Demand response combination optimization method considering response reliability and main transformer load balancing

Abstract

The invention provides a demand response combinatorial optimization method considering response reliability and main transformer load balancing, and the method comprises the steps: carrying out the evaluation of the reliability of resource response and the load balancing of a plurality of main transformers through building a demand response resource combinatorial optimization model, and carrying out the solving based on a heuristic optimization algorithm, so as to obtain a demand response resource combination; the demand response resource combinatorial optimization model comprises an objective function for minimizing the response cost of the whole network demand response resources, a response reliability constraint participating in response resources, a load balancing constraint after the demand response resources are accessed to a main transformer, and a variable logic constraint representing whether the demand response resources are added or not; the heuristic optimization algorithm is combined with an objective function of minimizing demand response cost, the satisfaction condition of response reliability constraint and main transformer load balancing constraint is sequentially judged according to a certain sequence after a certain demand response resource is incorporated into response, combined adjustment of the demand response resource is carried out, and a feasible solution of a combined optimization problem to be solved is given.

Description

Technical Field

[0001] The present invention belongs to the technical field of power systems, and in particular to a demand response combined optimization method taking into account response reliability and main transformer load balancing. Background Art

[0002] Under the background of the new power system, the power balance mode of the power system will change from the traditional "source follows load" to the new mode of "source, grid, load and storage interaction". User-side demand response is an indispensable regulation resource, which can not only reduce the overall peak load of the system and promote the consumption of new energy, but also provide auxiliary services such as frequency regulation and standby. With the improvement of system regulation requirements, demand response is no longer limited to the simple response modes such as power interruption, reduction, and translation in the initial demonstration period. In the future, demand response will have the characteristics of two-way, flexible and rapid response.

[0003] Active power regulation through user demand response has characteristics that are different from power supply and centralized energy storage: First, due to changes in response willingness, equipment status and other factors, the power response on the user side has a high degree of uncertainty, which makes it difficult to reliably meet the response capacity of the system demand; second, the capacity of the single demand response resource is small, and it is distributed to different main transformers. During the period of large photovoltaic power generation, power spikes are generated to adjust the demand downward, which may cause the main transformer to be overloaded during the period of concentrated demand response. At present, there are some demand response resource optimization methods that start from the perspective of demand response resources, guide the response behavior of demand response resources through penalty costs or incentive costs, and indirectly improve the execution effect of the demand capacity of the entire network, but such methods do not take into account whether the power grid can obtain the response capacity with a sufficient confidence level. In addition, the problem of main transformer overload caused by simultaneous resource response is often ignored. Therefore, there is an urgent need for a method to seek a sufficient, reliable, economical and safe combination of demand response resources based on the needs of the power grid.

[0004] The optimization method can solve a set of parameters so that the design index reaches the optimal value under a series of relevant constraints. It has been widely used in system scheduling, configuration and other issues. How to more comprehensively consider the demand response combination problem of the power grid, convert it into a mathematical optimization model, efficiently obtain the optimization solution results, and intuitively present the demand response resource combination to better serve the power grid scheduling still needs further exploration. Summary of the invention

[0005] In view of the defects and shortcomings of the prior art, the present invention provides a demand response combination optimization method taking into account response reliability and main transformer load balancing, which is used to improve the reliability, safety and economy of the power grid demand response resource combination solution.

[0006] The design and implementation process of this solution includes reading the power grid and demand response resources, establishing response reliability and main transformer load balancing indicators, establishing a demand response optimization model, solving the heuristic optimization algorithm and visual display.

[0007] First, the grid and demand response resource reading module obtains the existing system demand, demand response resources and access main transformer information from the operating grid. The demand response resource information includes the demand response type, response power distribution model and unit capacity response cost. The access main transformer information includes the rated capacity, power factor and load rate before demand response of the main transformer.

[0008] Secondly, construct response reliability and main transformer load balancing indicators to evaluate the feasibility of the demand response combination. Response reliability is reflected in the confidence level that the resources participating in the response meet the response capacity requirements, ensuring that the demand response combination can respond reliably. The main transformer load balancing indicator reflects whether the loads of the main transformers are relatively balanced when different demand response resources respond simultaneously, avoiding the risk of main transformer overload during the demand response process.

[0009] Then, a demand response optimization model is constructed based on the read demand response resources and main transformer information. The model includes the objective function of minimizing the response cost of the whole network demand response resources, the response reliability constraints of the participating response resources, the load balancing constraints after the demand response resources are connected to the main transformer, and the variable logic constraints representing whether the demand response resources are added.

