the load inherent peak-valley difference.
3. The method of claim 1, wherein the inputting of the step 2 considers the load of the source network charge storage system, the power supply, the basic parameters of the adjustable resource characteristics and the constraint conditions set in the step 1, performs the production simulation on the source network charge storage system one by one time in a daily unit, ensures that the generated power and the used power of each time of the source network charge storage system reach the power balance, then records the power balance result of each time of the source network charge storage system every day, and counts the electric quantity result and key indexes of each day, including:
step 21: determining basic operation parameters of the source network charge storage system on the ith day according to an actual load electricity utilization curve, an actual power supply power generation curve and adjustable resource characteristic parameters of the source network charge storage system on the ith day, taking the basic operation parameters as input data of production simulation, and carrying out production simulation calculation of the source network charge storage system based on the constraint conditions set in the step 1; wherein the adjustable resource characteristic parameter comprises a minimum adjustable coefficient of a part of adjustable load in the load K min Maximum adjustable coefficientK max And stored charge-discharge powerP Storage device Number of hoursH Storage device Capacity ofS Storage device The method comprises the steps of carrying out a first treatment on the surface of the Basic operation parameters are the power supply power, fixed load power, energy storage power and the power upper limit of the adjustable load at each momentP Adjustable max Lower power limitP Adjustable min ；
Step 22: counting the power of the non-adjustable resources in the source network load storage system on the ith day one by one; wherein the non-adjustable resource comprises fixed load power which can not participate in adjustmentP Load fixing Wind powerP Wind power generation And photovoltaic powerP Photovoltaic device ；
Step 23: judging whether a source network charge storage system at each moment on the ith day reaches power balance or not according to the power statistics result of the step 22; if there is surplus power at a certain momentδP + I.e.δP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Adjustable min ）>0, the power consumption of the adjustable load at the moment is increasedP Load-adjustable =min（P Adjustable min +δP + ，P Adjustable max ) If the power surplus exists after the adjustable load is lifted to reach the maximum limit, the adjustable load is charged according to the charging powerP Storage and filling device Charging the stored energy; if there is a shortage of power at a certain timeδP - I.e.δP - =P Load fixing +P Adjustable min -（P Wind power generation +P Photovoltaic device ) According to the discharge powerP Storage and placement Discharging the stored energy; when the source network charge storage system does not have surplus power and shortage power, the power balance is achieved;
Step 24: taking the adjustable load and energy storage in the step 23 into consideration, further judging whether the source network load storage system at each moment of the ith day reaches electric power balance or not; if there is surplus power at a certain moment, i.eδP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding electricity according to the surplus of the electricity, andrecording the power of the abandoned electricityP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement ) The outsourcing power is needed, and the maximum outsourcing power requirement of the source network charge storage system on the current day is calculatedP Outsourcing max =P Load max -P Generating electricity min And calculate the load inherent peak-valley differenceD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) Calculating the minimum outsourcing power demand of the source network charge storage system on the current day according to the maximum outsourcing power demand and the load inherent peak-valley differenceP Outsourcing min =P Outsourcing max -D Inherent to load The method comprises the steps of carrying out a first treatment on the surface of the Wherein,P load max At the maximum value of the load power,P generating electricity min The minimum power is generated for the power supply;
step 25: minimum outsourcing power requirements at step 24P Outsourcing min As outsourcing power valuesP Outsourcing Inputting the power source network charge storage system, and judging whether the power source network charge storage system at each moment on the ith day reaches power balance or not again; if there is surplus of electric power, i.e δP + =P Wind power generation +P Photovoltaic device +P Outsourcing -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement +P Outsourcing ) Adding an outsourcing power value and inputting the outsourcing power value into the source network charge storage system until the source network charge storage system reaches power balance;
step 26: on the ith day of step 25Based on the power balance at each moment, the peak-valley difference of the external net load of the solar source network load storage system is countedD Source network charge storage =P Outsourcing peak -P Outsourcing cereal Judging whether the peak-valley difference of the external net load of the solar source network load storage system is smaller than or equal to the peak-valley difference of the load inherentD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) The method comprises the steps of carrying out a first treatment on the surface of the If it isD Source network charge storage ≤D Inherent to load Then carrying out production simulation calculation on the (i+1) th day; otherwise, the outsourcing power value at each moment on the ith day is required to be adjusted and input into the source network load storage system again, and the step 25 is repeated until the peak-valley difference of the external net load of the source network load storage system on the ith day is smaller than or equal to the peak-valley difference of the load inherent to the source network load storage system; wherein,P outsourcing peak The actual outsourcing power maximum after the power balance is reached for the daily production simulation, P Outsourcing cereal The actual outsourcing power minimum value after the power balance is achieved for the daily production simulation;
step 27: and recording the power balance result of the source network charge storage system at each time every day, and counting the daily electric quantity result and key indexes.
