CN115425664A - Power distribution network electric quantity balancing method considering energy storage configuration and demand side management - Google Patents

Power distribution network electric quantity balancing method considering energy storage configuration and demand side management Download PDF

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CN115425664A
CN115425664A CN202210927187.4A CN202210927187A CN115425664A CN 115425664 A CN115425664 A CN 115425664A CN 202210927187 A CN202210927187 A CN 202210927187A CN 115425664 A CN115425664 A CN 115425664A
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load
power
energy storage
distribution network
power distribution
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Inventor
刘金森
罗宁
曹毅
梁宇
陈青
张彦
张裕
黄豫
贺红艳
陈露东
肖天颖
李庆生
张鹏城
刘志文
李震
郑飞
吴万军
白雪锋
贺墨琳
徐常
朱望
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Guizhou Power Grid Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy

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Abstract

The invention discloses a power distribution network electric quantity balancing method considering energy storage configuration and demand side management, which comprises the following steps: acquiring basic data information of the power distribution network; setting a target function and constraint conditions, and constructing a power and electricity balance model of the power distribution network considering energy storage configuration and demand side management; solving the model by adopting a branch-and-bound algorithm to obtain the minimum installation capacity of the transformer substation of the power distribution network; according to the power distribution network power and electric quantity balancing method considering energy storage configuration and demand side management, the power distribution network power and electric quantity balancing model is constructed by considering energy storage configuration and demand side management, research on the power distribution network power and electric quantity balancing method considering energy storage configuration and demand side management is achieved, and the transformer substation commissioning cost of the power distribution network is reduced.

Description

Power distribution network electric quantity balancing method considering energy storage configuration and demand side management
Technical Field
The invention relates to the technical field of power distribution networks, in particular to a power distribution network electric quantity balancing method considering energy storage configuration and demand side management.
Background
The high-proportion access of new energy represented by wind power and photovoltaic to a power distribution network can cause the problems of wind and light abandonment, voltage out-of-limit, tide reverse transmission, unreliable power supply and the like of the power distribution network, so that the power and electricity balance analysis of the power distribution network is necessary to guide the ordered access and the sufficient consumption of the new energy and reduce the investment cost of a transformer substation.
The following problems need to be considered when power distribution network electric power quantity balance analysis is carried out:
(1) Uncertainties exist in wind power, photovoltaic and load;
(2) Energy storage configuration demand side management needs to be fully considered, so that more reasonable maximum admission capacity of new energy is obtained.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The present invention has been made in view of the above-mentioned problems.
Therefore, the technical problem solved by the invention is as follows: the investment cost of the transformer substation is reduced, the requirement of fully absorbing new energy represented by wind power and photovoltaic is met, the energy utilization rate is improved, and the novel power distribution network is suitable for development.
In order to solve the technical problems, the invention provides the following technical scheme: a power distribution network electric quantity balancing method considering energy storage configuration and demand side management comprises the following steps:
acquiring basic data information of the power distribution network;
setting a target function and constraint conditions, and constructing a power and electric quantity balance model of the power distribution network considering energy storage configuration and demand side management;
and solving the model by adopting a branch-and-bound algorithm to obtain the minimum installation capacity of the transformer substation of the power distribution network.
As a preferable scheme of the power distribution network electric quantity balancing method considering energy storage configuration and demand side management, the method comprises the following steps: energy storage configuration and demand side management need to be considered in the process of constructing the power distribution network power and electricity balance model, and relevant measures are embedded into the model in a constraint mode.
As a preferable scheme of the power and electricity quantity balancing method for the power distribution network considering energy storage configuration and demand side management, the method comprises the following steps: the objective function includes: the minimum installation capacity of the transformer substation is taken as a target and expressed as follows:
Figure BDA0003780044200000021
wherein N is sub,i Counting the nodes for installing the transformer substation;
Figure BDA0003780044200000022
and newly adding the configured transformation capacity for the ith node.
As a preferable scheme of the power distribution network electric quantity balancing method considering energy storage configuration and demand side management, the method comprises the following steps: the constraint conditions include: the system comprises power and electric quantity balance, energy storage operation constraint, demand side management and distributed new energy operation constraint.