[0010] Then, a heuristic and efficient algorithm is used to solve the demand response optimization model and obtain the demand response combination. The algorithm combines the objective function of minimizing the demand response cost, judges the change of indicators after a certain demand response resource is included in the response in a certain order, and adjusts the combination of demand response resources, and outputs the final demand response combination after iteration.

[0011] Finally, the visualization module converts the optimization model solution results to match the demand response database into an intuitive demand response combination, presenting it in both text and graphic modes. It supports data export and clearly shows dispatchers the optimal demand response call strategy in multiple dimensions, including response reliability, main transformer load balancing, and response cost.

[0012] The demand response combination optimization method of the present invention, which takes into account response reliability and main transformer load balancing, proposes multi-dimensional indicators of response reliability and main transformer load balancing based on demand response resources and the operation status of the connected main transformer, constructs a demand response optimization model, and uses a heuristic algorithm to efficiently solve the optimization problem involving a large number of 0-1 variables to obtain a demand response resource combination, providing dispatchers with an intuitive and clear demand response resource combination strategy. While ensuring that the demand response provides response capacity at the confidence level requirement, this method avoids the problem of heavy overload of the main transformer when distributed resources are concentrated in the response, achieves economic optimization, and provides a reliable, safe, and economical demand response combination solution for the power grid.

[0013] The present invention specifically adopts the following technical solutions:

[0014] A combined optimization method for demand response considering response reliability and main transformer load balancing

[0015] By building a demand response resource combination optimization model, the reliability of resource response and the load balancing of multiple main transformers are included in the evaluation, and the solution is based on the heuristic optimization algorithm to obtain the demand response resource combination;

[0016] The demand response resource combination optimization model includes: an objective function of minimizing the response cost of the whole network demand response resources, a response reliability constraint of the participating response resources, a load balancing constraint after the demand response resources are connected to the main transformer, and a variable logic constraint representing whether the demand response resources are added;

[0017] The heuristic optimization algorithm combines the objective function of minimizing the demand response cost, and judges in a certain order whether the response reliability constraint and the main transformer load balancing constraint are satisfied after a certain demand response resource is included in the response, and makes a combination adjustment of the demand response resources, and gives a feasible solution to the combination optimization problem to be solved. After iteration, the final demand response combination is output.

[0018] Furthermore, the demand response resource combination optimization model specifically includes:

[0019] Optimization goal:

[0020] Minimize the response cost of the whole network demand response resources. The objective function is shown in formula (1):

[0021]

[0022] Wherein, the superscript a represents the number of the main transformer connected to the demand response resource, the subscript i represents the sequence number of the demand response resource; c represents the unit capacity response cost parameter of the demand response resource, and x represents whether the demand response resource participates in the response. The value of 1 indicates participation in the response, and the value of 0 indicates non-participation in the response; g i a(p) is the probability density function of the response power of the i-th resource connected to the main transformer a;

[0023] Constraints:

[0024] Including response reliability constraints, main transformer load balancing constraints and variable logic constraints;

[0025] The response reliability constraint means that the resources participating in the response can meet the response capacity requirements at the required confidence level, as shown in equations (2) and (3);

[0026]

[0027] Among them, l and u represent the lower and upper limit parameters of the response capacity demand, α is the confidence level parameter, p represents the response power, and f(p) is the probability density function of the response power and the response power of the resources participating in the response. is the convolution operator; assuming that the resource response behaviors are independent of each other, the probability density function of the sum of the response powers is the convolution result of the probability density functions of the response powers of each resource;

[0028] The main transformer load balancing constraint is a constraint set to consider the risk of overload of the connected main transformer when different demand response resources respond at the same time. It requires that the load rate of each connected main transformer should be as balanced as possible after the response, as shown in formulas (4)-(6);

[0029]

[0030] qm≤ε (6)

[0031] Among them, q and m are introduced intermediate variables, s a Indicates the load power before the main transformer a responds, o a represents the rated capacity of the main transformer a, and ε represents the upper limit of the allowable deviation of the load factor;

[0032] The variable logic constraint consists of variable attributes, characterizing the variable as a 0-1 variable, which must satisfy formula (7);

[0033]

[0034] Furthermore, the objective function of the demand response resource combination optimization model considers the unit capacity response price parameters based on the demand response resources, and sorts them from small to large as the basis for resource selection. Each time a new demand response resource is selected, the satisfaction of the response reliability constraint and the main transformer load balancing constraint after the resource is included in the response is judged, and the combination of demand response resources is adjusted; whether the demand response resource is included is determined by the following three conditions;