4. The method according to claim 1, wherein the predetermined threshold value of the reject ratio in step 3 is 10%.
5. The utility model provides a source net lotus stores up integration planning production analog system which characterized in that includes:
the constraint condition setting module is used for setting basic constraint conditions and peak-valley difference constraint conditions of the source network charge storage system; the basic constraint condition is that reverse power is not transmitted to the power grid, and the peak-valley difference constraint condition is that the peak-valley difference of daily external net load of the source network load storage system is not higher than the peak-valley difference inherent to load;
the time-by-time production simulation module is used for performing time-by-time production simulation on the source network charge storage system by taking a day as a unit based on the constraint condition set by the constraint condition setting module so as to ensure that each time of the source network charge storage systemThe power generation power and the power consumption power at each moment reach power balance, then the power balance result at each moment in the day of the source network charge storage system is recorded, and the power result and key indexes in the day are counted; wherein the power balance result comprises new energy power generation power P Generating electricity Electric power for loadP Load of Stored energy charging powerP Storage and filling device Energy storage discharge powerP Storage and placement Electric power for outsourcingP Outsourcing Electric power discardingP Discarding The electricity quantity result comprises the load electricity consumptionS Load of Generating capacity of new energyS Generating electricity New energy source for absorbing electric quantityS Absorption by Electric quantity of outsourcingS Outsourcing Electric quantity of abandoningS Discarding The key index comprises the power rejection rateR Discarding Peak-to-valley difference inherent to loadD Inherent to load Daily peak-to-peak-valley difference of external net load of source network load storage systemD Source network charge storage Number of times of energy storage and chargingN Storage and filling device Number of times of energy storage dischargeN Storage and placement Number of hours of wind power generationH Wind power Hours of photovoltaic power generationH Light source ；
The daily production simulation module is used for carrying out daily production simulation on the source network charge storage system all the year round according to the operation of the production simulation module all the time, counting the power balance result, the electric quantity result and the key index of the source network charge storage system all the time all the year round, evaluating the key index according to the counting result, ensuring that the power rejection rate of the source network charge storage system is smaller than a preset threshold value, and ensuring that the peak-valley difference of the daily external net load of the source network charge storage system is not higher than the inherent peak-valley difference of the load.
6. The system of claim 5, wherein the expressions for the base constraint and the peak-to-valley constraint are each:
P Discarding =P Generating electricity -P Load of -P Storage and filling device ；
D Source network charge storage ≤D Inherent to load ；
In the method, in the process of the invention,P discarding In order to discard the electric power,P generating electricity The power generated by the new energy source is used as the power,P load of The electric power is used for the load,P storage and filling device For the purpose of storing the charge power,D source network charge storage For daily peak-to-peak-valley differences of the external payload of the source network payload storage system,D inherent to load Is the load inherent peak-valley difference.
7. The system according to claim 5, characterized in that the simulation module is produced time by time, in particular for:
determining basic operation parameters of the source network charge storage system on the ith day according to an actual load electricity utilization curve, an actual power supply power generation curve and adjustable resource characteristic parameters of the source network charge storage system on the ith day, taking the basic operation parameters as input data of production simulation, and carrying out production simulation calculation of the source network charge storage system based on the constraint conditions set in the step 1; wherein the adjustable resource characteristic parameter comprises a minimum adjustable coefficient of a part of adjustable load in the loadK min Maximum adjustable coefficientK max And stored charge-discharge powerP Storage device Number of hoursH Storage device Capacity ofS Storage device The method comprises the steps of carrying out a first treatment on the surface of the Basic operation parameters are the power supply power, fixed load power, energy storage power and the power upper limit of the adjustable load at each moment P Adjustable max Lower power limitP Adjustable min ；
Counting the power of the non-adjustable resources in the source network load storage system on the ith day one by one; wherein the non-adjustable resource comprises fixed load power which can not participate in adjustmentP Load fixing Wind powerP Wind power generation And photovoltaic powerP Photovoltaic device ；
Judging whether a source network charge storage system at each moment of the ith day reaches electric power balance or not according to the power statistical result; if there is surplus power at a certain momentδP + I.e.δP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Adjustable min ）>0, the power consumption of the adjustable load at the moment is increasedP Load-adjustable =min（P Adjustable min +δP + ，P Adjustable max ) If the power surplus exists after the adjustable load is lifted to reach the maximum limit, the adjustable load is charged according to the charging powerP Storage and filling device Charging the stored energy; if there is a shortage of power at a certain timeδP - I.e.δP - =P Load fixing +P Adjustable min -（P Wind power generation +P Photovoltaic device ) According to the discharge powerP Storage and placement Discharging the stored energy; when the source network charge storage system does not have surplus power and shortage power, the power balance is achieved;