As a preferable scheme of the power distribution network electric quantity balancing method considering energy storage configuration and demand side management, the method comprises the following steps: the method comprises the following steps: the power electricity balance constraint of the power distribution network is as follows:
Figure BDA0003780044200000023
Figure BDA0003780044200000024
Figure BDA0003780044200000025
wherein,
Figure BDA0003780044200000026
and
Figure BDA0003780044200000027
the transformer substation active power output, the photovoltaic active power output and the fan active power output of a t-time node i are respectively;
Figure BDA0003780044200000028
the load active demand of the node i at the moment t is obtained;
Figure BDA0003780044200000029
and the reactive power output of the transformer substation at the node i at the time t is obtained.
As a preferable scheme of the power distribution network electric quantity balancing method considering energy storage configuration and demand side management, the method comprises the following steps: the stored energy operating constraints include: the operation of the energy storage accessed to the distribution network node i needs to satisfy the following constraints:
Figure BDA00037800442000000210
Figure BDA00037800442000000211
Figure BDA00037800442000000212
Figure BDA00037800442000000213
Figure BDA00037800442000000214
wherein,
Figure BDA00037800442000000215
and
Figure BDA00037800442000000216
respectively is energy storage charging and discharging power; 0-1 variable gamma i,t Representing the charge and discharge state of energy storage, wherein 1 is discharge and 0 is charge; p i BES The rated power of a single energy storage module;
Figure BDA0003780044200000031
energy storage capacity is obtained;
Figure BDA0003780044200000032
and
Figure BDA0003780044200000033
respectively the energy storage charging and discharging efficiency; delta t is the time length between adjacent scheduling moments; s i,max And S i,min Respectively an upper limit and a lower limit of the energy storage charge state;
Figure BDA0003780044200000034
and
Figure BDA0003780044200000035
respectively the electric quantity of the initial time and the end time of the scheduling.
As a preferable scheme of the power and electricity quantity balancing method for the power distribution network considering energy storage configuration and demand side management, the method comprises the following steps: the demand side management measures comprise load reduction and load translation; the load is composed of a basic load, a reducible load and a translatable load; the load model at time t at node i is:
Figure BDA0003780044200000036
Figure BDA0003780044200000037
wherein,
Figure BDA0003780044200000038
respectively representing the active power of the total load, the basic load, the reducible load, the reduced load and the translatable load of the node i at the moment t;
Figure BDA0003780044200000039
Figure BDA00037800442000000310
the total load, the base load, the reducible load, the reduced load and the translatable load reactive power of the node i at the time t are respectively.
As a preferable scheme of the power and electricity quantity balancing method for the power distribution network considering energy storage configuration and demand side management, the method comprises the following steps: the load shedding mathematical model is as follows:
Figure BDA00037800442000000311
Figure BDA00037800442000000312
wherein,
Figure BDA00037800442000000313
and
Figure BDA00037800442000000314
respectively the lower limit and the upper limit of the load active power reduction amount;
Figure BDA00037800442000000315
and
Figure BDA00037800442000000316
respectively the lower limit and the upper limit of the load reactive power reduction amount.
As a preferable scheme of the power distribution network electric quantity balancing method considering energy storage configuration and demand side management, the method comprises the following steps: the load translation includes:
in translatable load modeling, for translatable loads connected at node i, t is used D Indicating the number of periods during which it has been operated,
Figure BDA00037800442000000317
and
Figure BDA00037800442000000318
respectively representing the upper limit and the lower limit of the load translation time interval, the load translation starting time interval is as follows:
Figure BDA00037800442000000319
is provided with
Figure BDA00037800442000000320
Is a flag bit row vector, wherein only one element is 1, and the other elements are 0; the load state matrix is defined as follows:
Figure BDA0003780044200000041
Figure BDA0003780044200000042
wherein,
Figure BDA0003780044200000043
the sizes of the movable active load and the movable reactive load of the node i in the period j are respectively; in the translation period, the active power and the reactive power of the translatable load can be respectively used by a matrix P i fl And
Figure BDA0003780044200000044
represents:
Figure BDA0003780044200000045
Figure BDA0003780044200000046
wherein, P i fl 、
Figure BDA0003780044200000047
The sizes of the translational active load and the translational reactive load of the node i are respectively;
the active and reactive power of the translatable load are:
Figure BDA0003780044200000048
Figure BDA0003780044200000049
wherein,
Figure BDA00037800442000000410
the sizes of the translatable active load and the translatable reactive load of the node i in the t period are respectively.
