Method for stimulating compatible demand response trading market to promote new energy consumption

Abstract

The invention provides a method for promoting new energy consumption by exciting a compatible demand response transaction market, which relates to the technical field of new energy consumption and comprises the following steps: acquiring power grid topology information, generator set operation data, load data and new energy data; establishing a target function by taking the minimum electricity purchase cost as a target according to the data; performing function solution by taking a power balance constraint, a unit operation constraint, a standby constraint and a demand response constraint as constraint conditions to obtain a new energy consumption result; issuing the total transfer load in the consumption result to the demand response users, so that each demand response user declarates to the system; and determining incentive fees paid to the demand response users according to the promotion effect of the demand response users on new energy consumption so as to guide the demand response users to report real information. According to the scheme, the wind power consumption can be promoted by guiding and responding to the real quotation of the user, and the market efficiency loss possibly caused by the strategy quotation in the existing scheme is reduced.

Description

Technical Field

[0001] The present invention relates to the field of new energy consumption technology, and in particular to a method for promoting new energy consumption through an incentive-compatible demand response trading market. Background Art

[0002] New energy represented by wind power and photovoltaic power is a strategic resource for coping with climate change and realizing my country's energy transformation, and has been rapidly developed in various regions. However, the characteristics of new energy such as random volatility make it impossible to control it like conventional power sources, and put forward higher requirements for the flexibility of the power system. With the continuous expansion of the installed capacity of new energy such as wind power and photovoltaic power, the development of new energy faces more challenges, among which the problem of grid connection and consumption has become an important factor restricting the development of new energy. The difficulty of new energy consumption lies in its inherent randomness, volatility, intermittency, etc. The access of large-scale new energy has significantly increased the volatility and uncertainty of the system. The system generally relies on the flexible adjustment ability of conventional power sources to cope with the uncertainty of new energy output and maintain system balance. However, in this mode, first of all, with the expansion of the scale of new energy grid connection, the regulation pressure of the system continues to increase; secondly, excessive reliance on the dispatching mode of conventional units will lead to problems such as frequent start and stop of units and deviation from the economic operation point, increase additional coal consumption and carbon emissions, and reduce the environmental and economic benefits of new energy access; finally, the proportion of conventional power sources with flexible adjustment capabilities is insufficient, and the flexible adjustment capacity of the power generation side is very limited. It is difficult to meet the growing demand for new energy consumption by relying solely on the power generation side.

[0003] With the continuous advancement of intelligent grid construction, the level of information interaction between the demand side and the grid continues to improve, and more and more user-side resources are being discovered. Demand response has become an important way to absorb new energy due to its flexible deployment and rapid response. Using demand response in conjunction with new energy operation can effectively improve the utilization efficiency of new energy and promote the absorption of new energy.

[0004] Demand response (DR) is a part of demand side management (DSM). It is proposed to fully play the role of demand side management in the competitive market, maintain system reliability and improve market operation efficiency. With the development of the power market, many DR projects have emerged. Based on the different characteristics of DR projects, they can be divided into different types. The most widely used classification method is the two types of demand response proposed according to different user response methods: price-based demand response (PBDR) and incentive-based demand response (IBDR). Among them, PBDR refers to the user's response to changes in electricity prices and the adjustment of electricity demand, mainly including time of use pricing (TOU), real time pricing (RTP), critical peak pricing (CPP), etc. IBDR means that the DR implementation agency formulates deterministic or time-varying policies to encourage users to respond in a timely manner and reduce load when system operation is affected or electricity prices are high. Users participating in such DR projects generally need to sign a contract with the DR implementation agency. The contract clearly includes the calculation method of the user's basic load consumption and load reduction, incentive rates and penalties when the user fails to respond as required. It mainly includes direct load control (DLC), interruptible load (IL), demand side bidding (DSB), emergency demand response (EDR), capacity / ancillary service program, etc.