[0035] Condition 1: The resource has not been included in the response, as shown in formula (8);

[0036]

[0037] Condition 2: After the new demand response resources are added, the response reliability index is improved, that is, equations (9)-(11) are established;

[0038]

[0039] Condition 3: After the resource is newly added, the load rates of different main transformers do not exceed the upper limit of the allowable deviation, that is, formula (12) is established;

[0040]

[0041] After taking reliability into consideration, the capacity of all demand response resources should be able to cover the upper limit of the response capacity demand, that is, there must be a solution that satisfies equations (2) and (3). Considering the situation where the response reliability performance does not meet the requirements after traversing all resources due to the failure to meet the main transformer load balancing constraints, the method of relaxing the main transformer load balancing constraints and then searching for the demand response resource combination from the beginning is adopted; whether to relax the main transformer load balancing constraints is distinguished by the variables flag = 0 and flag = 1.

[0042] Furthermore, solving the demand response resource combination optimization model based on the heuristic optimization algorithm specifically includes the following steps:

[0043] Demand response resource sorting; according to the demand response resource unit capacity response cost parameter c i a The size of is sorted from small to large to generate an n×2 index matrix Index, where n represents the total number of demand response resources, the first column marks the main transformer serial number a to which the resource is connected, and the second column marks the resource serial number i corresponding to the main transformer to which the resource is connected;

[0044] Initialize parameters; initialize the inclusion flag of demand response resources, the number of search rows, and the main transformer load balancing constraint relaxation flag;

[0045] Demand response resource search: Search for demand response resources starting from the first row of the Index matrix, and record the current search row number as count;

[0046] Determine the main transformer load balancing constraint relaxation flag; when the main transformer load balancing constraint is not relaxed, that is, flag = 0, the inclusion of demand response resources requires the satisfaction of conditions 1 and 2; when the main transformer load balancing constraint is relaxed, that is, flag = 1, the inclusion of demand response resources requires the satisfaction of conditions 1, 2, and 3;

[0047] Determine whether the current demand response resource is included; if it is determined to be included in the current demand response resource, mark it as included x ia Mark it as 1 and move to the next row for retrieval; if the condition is not met, move directly to the next row for retrieval;

[0048] Determine whether it is necessary to relax the load balancing constraint of the main transformer; after traversing all demand response resources, determine whether the response reliability of the current demand response combination meets the standard; if not, relax the load balancing constraint of the main transformer and search and judge the demand response resources again; if it meets the standard, output the demand response resource combination result.

[0049] Furthermore, the demand response resource combination optimization model obtains demand response resources and access main transformer information from the operating power grid through the power grid and demand response resource reading module; wherein the demand response resource information includes demand response type, response power distribution model and unit capacity response cost; the access main transformer information includes the rated capacity, power factor and load rate before demand response of the main transformer.

[0050] And, a demand response combination optimization system taking into account response reliability and main transformer load balancing, comprising: a demand response resource combination optimization model and a calculation module;

[0051] The demand response resource combination optimization model includes: an objective function of minimizing the response cost of the whole network demand response resources, a response reliability constraint of the participating response resources, a load balancing constraint after the demand response resources are connected to the main transformer, and a variable logic constraint representing whether the demand response resources are added;

[0052] The calculation module is used to combine the objective function of minimizing the demand response cost through a heuristic optimization algorithm, and judge in a certain order whether the response reliability constraint and the main transformer load balancing constraint are satisfied after a certain demand response resource is included in the response, and make a combination adjustment of the demand response resources, and give a feasible solution to the combination optimization problem to be solved, and output the final demand response combination after iteration.

[0053] Furthermore, it also includes a power grid and demand response resource reading module, which is used to obtain demand response resources and access main transformer information from the operating power grid; wherein the demand response resource information includes the demand response type, the response power distribution model and the unit capacity response cost; the access main transformer information includes the rated capacity, power factor and load rate before demand response of the main transformer, and then inputs the demand response resource combination optimization model.

[0054] Furthermore, a visualization module is included, which is used to match the optimization model solution result output by the calculation module with the demand response database, convert it into a demand response combination, and display it.

[0055] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of a demand response combined optimization method taking into account response reliability and main transformer load balancing are implemented as described above.

[0056] A non-transitory computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a demand response combined optimization method that takes into account response reliability and main transformer load balancing as described above.