As a preferable scheme of the power distribution network electric quantity balancing method considering energy storage configuration and demand side management, the method comprises the following steps: the distributed new energy operation constraints include:
Figure BDA00037800442000000411
Figure BDA00037800442000000412
Figure BDA00037800442000000413
Figure BDA00037800442000000414
wherein,
Figure BDA00037800442000000415
the power factor angles of the PVG and the WTG respectively are fixed values.
The invention has the beneficial effects that: according to the power distribution network power and electric quantity balancing method considering energy storage configuration and demand side management, the power distribution network power and electric quantity balancing model is constructed by considering energy storage configuration and demand side management, research on the power distribution network power and electric quantity balancing method considering energy storage configuration and demand side management is achieved, and the transformer substation commissioning cost of the power distribution network is reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive labor. Wherein:
fig. 1 is an overall flowchart of a power balance method for a distribution network considering energy storage configuration and demand side management according to a first embodiment of the present invention.
FIG. 2 is a Portugal 54 algorithm system in a simulation example of a power-electricity balancing method for a distribution network with consideration of energy storage configuration and demand-side management according to a second embodiment of the present invention;
fig. 3 is typical daily data of wind power, photovoltaic and load in a simulation example of a power distribution network power and electricity balance method considering energy storage configuration and demand side management according to a second embodiment of the present invention;
fig. 4 shows the wind curtailment light curtailment amounts of 4 typical days for different scenarios in a simulation example of a power distribution network power electricity balancing method considering energy storage configuration and demand side management according to a second embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced otherwise than as specifically described herein, and it will be appreciated by those skilled in the art that the present invention may be practiced without departing from the spirit and scope of the present invention and that the present invention is not limited by the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
The present invention will be described in detail with reference to the drawings, wherein the cross-sectional views illustrating the structure of the device are not necessarily enlarged to scale, and are merely exemplary, which should not limit the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation and operate, and thus, cannot be construed as limiting the present invention. Furthermore, the terms first, second, or third are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected and connected" in the present invention are to be understood broadly, unless otherwise explicitly specified or limited, for example: can be fixedly connected, detachably connected or integrally connected; they may be mechanically, electrically, or directly connected, or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Referring to the drawings, a first embodiment of the present invention provides a method for balancing power and electric quantity of a power distribution network considering energy storage configuration and demand side management, including:
s1: acquiring basic data information of the power distribution network;
furthermore, basic data information of the power distribution network is obtained to construct the power and electric quantity balance model of the power distribution network, energy storage configuration and demand side management are also required to be considered in the construction process, and relevant measures are embedded into the model in a constraint mode.
S2: setting a target function and constraint conditions, and constructing a power and electric quantity balance model of the power distribution network considering energy storage configuration and demand side management;
specifically, the objective function aims at minimizing the installation capacity of the substation, and is expressed as follows:
Figure BDA0003780044200000061
wherein N is sub,i Counting the nodes for installing the transformer substation;
Figure BDA0003780044200000062
and newly adding the configured transformation capacity for the ith node.
The constraint conditions include: the system comprises the following steps of power and electric quantity balance, energy storage operation constraint, demand side management and distributed new energy operation constraint.
Specifically, the power-electricity balance constraint of the power distribution network is as follows:
Figure BDA0003780044200000063
Figure BDA0003780044200000071
Figure BDA0003780044200000072
wherein,
Figure BDA0003780044200000073
and
Figure BDA0003780044200000074
the transformer substation active power output, the photovoltaic active power output and the fan active power output of a node i at the time t are respectively;
Figure BDA0003780044200000075
the load active demand of the node i at the moment t is obtained;
Figure BDA0003780044200000076
and the reactive power output of the transformer substation at the node i at the time t is obtained.