[0005] Demand response provides a more flexible and economical way to absorb large-scale renewable energy due to its flexible deployment and rapid response to changes in system operation. On October 5, 2012, the International Electrotechnical Commission officially released the white paper "Large-capacity renewable energy grid connection and large-capacity energy storage grid connection", which comprehensively reviewed the current application status and future development of large-capacity renewable energy grid connection represented by wind power generation and solar power generation and large-capacity energy storage. The book lists "developing the application potential of demand response" as one of the solutions and technical requirements to support more renewable energy grid connection in the future. Promoting wind power absorption through demand-side resources has also become a current research hotspot. The research content involves the dispatching strategies of different DR projects participating in wind power absorption and the combination of DR and other technical means.

[0006] At present, market operators in various countries mostly adopt fixed electricity prices and financial subsidies as incentive policies for demand response projects. Or introduce a demand response trading market, and form a demand response trading price through users with demand response capabilities in the market. This method can effectively activate demand response users to participate in market transactions, but the above-mentioned centralized declaration-clearing model will also bring opportunities for demand response users to exercise market power. The strategic bidding behavior of demand response users will lead to excessively high market transaction prices. Although there are relatively mature regulatory measures to inhibit market participants from making strategic bids, these regulatory measures will not fundamentally inhibit the strategic bidding behavior of demand response users. Summary of the invention

[0007] In view of this, in order to address the above shortcomings, it is necessary to propose an incentive-compatible demand response trading market method to promote the consumption of new energy, so as to promote wind power consumption by guiding the real quotations of responding users and reduce the market efficiency loss that may be caused by strategic quotations in existing schemes.

[0008] In a first aspect, the present invention provides a method for promoting new energy consumption through an incentive-compatible demand response trading market, comprising:

[0009] Obtain grid topology information, generator set operation data, load data and new energy data;

[0010] According to the grid topology information, generator set operation data, load data and new energy data, an objective function is established with the goal of minimizing the electricity purchase cost;

[0011] Taking power balance constraint, unit operation constraint, reserve constraint and demand response constraint as constraint conditions of the objective function, solving the objective function to obtain the result of new energy consumption; wherein the result of new energy consumption includes the total amount of transferred load;

[0012] The total amount of transferred load is issued to demand response users, so that each demand response user can report to the system;

[0013] The incentive fees paid to demand response users are determined based on their role in promoting the consumption of new energy, so as to guide each demand response user to report true information.

[0014] Preferably, the objective function established includes:

[0015]

[0016] Among them, minF uc is the objective function, T is the set of scheduling periods, N g is a collection of conventional generator sets, D IL is the set of users participating in the interruptible load, f(p n,t ) is the power generation cost function, p n,t is the output of generator set n at time t, which is the decision variable; g n,t is the startup cost of generator set n at time t, and is the decision variable; is the spare capacity provided by interruptible load user d at time t, which is the decision variable; is the capacity compensation unit cost of interruptible load user d; The capacity cost for interruptible load response; C pena They are the unit penalty cost for wind curtailment and the unit penalty cost for load shedding respectively; are wind power abandonment and load shedding respectively, and are decision variables.

[0017] Preferably, the power balance constraint includes:

[0018]

[0019] Among them, L t is the initial load of the system, is the response load of user d participating in the transferable load at time t; W t To forecast the output of wind power,

[0020] Preferably, the unit operation constraints include: output limit, unit climbing constraint, unit minimum start-stop time constraint and start-stop cost constraint;

[0021] The output limit is expressed as:

[0022]

[0023] In the formula, μ n,t A 0-1 decision variable representing the startup state of the unit, where 1 represents the unit running; and They are the minimum output limit and maximum output limit of the unit respectively;

[0024] The unit climbing constraint is expressed as:

[0025]

[0026] In the formula, They are the hourly up-climbing capability and down-climbing capability of the generator respectively;

[0027] The minimum start and stop time constraint of the unit is expressed as:

[0028]

[0029] Where D n and O n are the minimum downtime and minimum start-up time of unit n respectively;

[0030] The start-stop cost constraint is expressed as:

[0031]

[0032] In the formula, G n is the start-up and shutdown cost of unit n.