[0057] Compared with the prior art, the present invention and its preferred solution improve the reliability and safety of the demand response combination under the power grid demand response scenario while ensuring the economy of demand response, thereby improving the feasibility of the demand response solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0059] Figure 1 It is a schematic diagram of the overall process of designing and implementing the method of the embodiment of the present invention;

[0060] Figure 2 is a schematic diagram of a combination of demand adjustment and demand response of a system according to an embodiment of the present invention;

[0061] Figure 3 It is a flow chart of a heuristic algorithm for optimizing resource combination in response to demand according to an embodiment of the present invention. DETAILED DESCRIPTION

[0062] Hereinafter, the specific embodiments of the present application will be described in detail with reference to the accompanying drawings. According to these detailed descriptions, those skilled in the art can clearly understand the present application and can implement the present application. Without violating the principles of the present application, the features in the various embodiments can be combined to obtain new implementations, or certain features in certain embodiments can be replaced to obtain other preferred implementations.

[0063] In order to make the features and advantages of this patent more obvious and easy to understand, the following embodiments are specifically described in detail with the accompanying drawings as follows:

[0064] The present invention provides a demand response combination optimization method taking into account response reliability and main transformer load balancing, including: grid operation status reading, used to obtain information about existing demand response resources and connected main transformers from the operating grid; response reliability and main transformer load balancing indicators, used to quantitatively evaluate the feasibility of demand response combinations; demand response optimization model construction abstracts the physical problem of demand response resource optimization taking into account response reliability and main transformer load balancing into a mathematical form; a heuristic and efficient algorithm takes the capacity response cost of demand response resources as the basis for resource selection, judges the satisfaction of response reliability constraints and main transformer load balancing constraints after the resources are included in the response, and performs combination adjustment of demand response resources, and finally gives a feasible solution to the combination optimization problem to be solved; a visualization display module converts the optimization model solution result into an intuitive demand response combination, presents it in two modes: text and diagram, and generates a demand response resource combination strategy for reference by dispatchers;

[0065] The power grid and demand response resource reading module specifically includes: reading the type of demand response resources in the current area, the response power distribution model and the unit capacity response cost to form a standardized demand response resource database; reading the information of the main transformers that can be connected to the demand response resources, including the rated capacity, power factor and load rate before demand response of the main transformers, and entering the connection relationship between the demand response resources and each main transformer; regularly updating the demand response resource database and the information of the main transformers that can be connected to reflect the latest status of the power grid;

[0066] It includes quantitative evaluation of the response reliability of demand response resources and main transformer load balancing indicators; response reliability is the confidence level that the resources participating in the response meet the response capacity requirements; main transformer load balancing requires that the load rates of each connected main transformer should be as balanced as possible after the demand response;

[0067] The constructed model includes: (1) minimizing the response cost of the whole network demand response resources as the optimization goal; (2) response reliability constraints, main transformer load balancing constraints and variable logic constraints; the response reliability constraint is that the resources participating in the response can meet the response capacity requirements with the required confidence level, the main transformer load balancing constraint is that the allowable deviation of the main transformer load after the demand response resources are connected simultaneously is within the allowable range, and the variable logic constraint represents whether the demand response resources participate in the response;

[0068] The algorithm solution steps include: sorting the demand response resources according to the unit capacity response price parameter; selecting the demand response resources according to the sorting; judging whether the response reliability is improved after the resource is included in the response and whether the load balancing constraint of the main transformer is satisfied; adjusting the combination of demand response resources; selecting the demand response resources according to the sorting and repeating the judgment step; outputting the final demand response resource combination;

[0069] The visualization display module specifically includes: matching the demand response resource library and accessing the main transformer data according to the solution results of the optimization model, outputting the demand response resource call strategy in the form of text and graphics, and supporting tabular data export.

[0070] Among them, the model and solution algorithm are the core designs of the present invention to solve the technical problems, and the grid and demand response resource reading module and visualization display are optional functions, such as Figure 1 As shown, in a typical embodiment, the complete implementation of the above solution may generally include the following steps, but it should be noted that the sequence number of the steps cannot be regarded as a limitation of the solution of the present invention:

[0071] Step 1: Read the demand response resource information. Read the current system response demand in the area; read the type of demand response resource, response power distribution model and unit capacity response cost; read the demand response resource access main transformer information, including the rated capacity, power factor and load rate before demand response of the main transformer, as well as the connection relationship between the demand response resource and each main transformer.