The stored energy operating constraints include: the operation of the stored energy accessed to the node i of the power distribution network needs to satisfy the following constraints:
Figure BDA0003780044200000077
Figure BDA0003780044200000078
Figure BDA0003780044200000079
Figure BDA00037800442000000710
Figure BDA00037800442000000711
wherein,
Figure BDA00037800442000000712
and
Figure BDA00037800442000000713
respectively is energy storage charging and discharging power; 0-1 variable gamma i,t Representing the charge and discharge state of energy storage, wherein 1 is discharge and 0 is charge; p i BES The rated power of a single energy storage module;
Figure BDA00037800442000000714
energy storage capacity is obtained;
Figure BDA00037800442000000715
and
Figure BDA00037800442000000716
respectively charging and discharging the energy storage efficiency; delta t is the time length between adjacent scheduling moments; s i,max And S i,min Respectively an upper limit and a lower limit of the energy storage charge state;
Figure BDA00037800442000000717
and
Figure BDA00037800442000000718
respectively the electric quantity at the initial time and the end time of the scheduling.
It should be noted that as socio-economic continues to steadily develop, the peak load and load peak-to-valley difference of the power system gradually increases. And the double pressure of energy crisis and environmental pollution puts forward higher requirements such as promotion of renewable energy consumption on the operation of the power distribution network in the smart cities and towns. In this context, the demand for energy storage applications is increasing, mainly due to the following: the renewable energy power generation output prediction technology cannot accurately predict renewable energy power generation output at present, so that power deviation exists between actual output and planned output of a renewable energy station, and the power deviation occupies system spare capacity. After the high-proportion renewable energy is connected to the power distribution network of the smart town, the reliability and the economy of the power system are further influenced. The energy storage technology has better performance in the aspects of reducing power deviation, improving the consumption capability of renewable energy power generation and the like, and is widely concerned by academia and industry. The method of the present invention takes into account energy storage operation constraints.
The demand side management measures comprise load reduction and load translation; the load is composed of a basic load, a reducible load and a translatable load; the load model at time t at node i is:
Figure BDA0003780044200000081
Figure BDA0003780044200000082
wherein,
Figure BDA0003780044200000083
respectively representing the active power of the total load, the basic load, the reducible load, the reduced load and the translatable load of the node i at the moment t;
Figure BDA0003780044200000084
Figure BDA0003780044200000085
the total load, the basic load, the reducible load and the reduced load of the node i at the time tLoad and translatable load reactive power.
The load shedding mathematical model is as follows:
Figure BDA0003780044200000086
Figure BDA0003780044200000087
wherein,
Figure BDA0003780044200000088
and
Figure BDA0003780044200000089
respectively the lower limit and the upper limit of the load active power reduction amount;
Figure BDA00037800442000000810
and
Figure BDA00037800442000000811
respectively the lower limit and the upper limit of the load reactive power reduction amount.
The load translation includes:
in translatable load modeling, for translatable loads connected at node i, t is used D Indicating the number of periods during which it has been operated,
Figure BDA00037800442000000812
and
Figure BDA00037800442000000813
respectively representing the upper limit and the lower limit of the load translation time interval, the load translation starting time interval is as follows:
Figure BDA00037800442000000814
is provided with
Figure BDA00037800442000000815
Is a flag bit row vector, wherein, only one element is 1, and the rest elements are 0; the load state matrix is defined as follows:
Figure BDA00037800442000000816
Figure BDA00037800442000000817
wherein,
Figure BDA00037800442000000818
the sizes of the translational active load and the translational reactive load of the node i in the period j are respectively; in the translation period, the active power and the reactive power of the translatable load can be respectively used by a matrix P i fl And
Figure BDA00037800442000000819
represents:
Figure BDA00037800442000000820
Figure BDA0003780044200000091
wherein, P i fl 、
Figure BDA0003780044200000092
The sizes of the translational active load and the translational reactive load of the node i are respectively;
the active and reactive power of the translatable load is:
Figure BDA0003780044200000093
Figure BDA0003780044200000094
wherein,
Figure BDA0003780044200000095
the sizes of the translatable active load and the translatable reactive load of the node i in the t period are respectively.