[0033] Preferably, the reserve constraint includes: a positive spinning reserve constraint and a negative spinning reserve constraint;

[0034] The positive spinning reserve constraint is expressed as:

[0035]

[0036] In the formula, is the positive spinning reserve provided by unit n at time t, Positive spinning reserve demand for wind power;

[0037] The negative spinning reserve constraint is expressed as:

[0038]

[0039] In the formula, is the negative spinning reserve provided by unit n at time t, Negative spinning reserve demand for wind power.

[0040] Preferably, the demand response constraint includes a transferable load related constraint, and the transferable load related constraint is expressed as:

[0041]

[0042] In the formula, α1 and β1 are the first and second coefficients of the utility function, α2 and β2 are the first and second coefficients of the loss function, respectively. The utility function used to characterize the users of transferable load, The loss function used to characterize the users of transferable load, Used to characterize the capacity constraints of users who can shift load.

[0043] Preferably, the demand response constraint further includes an interruptible load response capacity constraint, and the interruptible load response capacity constraint is expressed as:

[0044]

[0045] In the formula, is a 0-1 decision variable representing the call state of interruptible load user d, and are the lower and upper response limits of user d participating in the interruptible load.

[0046] Preferably, when each demand response user submits a report to the system, it includes:

[0047] When there is excess wind power output, each transferable load user reports it to the system in the form of the utility function;

[0048] When the system output is insufficient, each transferable load user reports it to the system in the form of the loss function.

[0049] Preferably, the step of determining the incentive fee to be paid to the demand response user according to the promotion effect of the demand response user on the consumption of new energy includes:

[0050] The unit fee paid to demand response customers is determined using the following calculation:

[0051]

[0052] In the formula, π d,t It is used to represent the unit fee paid to demand response user d at time t. It is used to characterize the total cost or total utility of the demand response trading market after removing the demand response user d. It represents the set of loads that need to be transferred by the remaining demand response users after removing the demand response user d, expressed as a vector; The total market cost or total utility of all demand response users participating in the transaction; It is used to represent the total market cost or total utility remaining after removing user d when all demand response users participate in market transactions.

[0053] In a second aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed in a computer, the computer is caused to execute any of the incentive-compatible demand response trading market methods for promoting new energy consumption as described in the first aspect.

[0054] It can be seen from the above technical scheme that in the incentive-compatible demand response trading market promotion method for new energy consumption provided by the present invention, firstly, the grid topology information, generator set operation data, load data and new energy data are obtained, and then based on these data, the objective function is established with the minimum power purchase cost as the goal; further, the objective function is solved with power balance constraints, unit operation constraints, standby constraints and demand demand response as the constraint conditions of the objective function, and the consumption result including the total amount of transferred load is obtained, so that it is issued to the demand response user according to the total amount of transferred load, so that each demand response user reports to the system, and the incentive fee paid by the demand response user is determined according to the promotion effect of the demand response user on the new energy consumption. In this way, by paying incentive fees to users according to the promotion effect of the demand response user on the new energy consumption, the value of the demand response user to promote the new energy consumption can be accurately identified, and then the demand response user can be guided to report real information, and the demand response user is encouraged to actively provide support for the new energy consumption, which effectively overcomes the market efficiency loss that may be caused by strategic quotations. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A flow chart of a method for promoting new energy consumption in an incentive-compatible demand response trading market provided in an embodiment of the present invention.

[0056] Figure 2 A schematic diagram of the initial load of the system provided in an embodiment of the present invention.

[0057] Figure 3 The day-ahead wind power forecast provided by the embodiment of the present invention.

[0058] Figure 4 The active power planned output diagram of the units under the traditional scheduling model of Mode 1 provided in the embodiment of the present invention.

[0059] Figure 5 Mode 2 provided in the embodiment of the present invention takes into account the planned active power output diagram of the unit after the transferable load.