[0072] Step 2: Construct response reliability and main transformer load balancing indicators. Construct response reliability mathematical indicators based on the grid demand response capacity requirements (including capacity upper limit, capacity lower limit, and confidence level) and the power distribution probability density function of demand response resources; construct main transformer load balancing indicators based on the main transformer pre-response load power, main transformer rated capacity, and load rate allowable deviation upper limit.

[0073] Step 3: Construct a demand response optimization model. Taking minimizing the response cost of the whole network's demand response resources as the optimization goal, add variable logic constraints, and convert the response reliability and main transformer load balancing indicators into response reliability constraints and main transformer load balancing constraints.

[0074] Step 4: Use heuristic algorithm to solve the optimization model. Consider the unit capacity response price parameters based on demand response resources, sort them from small to large, as the basis for resource selection, and each time a new demand response resource is selected, determine whether the response reliability constraint and the main transformer load balancing constraint are satisfied after the resource is included in the response, and adjust the combination of demand response resources according to the indicators.

[0075] Step 5: Visual display. According to the solution results of the optimization model, match the demand response resource library and the access main transformer data, and present the demand response resource call strategy in the form of text and diagrams. The text shows the number and capacity of the demand response resource called under the current grid response demand; the diagram shows the access relationship between the demand response resource and the main transformer, ensuring that the demand response combination results are clear and intuitive.

[0076] More specifically, in the preferred embodiment of this invention:

[0077] Step 1: Read the grid and demand response resource information.

[0078] Demand response resources are diverse. The types of demand response resources, response power distribution models, and unit capacity response costs in the current region are read to form a standardized demand response resource model and database to accurately describe the response behavior of demand response resources and participate in mathematical optimization models. On this basis, the information of demand response resources accessing the main transformer is identified, including the rated capacity, power factor, and load rate before demand response of the main transformer, and the connection relationship between the demand response resources and each main transformer is entered. At the same time, the system is set to continuously collect demand response resource data, update the power response model of the resource, and update the grid-side active power regulation requirements and main transformer information to more accurately reflect the grid demand response behavior.

[0079] Step 2: Construct response reliability and main transformer load balancing indicators.

[0080] The grid dispatching department calculates and issues demand response capacity requirements based on the current grid operation mode. Considering the uncertainty of user response behavior, the response capacity requirement is given in the form of an interval [l,u], and requires an expected confidence level α. The corresponding physical meaning is that the users who are finally determined to be included in the response should be able to jointly provide a response capacity of [l,u] with a probability of not less than α. This requirement is defined as the response reliability requirement. From a mathematical point of view, the area enclosed by the probability density curve of the total response power and the horizontal axis [l,u] range must be greater than or equal to the confidence level α. For example Figure 2 shown.

[0081] The demand response capacity requirements issued need to be completed by connecting to the demand response resources of different main transformers. Different resource combinations will lead to different costs, response reliability and main transformer load rate performance. In actual engineering problems, it is necessary to avoid the situation where some main transformers are seriously overloaded due to demand response, while other main transformers still have a large load capacity. That is, the load rate deviation of different main transformers is best controlled within a certain deviation limit. This requirement is called the main transformer load balancing requirement. The demand response resource optimization problem is to determine the access main transformer corresponding to the participating response resources and the sequence number of the response resources among all the access main transformers, so that the response reliability and main transformer load balancing requirements are met while seeking the optimal economy.

[0082] Step 3: Construction of demand response optimization model.

[0083] Based on the demand response resource information in step one and the indicators in step two, step three is based on the physical problem of demand response resource optimization taking into account response reliability and main transformer load balancing, and its mathematical model is abstractly constructed.

[0084] 1. Optimization objectives:

[0085] The optimization goal considered in this method is to minimize the response cost of the whole network demand response resources. The objective function is shown in formula (1):

[0086]

[0087] Among them, the superscript a represents the number of the main transformer connected to the demand response resource, and the subscript i represents the sequence number of the demand response resource. c represents the unit capacity response cost parameter of the demand response resource, and x is a variable representing whether the demand response resource participates in the response. The value of 1 indicates participation in the response, and the value of 0 indicates non-participation in the response. i a (p) is the probability density function of the response power of the i-th resource connected to the main transformer a.

[0088] 2. Constraints:

[0089] The constraints considered in this method include response reliability constraints, main transformer load balancing constraints and variable logic constraints.

[0090] (1) Response reliability constraints

[0091] The response reliability constraint means that the resources participating in the response can meet the response capacity requirements at the required confidence level, as shown in Equations (2) and (3).