The power demand side management is management performed on the electricity consumer side. The management is a method for guiding users to consume less power at peak and more power at valley by the state through policy measures, so that the power supply efficiency is improved and the power utilization mode is optimized. Therefore, the power consumption and the power demand can be reduced under the condition of completing the same power utilization function, so that the power shortage pressure is relieved, and the power supply cost and the power utilization cost are reduced. Both power supply and power utilization are facilitated. The long-term purposes of saving energy and protecting the environment are achieved. The method of the present invention takes into account demand side management constraints.
The distributed new energy operation constraints include:
Figure BDA0003780044200000096
Figure BDA0003780044200000097
Figure BDA0003780044200000098
Figure BDA0003780044200000099
wherein,
Figure BDA00037800442000000910
the power factor angles of the PVG and the WTG respectively are fixed values.
It should be noted that wind energy has the advantages of large reserves and wide distribution, and is one of the earliest new energy sources for human use. As the name implies, wind power generation refers to converting the kinetic energy of wind into electrical energy. Specifically, wind power generation mainly converts wind energy into kinetic energy rotating at high speed through a propeller blade arranged on a fan to drive a generator to do work, and then the kinetic energy is converted into electric energy. Wind energy is generally influenced by various factors such as wind speed, temperature, illumination and geographical position, the power generation amount of the wind energy also presents high uncertainty and intermittency, and the effect is increased along with the increase of the time scale. The wind speed is the most influential factor, and can be divided into a cut-in wind speed, a cut-out wind speed, and a rated wind speed according to the characteristics of the blades of the fan.
Compared with the traditional power generation system, the photovoltaic power generation system has the common advantages of consuming new energy resources such as environmental protection and safe operation, and has the unique advantages of being slightly influenced by geographical environment, free and flexible in installation scale, relatively simple in operation and maintenance and the like, and different from the new energy resources. Therefore, the photovoltaic power generation system has considerable application prospect. However, as a large amount of photovoltaic power generation is connected to the power distribution network, the intermittent power generation characteristic of the photovoltaic power generation and the randomness generated by the influence of external natural resources can cause influence which is difficult to estimate on the safe and stable operation of the power distribution network.
Therefore, the method of the invention considers the operation constraint of the distributed new energy.
S3: and solving the model by adopting a branch-and-bound algorithm to obtain the minimum installation capacity of the transformer substation of the power distribution network.
It should be noted that a power distribution network power and electricity balance model is constructed in consideration of energy storage configuration and demand side management, research on a power distribution network power and electricity balance method in consideration of energy storage configuration and demand side management is achieved, and the investment cost of a transformer substation of a power distribution network is reduced.
Example 2
Referring to fig. 2 to 4, a power distribution network power and electric quantity balancing method considering energy storage configuration and demand side management is provided as an embodiment of the present invention, and in order to verify the beneficial effects of the present invention, scientific demonstration is performed through simulation experiments.
The power distribution network planning method is tested on a Portugal 54-node power distribution network system shown in fig. 3, fig. 2 is a topological structure diagram of a Portugal 54-node power distribution network calculation example system, the total load is 76.3MW, a part of wind power and photovoltaic power are configured in the system, the wind power is 15.0MW, the photovoltaic power is 15.0MW, the set wind abandoning rate and the set light abandoning rate are not more than 20%, and in addition, in order to meet various constraint conditions of power distribution network operation, the total installed capacity of a transformer substation needs to be calculated.
Wind power, photovoltaic and load information of a region in Guangdong of China in nearly 1 year is collected, 4 typical scenes are generated through a scene clustering method, and the result is shown in figure 3.