[0060] Figure 6 Mode 3 provided in the embodiment of the present invention takes into account the planned active power output diagram of the unit after the interruptible load.

[0061] Figure 7 Mode 4 provided in the embodiment of the present invention comprehensively considers the active power planned output diagram of the unit after the transferable and interruptible loads are considered.

[0062] Figure 8 Comparison of load curves before and after considering transferable loads provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0064] like Figure 1 As shown, the present invention provides an incentive-compatible demand response trading market to promote new energy consumption method, which may include the following steps:

[0065] Step 101: Obtaining grid topology information, generator set operation data, load data, and new energy data;

[0066] Step 102: Establish an objective function with the goal of minimizing the electricity purchase cost based on the grid topology information, generator set operation data, load data and new energy data;

[0067] Step 103: Taking the power balance constraint, the unit operation constraint, the reserve constraint and the demand response constraint as the constraint conditions of the objective function, solving the objective function to obtain the result of the consumption of new energy; wherein the consumption result includes the total amount of transferred load;

[0068] Step 104: Send the total amount of transferred load to the demand response users, so that each demand response user can report to the system;

[0069] Step 105: Determine the incentive fee to be paid to the demand response user according to the role of the demand response user in promoting the consumption of new energy, so as to guide each demand response user to report real information.

[0070] For step 101, grid topology information, generator set operation data, load data and new energy data are obtained;

[0071] In this step, the data used to obtain grid topology information, generator operation data, load data, and new energy data, etc. For example, it may include data of generator sets in the grid, wind curtailment, unit penalty costs for load shedding, users and load data of interruptible loads, maximum and minimum output limit data of the units, the ramping capability of the generators, the start-stop cost of the units, the positive and negative spinning reserve requirements of the units, and the maximum transferable load of transferable load users.

[0072] For step 102, an objective function is established with the goal of minimizing the electricity purchase cost according to the grid topology information, the generator set operation data, the load data and the new energy data;

[0073] When constructing the objective function, the goal is to minimize the system operating cost, that is, the minimum electricity purchase cost. At the same time, the impact of wind power access is considered, and the penalty cost of wind abandonment and load shedding is introduced into the objective function. Specifically, the established objective function may include:

[0074]

[0075] Among them, minF uc is the objective function, T is the set of scheduling periods, N g is a collection of conventional generator sets, D IL is the set of users participating in the interruptible load, f(p n,t ) is the power generation cost function, p n,t is the output of generator set n at time t, which is the decision variable; g n,t is the startup cost of generator set n at time t, and is the decision variable; is the spare capacity provided by interruptible load user d at time t, which is the decision variable; is the capacity compensation unit cost of interruptible load user d; The capacity cost for interruptible load response; C pena They are the unit penalty cost for wind curtailment and the unit penalty cost for load shedding respectively; are wind power abandonment and load shedding respectively, and are decision variables.

[0076] In this embodiment, the introduction of the two decision variables of wind curtailment and load shedding is mainly used as relaxation variables to ensure that the model has a solution, and the unit penalty cost of wind curtailment can reflect the priority of wind power consumption. If this value is much greater than the power generation cost of conventional units, the surface system should give priority to wind power consumption, and wind power will be abandoned only when it exceeds the system risk absorption capacity.

[0077] It should be noted that since there is a situation where the reserve is not used, the capacity cost has nothing to do with whether a load interruption occurs. As long as the dispatching decision allows the interruptible load users to participate in the reserve, they will pay capacity compensation according to the contract agreement based on the capacity of the reserve provided. The electricity cost is related to the actual load reduction. Only when the interruptible load is actually called upon to cause a load interruption in the event of an emergency in the power grid, will corresponding electricity compensation be given according to the actual load reduction.

[0078] For step 103, the objective function is solved with power balance constraint, unit operation constraint, reserve constraint and demand response constraint as constraint conditions of the objective function to obtain the result of new energy consumption; wherein the result of consumption includes the total amount of transferred load;

[0079] Considering that the unit commitment problem is a high-dimensional, discrete, non-convex and nonlinear optimization problem, the objective function is solved by considering power balance constraints, unit operation constraints, reserve constraints and demand response constraints as constraints of the objective function.