[0092]

[0093] Among them, l and u represent the lower and upper limit parameters of the response capacity demand, α is the confidence level parameter, p represents the response power, and f(p) is the probability density function of the response power and the response power of the resources participating in the response. is the convolution operator. Assuming that the resource response behaviors are independent of each other, the probability density function of the sum of the response powers is the convolution result of the probability density functions of the response powers of each resource.

[0094] (2) Main transformer load balancing constraints

[0095] The main transformer load balancing constraint is a constraint set to take into account the risk of overload of the connected main transformer when different demand response resources respond simultaneously. It requires that the load rates of the connected main transformers should be as balanced as possible after the response, as shown in equations (4)-(6).

[0096]

[0097] qm≤ε (6)

[0098] Among them, q and m are introduced intermediate variables, s a Indicates the load power before the main transformer a responds, o a It represents the rated capacity of the main transformer a, and ε represents the upper limit of the allowable deviation of the load factor.

[0099] (3) Variable logical constraints

[0100] According to the variable attributes, the variable is characterized as a 0-1 variable and must satisfy equation (7).

[0101]

[0102] Step 4: Heuristic algorithm solves the optimization model.

[0103] It can be seen from formulas (1)-(7) that the demand response resource optimization model is a mixed integer optimization problem. The capacity of individual demand response resources is relatively small. When there is a power regulation demand that requires demand response in the power grid, the gap is often large, and a large number of 0-1 variables must be introduced. As the number of 0-1 variables increases, the complexity of strict mathematical programming methods increases exponentially, and they face the problem of difficulty in solving. The present invention adopts a heuristic and efficient solution algorithm to improve the calculation efficiency under the premise of low error in the calculation results.

[0104] According to the objective function of the optimization model, the unit capacity response price parameters based on the demand response resources are considered and sorted from small to large as the basis for resource selection. Each time a new demand response resource is selected, the satisfaction of the response reliability constraint and the main transformer load balancing constraint after the resource is included in the response is judged, and the combination of demand response resources is adjusted. There are three conditions for judging whether the demand response resource is included.

[0105] Condition 1: The resource has not been included in the response, as shown in formula (8).

[0106]

[0107] Condition 2: After the new demand response resources are added, the response reliability index is improved, that is, equations (9)-(11) are established.

[0108]

[0109] Condition 3: After the resource is newly added, the load factors of different main transformers do not exceed the upper limit of the allowable deviation, that is, formula (12) holds.

[0110]

[0111] In actual projects, after taking reliability into consideration, the capacity of all demand response resources should be able to cover the upper limit of the response capacity demand, that is, there must be a solution that satisfies equations (2) and (3), but the rigidity requirement of the main transformer load balancing constraint is relatively low. This method takes into account the situation where the response reliability performance does not meet the requirements after traversing all resources due to the failure to meet the main transformer load balancing constraint. It is handled by relaxing the main transformer load balancing constraint and searching for the demand response resource combination from the beginning. Whether the main transformer load balancing constraint is relaxed or not is distinguished by the variables flag = 0 and flag = 1.

[0112] The flow chart of the heuristic algorithm for demand response resource optimization is as follows: Figure 3 shown.

[0113] The specific steps of the heuristic algorithm adopted by the present invention are as follows:

[0114] Step 1: Demand response resource sorting. According to the demand response resource unit capacity response cost parameter c i a The size of is sorted from small to large to generate an n×2 index matrix Index, where n represents the total number of demand response resources, the first column marks the main transformer serial number a to which the resource is connected, and the second column marks the resource serial number i corresponding to the main transformer to which the resource is connected.

[0115] Step 2: Initialize parameters. Initialize the inclusion flag of demand response resources, the number of search rows, and the main transformer load balancing constraint relaxation flag.

[0116] Step 3: Search for demand response resources. Search for demand response resources starting from the first row of the Index matrix, and record the current search row number as count.

[0117] Step 4: Determine the main transformer load balancing constraint relaxation flag. When the main transformer load balancing constraint is not relaxed (flag = 0), the inclusion of demand response resources requires the satisfaction of conditions 1 and 2; when the main transformer load balancing constraint is relaxed (flag = 1), the inclusion of demand response resources requires the satisfaction of conditions 1, 2, and 3.

[0118] Step 5: Determine whether the current demand response resource is included. If it is determined that the current demand response resource is included, mark it with the inclusion mark x i a Mark it as 1 and move to the next row for retrieval; if the condition is not met, move directly to the next row for retrieval.