after the adjustable load and the energy storage are considered, whether a source network load storage system at each moment on the ith day reaches electric power balance is further judged; if there is surplus power at a certain moment, i.eδP + =P Wind power generation +P Photovoltaic device -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.eδP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement ) The outsourcing power is needed, and the maximum outsourcing power requirement of the source network charge storage system on the current day is calculatedP Outsourcing max =P Load max -P Generating electricity min And calculate the load inherent peak-valley differenceD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) Calculating the minimum outsourcing power demand of the source network charge storage system on the current day according to the maximum outsourcing power demand and the load inherent peak-valley differenceP Outsourcing min =P Outsourcing max -D Inherent to load The method comprises the steps of carrying out a first treatment on the surface of the Wherein,P load max For work loadThe maximum value of the rate at which the data is to be processed,P generating electricity min The minimum power is generated for the power supply;
with minimum outsourcing power requirementsP Outsourcing min As outsourcing power valuesP Outsourcing Inputting the power source network charge storage system, and judging whether the power source network charge storage system at each moment on the ith day reaches power balance or not again; if there is surplus of electric power, i.eδP + =P Wind power generation +P Photovoltaic device +P Outsourcing -（P Load fixing +P Load-adjustable +P Storage and filling device ）>0, discarding power according to the surplus of the power, and recording the discarded powerP Discarding =δP + And accumulated electric quantityS Discarding The method comprises the steps of carrying out a first treatment on the surface of the If there is a shortage of electric power, i.e δP - =P Load fixing +P Load-adjustable -（P Wind power generation +P Photovoltaic device +P Storage and placement +P Outsourcing ) Adding an outsourcing power value and inputting the outsourcing power value into the source network charge storage system until the source network charge storage system reaches power balance;
based on the power balance at each moment of the ith day, the peak-valley difference of the external payload of the daily source network load storage system is countedD Source network charge storage =P Outsourcing peak -P Outsourcing cereal Judging whether the peak-valley difference of the external net load of the solar source network load storage system is smaller than or equal to the peak-valley difference of the load inherentD Inherent to load =max（P Load fixing +P Load-adjustable ）-min（P Load fixing +P Load-adjustable ) The method comprises the steps of carrying out a first treatment on the surface of the If it isD Source network charge storage ≤D Inherent to load Then carrying out production simulation calculation on the (i+1) th day; otherwise, the outsourcing power value at each moment on the ith day is required to be adjusted and input into the source network load storage system again, and the step 25 is repeated until the peak-valley difference of the external net load of the source network load storage system on the ith day is smaller than or equal to the peak-valley difference of the load inherent to the source network load storage system; wherein,P outsourcing peak The actual outsourcing power maximum after the power balance is reached for the daily production simulation,P outsourcing cereal Real time after power balance is achieved for the daily production simulationMinimum value of the power purchased from the outside world;
and recording the power balance result of the source network charge storage system at each time every day, and counting the daily electric quantity result and key indexes.
8. The system of claim 5, wherein the predetermined threshold of electrical rejection is 10%.
9. A computer readable storage medium storing a computer program for performing the method of any one of the preceding claims 1-4.
10. An electronic device, the electronic device comprising:
a processor;
a memory for storing the processor-executable instructions;
the processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the method of any of the preceding claims 1-4.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114638125A (en) * | 2022-04-15 | 2022-06-17 | 湖北工业大学 | Complex power grid investment decision method considering source-grid-load-storage |
| CN115438851A (en) * | 2022-08-31 | 2022-12-06 | 南京理工大学 | Source network load and storage coordinated operation method considering extreme conditions |
| CN115619139A (en) * | 2022-10-11 | 2023-01-17 | 国网经济技术研究院有限公司 | Method, system, device and medium for calculating net load of source network load storage hierarchical partition |
| CN116205337A (en) * | 2022-12-29 | 2023-06-02 | 特变电工科技投资有限公司 | Annual operation evaluation method and device for source network charge storage project planning |
| CN116418020A (en) * | 2023-04-20 | 2023-07-11 | 国网青海省电力公司清洁能源发展研究院 | Energy storage configuration method for improving new energy consumption capability of provincial area |
| WO2023236450A1 (en) * | 2022-06-10 | 2023-12-14 | 国电南瑞科技股份有限公司 | Method and system for evaluating adjustable capability of electric vehicle cluster |
-
2024
- 2024-03-06 CN CN202410252696.0A patent/CN117852927B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114638125A (en) * | 2022-04-15 | 2022-06-17 | 湖北工业大学 | Complex power grid investment decision method considering source-grid-load-storage |
| WO2023236450A1 (en) * | 2022-06-10 | 2023-12-14 | 国电南瑞科技股份有限公司 | Method and system for evaluating adjustable capability of electric vehicle cluster |
| CN115438851A (en) * | 2022-08-31 | 2022-12-06 | 南京理工大学 | Source network load and storage coordinated operation method considering extreme conditions |
| CN115619139A (en) * | 2022-10-11 | 2023-01-17 | 国网经济技术研究院有限公司 | Method, system, device and medium for calculating net load of source network load storage hierarchical partition |
| CN116205337A (en) * | 2022-12-29 | 2023-06-02 | 特变电工科技投资有限公司 | Annual operation evaluation method and device for source network charge storage project planning |
| CN116418020A (en) * | 2023-04-20 | 2023-07-11 | 国网青海省电力公司清洁能源发展研究院 | Energy storage configuration method for improving new energy consumption capability of provincial area |
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