In order to research the influence of different management measures on the minimum planning capacity of the transformer substation of the new energy distribution network, the following scenes are set for comparative analysis:
scenario 1: simulating operation is carried out according to a plurality of typical scenes after clustering without considering any active management measures, and the minimum planning capacity of the transformer substation when the minimum planning capacity meets various constraint conditions is calculated;
scenario 2: configuring an energy storage device with the capacity not exceeding 9MW (18 MWh), performing simulated operation according to a plurality of clustered typical scenes, and calculating the minimum planned capacity of the transformer substation when the minimum planned capacity meets various constraint conditions;
scenario 3: considering demand side management, performing simulation operation according to the clustered typical scenes, and calculating the minimum planning capacity of the transformer substation when the minimum planning capacity meets various constraint conditions;
scenario 4: and considering energy storage configuration and demand side management, performing simulation operation according to a plurality of clustered typical scenes, and calculating the minimum planned capacity of the transformer substation when the minimum planned capacity meets various constraint conditions.
The minimum planned capacity of the transformer substation under different situations is obtained through simulation operation on an MATLAB R2010a simulation platform with a built-in YALMIP toolbox and a Gurobi 9.0.0 solver, and is shown in table 1. As can be seen from table 1, if no active management measures are taken, the minimum planned capacity of the substation is large, which results in a large investment waste. After different active management measures are taken, the minimum planned capacity of the transformer substation is reduced to different degrees, particularly after all the active management measures are taken, the minimum planned capacity of the transformer substation is reduced to 52.8MW, and the investment cost can be greatly saved.
Table 1 minimum planned capacity of substation under different scenarios
Scene number Minimum planned capacity of transformer substation
Scenario
1 67.3MW
Scenario
2 60.8MW
Scene
3 59.4MW
Scene
4 52.8MW
After further comparative analysis of the schemes taking different active management measures, the following conclusions can be drawn:
the energy storage device is configured to reduce the planning capacity of the transformer substation by reducing the load peak value;
the demand side management reduces the peak of the load by translating the load, and can reduce the planning capacity of the transformer substation.
Fig. 4 shows the amount of wind curtailment for 4 typical days for different scenarios. The influence of various active management measures on the wind and light abandoning amount of the system can be visually seen from fig. 4 and fig. 3, and after the various active management measures are considered, the consumption of new energy is greatly promoted under the condition of meeting various operation constraints of the power distribution network.
The simulation experiment fully illustrates the feasibility and the beneficial effects of the method, realizes the research of the power and electricity quantity balance method of the power distribution network considering energy storage configuration and demand side management, and reduces the construction cost of the transformer substation of the power distribution network.
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.

Claims (10)

1. A power distribution network electric quantity balancing method considering energy storage configuration and demand side management is characterized by comprising the following steps:
acquiring basic data information of the power distribution network;
setting a target function and constraint conditions, and constructing a power and electric quantity balance model of the power distribution network considering energy storage configuration and demand side management;
and solving the model by adopting a branch-and-bound algorithm to obtain the minimum installation capacity of the transformer substation of the power distribution network.
2. The method for balancing power of a power distribution network according to claim 1, considering energy storage configuration and demand side management, comprising: energy storage configuration and demand side management need to be considered in the process of constructing the power and electricity balance model of the power distribution network, and relevant measures are embedded into the model in a constraint mode.
3. The method of claim 2, wherein the objective function comprises: the minimum installation capacity of the transformer substation is taken as a target and expressed as follows:
Figure FDA0003780044190000011
wherein N is sub,i The number of nodes for installing the transformer substation;
Figure FDA0003780044190000012
and newly adding the configured transformation capacity for the ith node.
4. The method of claim 3, wherein the constraints include: the system comprises the following steps of power and electric quantity balance, energy storage operation constraint, demand side management and distributed new energy operation constraint.
5. The method for balancing power of the power distribution network according to claim 4, considering energy storage configuration and demand side management, comprising: the power and electric quantity balance constraint of the power distribution network is as follows:
Figure FDA0003780044190000013
Figure FDA0003780044190000014
Figure FDA0003780044190000015
wherein,
Figure FDA0003780044190000016
and
Figure FDA0003780044190000017
the transformer substation active power output, the photovoltaic active power output and the fan active power output of a t-time node i are respectively;
Figure FDA0003780044190000018
the load active demand of the node i at the moment t is obtained;
Figure FDA0003780044190000019
and the reactive power output of the transformer substation at the node i at the time t is obtained.