[0119] Step 6: Determine whether it is necessary to relax the load balancing constraint of the main transformer. After traversing all demand response resources, determine whether the response reliability of the current demand response combination meets the standard. If not, relax the load balancing constraint of the main transformer and search and judge the demand response resources again; if it meets the standard, output the demand response resource combination result.

[0120] Step 5: Visual display.

[0121] Firstly, based on the solution of the demand response combination optimization problem, the demand response resource database is matched, the demand response resource combination is identified, and the resources are grouped and arranged according to the main transformers to which they are connected, completing the conversion of the mathematical problem results into specific demand response combination solutions.

[0122] Secondly, the demand response combination scheme is presented in text and graphic form, the demand response resources participating in the response on each main transformer are output, and the confidence level of reliable response under the current combination scheme and the maximum and minimum load rate deviations of each main transformer are displayed. The results support tabular data export.

[0123] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0124] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0125] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0126] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0127] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0128] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

[0129] This patent is not limited to the above-mentioned optimal implementation mode. Anyone can derive various other forms of a demand response combination optimization method that takes into account response reliability and main transformer load balancing under the inspiration of this patent. All equal changes and modifications made within the scope of the patent application of the present invention should fall within the scope of this patent.

Claims

1. A demand response combined optimization method taking into account response reliability and main transformer load balancing, characterized in that: By building a demand response resource combination optimization model, the reliability of resource response and the load balancing of multiple main transformers are included in the evaluation, and the solution is based on the heuristic optimization algorithm to obtain the demand response resource combination; The demand response resource combination optimization model includes: an objective function of minimizing the response cost of the whole network demand response resources, a response reliability constraint of the participating response resources, a load balancing constraint after the demand response resources are connected to the main transformer, and a variable logic constraint representing whether the demand response resources are added; The heuristic optimization algorithm combines the objective function of minimizing the demand response cost, and judges in a certain order whether the response reliability constraint and the main transformer load balancing constraint are satisfied after a certain demand response resource is included in the response, and makes a combination adjustment of the demand response resources, and gives a feasible solution to the combination optimization problem to be solved. After iteration, the final demand response combination is output.

2. A demand response combined optimization method taking into account response reliability and main transformer load balancing according to claim 1, characterized in that: The demand response resource combination optimization model specifically includes: Optimization goal: Minimize the response cost of the whole network demand response resources. The objective function is shown in formula (1): Wherein, the superscript a represents the number of the main transformer connected to the demand response resource, the subscript i represents the sequence number of the demand response resource; c represents the unit capacity response cost parameter of the demand response resource, and x represents whether the demand response resource participates in the response. The value of 1 indicates participation in the response, and the value of 0 indicates non-participation in the response; g i a (p) is the probability density function of the response power of the i-th resource connected to the main transformer a; Constraints: Including response reliability constraints, main transformer load balancing constraints and variable logic constraints; The response reliability constraint means that the resources participating in the response can meet the response capacity requirements at the required confidence level, as shown in equations (2) and (3); Among them, l and u represent the lower and upper limit parameters of the response capacity demand, α is the confidence level parameter, p represents the response power, and f(p) is the probability density function of the response power and the response power of the resources participating in the response. is the convolution operator; assuming that the resource response behaviors are independent of each other, the probability density function of the sum of the response powers is the convolution result of the probability density functions of the response powers of each resource; The main transformer load balancing constraint is a constraint set to take into account the risk of overload of the connected main transformer when different demand response resources respond simultaneously. It requires that the load rates of the connected main transformers should be as balanced as possible after the response, as shown in equations (4)-(6); qm≤ε (6) Among them, q and m are introduced intermediate variables, s a Indicates the load power before the main transformer a responds, o a represents the rated capacity of the main transformer a, and ε represents the upper limit of the allowable deviation of the load factor; The variable logic constraint is based on the variable attribute, and the variable is characterized as a 0-1 variable, which must satisfy formula (7); 3. A demand response combined optimization method taking into account response reliability and main transformer load balancing according to claim 2, characterized in that: According to the objective function of the demand response resource combination optimization model, the unit capacity response price parameters based on the demand response resources are considered and sorted from small to large as the basis for resource selection. Each time a new demand response resource is selected, the satisfaction of the response reliability constraint and the main transformer load balancing constraint after the resource is included in the response is judged, and the combination of demand response resources is adjusted; whether the demand response resource is included is determined by the following three conditions; Condition 1: The resource has not been included in the response, as shown in formula (8); Condition 2: After the new demand response resources are added, the response reliability index is improved, that is, equations (9)-(11) are established; Condition 3: After the resource is newly added, the load rates of different main transformers do not exceed the upper limit of the allowable deviation, that is, formula (12) is established; After taking reliability into consideration, the capacity of all demand response resources should be able to cover the upper limit of the response capacity demand, that is, there must be a solution that satisfies equations (2) and (3); considering the situation that after traversing all resources, the response reliability performance does not meet the requirements due to the failure to meet the main transformer load balancing constraints, the main transformer load balancing constraints are relaxed and then the demand response resource combination is searched from the beginning; whether to relax the main transformer load balancing constraints is distinguished by the variables flag = 0 and flag = 1.

4. A demand response combined optimization method taking into account response reliability and main transformer load balancing according to claim 3, characterized in that: Solving the demand response resource combination optimization model based on the heuristic optimization algorithm specifically includes the following steps: Demand response resource sorting; according to the demand response resource unit capacity response cost parameter c i a The size of is sorted from small to large to generate an n×2 index matrix Index, where n represents the total number of demand response resources, the first column marks the main transformer serial number a to which the resource is connected, and the second column marks the resource serial number i corresponding to the main transformer to which the resource is connected; Initialize parameters; initialize the inclusion flag of demand response resources, the number of search rows, and the main transformer load balancing constraint relaxation flag; Demand response resource search: Search for demand response resources starting from the first row of the Index matrix, and record the current search row number as count; Determine the main transformer load balancing constraint relaxation flag; when the main transformer load balancing constraint is not relaxed, that is, flag = 0, the inclusion of demand response resources requires the satisfaction of conditions 1 and 2; when the main transformer load balancing constraint is relaxed, that is, flag = 1, the inclusion of demand response resources requires the satisfaction of conditions 1, 2, and 3; Determine whether the current demand response resource is included according to the conditions; if it is determined to be included in the current demand response resource, mark it as included x i a Mark it as 1 and move to the next row for retrieval; if the condition is not met, move directly to the next row for retrieval; Determine whether it is necessary to relax the load balancing constraint of the main transformer; after traversing all demand response resources, determine whether the response reliability of the current demand response resource combination meets the standard; if not, relax the load balancing constraint of the main transformer and search and judge the demand response resources again; if it meets the standard, output the demand response resource combination result.

5. The demand response combined optimization method taking into account response reliability and main transformer load balancing according to claim 1 is characterized in that: The demand response resource combination optimization model obtains demand response resources and access main transformer information from the operating power grid through the power grid and demand response resource reading module; wherein the demand response resource information includes the demand response type, the response power distribution model and the unit capacity response cost; the access main transformer information includes the rated capacity, power factor and load rate before demand response of the main transformer.

6. A demand response combined optimization system taking into account response reliability and main transformer load balancing, characterized in that: include: Demand response resource portfolio optimization model and calculation module; The demand response resource combination optimization model includes: an objective function of minimizing the response cost of the whole network demand response resources, a response reliability constraint of the participating response resources, a load balancing constraint after the demand response resources are connected to the main transformer, and a variable logic constraint representing whether the demand response resources are added; The calculation module is used to combine the objective function of minimizing the demand response cost through a heuristic optimization algorithm, and judge in a certain order whether the response reliability constraint and the main transformer load balancing constraint are satisfied after a certain demand response resource is included in the response, and make a combination adjustment of the demand response resources, and give a feasible solution to the combination optimization problem to be solved, and output the final demand response combination after iteration.

7. A demand response combined optimization system taking into account response reliability and main transformer load balancing according to claim 6, characterized in that: It also includes a power grid and demand response resource reading module, which is used to obtain demand response resources and access main transformer information from the operating power grid; the demand response resource information includes the demand response type, response power distribution model and unit capacity response cost; the access main transformer information includes the rated capacity, power factor and load rate before demand response of the main transformer; after reading, the data is input into the demand response resource combination optimization model.

8. A demand response combined optimization system taking into account response reliability and main transformer load balancing according to claim 6, characterized in that: It also includes a visualization module, which is used to match the optimization model solution results output by the calculation module with the demand response database, convert them into demand response combinations, and display them.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of a demand response combined optimization method taking into account response reliability and main transformer load balancing as described in any one of claims 1 to 5 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a demand response combined optimization method taking into account response reliability and main transformer load balancing as described in any one of claims 1 to 5 are implemented.

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