6. The method of claim 5, wherein the energy storage operation constraints comprise: the operation of the stored energy accessed to the node i of the power distribution network needs to satisfy the following constraints:
Figure FDA0003780044190000021
Figure FDA0003780044190000022
Figure FDA0003780044190000023
Figure FDA0003780044190000024
Figure FDA0003780044190000025
wherein,
Figure FDA0003780044190000026
and
Figure FDA0003780044190000027
are respectively provided withThe energy storage charging and discharging power; 0-1 variable gamma i,t Representing the charge and discharge state of energy storage, wherein 1 is discharge and 0 is charge; p i BES The rated power of a single energy storage module;
Figure FDA0003780044190000028
energy storage capacity is obtained;
Figure FDA0003780044190000029
and
Figure FDA00037800441900000210
respectively charging and discharging the energy storage efficiency; delta t is the time length between adjacent scheduling moments; s i,max And S i,min Respectively an upper limit and a lower limit of the energy storage charge state;
Figure FDA00037800441900000211
and
Figure FDA00037800441900000212
respectively the electric quantity at the initial time and the end time of the scheduling.
7. The method of claim 6, wherein the demand side management measures include load shedding and load shifting; the load is composed of a basic load, a reducible load and a translatable load; the load model at time t at node i is:
Figure FDA00037800441900000213
Figure FDA00037800441900000214
wherein,
Figure FDA00037800441900000215
respectively representing the active power of the total load, the basic load, the reducible load, the reduced load and the translatable load of the node i at the moment t;
Figure FDA00037800441900000216
Figure FDA00037800441900000217
the total load, the base load, the reducible load, the reduced load and the translatable load reactive power of the node i at the time t are respectively.
8. The method of claim 7, wherein the method for balancing the power of the distribution network in consideration of energy storage configuration and demand side management comprises: the load shedding mathematical model is as follows:
Figure FDA00037800441900000218
Figure FDA00037800441900000219
wherein,
Figure FDA00037800441900000220
and
Figure FDA00037800441900000221
respectively the lower limit and the upper limit of the load active power reduction amount;
Figure FDA00037800441900000222
and
Figure FDA00037800441900000223
respectively the lower limit and the upper limit of the load reactive power reduction amount.
9. The method of claim 8, wherein the load shifting comprises:
in translatable load modeling, for translatable loads connected at node i, t is used D Indicating the number of periods for which it is operating,
Figure FDA0003780044190000031
and
Figure FDA0003780044190000032
respectively representing the upper limit and the lower limit of the load translation time interval, the load translation starting time interval is as follows:
Figure FDA0003780044190000033
is provided with
Figure FDA0003780044190000034
Is a flag bit row vector, wherein, only one element is 1, and the rest elements are 0; the load state matrix is defined as follows:
Figure FDA0003780044190000035
Figure FDA0003780044190000036
wherein,
Figure FDA0003780044190000037
the sizes of the translational active load and the translational reactive load of the node i in the period j are respectively; in the translation period, the active power and the reactive power of the translatable load can be respectively used by a matrix P i fl And Q i fl Represents:
Figure FDA0003780044190000038
Figure FDA0003780044190000039
wherein, P i fl 、
Figure FDA00037800441900000310
Respectively the size of the translational active load and the size of the reactive load of the node i;
the active and reactive power of the translatable load are:
Figure FDA00037800441900000311
Figure FDA00037800441900000312
wherein,
Figure FDA00037800441900000313
the sizes of the translational active load and the translational reactive load of the node i in the t period are respectively.
10. The method of claim 9, wherein the distributed new energy operation constraints comprise:
Figure FDA0003780044190000041
Figure FDA0003780044190000042
Figure FDA0003780044190000043
Figure FDA0003780044190000044
wherein,
Figure FDA0003780044190000045
the power factor angles of the PVG and the WTG respectively are fixed values.
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116805792A (en) * 2023-06-21 2023-09-26 国网湖南省电力有限公司 Thermal power-energy storage regulation demand judging method and system in high-proportion new energy system
CN116805792B (en) * 2023-06-21 2024-06-11 国网湖南省电力有限公司 Thermal power-energy storage regulation demand judging method and system in high-proportion new energy system

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