[0080] Among them, the power balance constraint can be expressed as:

[0081]

[0082] Among them, L t is the initial load of the system, is the response load of user d participating in the transferable load at time t; W t To forecast the output of wind power,

[0083] Unit operation constraints may include: output limit, unit ramp constraint, unit minimum start / stop time constraint, and start / stop cost constraint;

[0084] Among them, the output limit can be expressed as:

[0085]

[0086] In the formula, μ n,t A 0-1 decision variable representing the startup state of the unit, where 1 represents the unit running; and They are the minimum output limit and maximum output limit of the unit respectively;

[0087] The unit climbing constraint can be expressed as:

[0088]

[0089] In the formula, They are the hourly up-climbing capability and down-climbing capability of the generator respectively;

[0090] The minimum start and stop time constraint of the unit can be expressed as:

[0091]

[0092] Where D n and O n are the minimum downtime and minimum start-up time of unit n respectively; t∈T.

[0093] The start-stop cost constraint can be expressed as:

[0094]

[0095] In the formula, G n is the start-up and shutdown cost of unit n, t∈T.

[0096] Considering the random fluctuation characteristics of wind power, the system needs to reserve both positive and negative spinning reserves to cope with the changes in wind power output, and consider the utility of interruptible loads in providing reserves and integrate them into the spinning reserve constraints. In addition, it should be noted that in order to reflect the impact of wind power on the system, this solution does not consider load forecast errors. In this way, the reserve constraints can specifically include: positive spinning reserve constraints and negative spinning reserve constraints;

[0097] The positive spinning reserve constraint can be expressed as:

[0098]

[0099] In the formula, is the positive spinning reserve provided by unit n at time t, Positive spinning reserve demand for wind power;

[0100] The negative spinning reserve constraint can be expressed as:

[0101]

[0102] In the formula, is the negative spinning reserve provided by unit n at time t, Negative spinning reserve demand for wind power.

[0103] For demand response constraints, they can first include transferable load-related constraints, that is, transferable load participation in the demand response market. When wind power output is in excess, the system requires transferable loads to increase their load levels. Each transferable load user reports to the system in the form of a utility function, and the system uniformly dispatches to determine the amount of load that each transferable load needs to increase and obtain economic compensation; similarly, when the system output is insufficient, the system requires transferable load users to reduce their output levels. At this time, each transferable user reports to the system in the form of a loss function. Specifically, the relevant functions and constraints of transferable load-related constraints can be expressed as:

[0104]

[0105] In the formula, α1 and β1 are the first and second coefficients of the utility function, α2 and β2 are the first and second coefficients of the loss function, respectively. The utility function used to characterize the users of transferable load, The loss function used to characterize the users of transferable load, Used to characterize the capacity constraints of users who can shift load.

[0106] Secondly, the demand response constraint can also include an interruptible load response capacity constraint, which is expressed as:

[0107]

[0108] In the formula, is a 0-1 decision variable representing the call state of interruptible load user d, and are the lower and upper response limits of user d participating in the interruptible load.

[0109] It should be pointed out that since all models are mixed integer programming models, they can be solved by Python and CPLEX to determine the scheduling strategy and consumption results.

[0110] In step 104, the total amount of transferred load is sent to the demand response users so that each demand response user can report to the system;

[0111] In this step, when each demand response user reports to the system, if the wind power output is in excess, the system requires transferable loads to increase their load level. Each transferable load user reports to the system in the form of a utility function, and the system uniformly dispatches to determine the amount of load that each transferable load needs to increase and obtain economic compensation. Similarly, if the system output is insufficient, the system requires transferable load users to reduce their output level. At this time, each transferable user reports to the system in the form of a loss function.

[0112] For step 105, the incentive fee to be paid to the demand response user is determined according to the role of the demand response user in promoting the consumption of new energy, so as to guide each demand response user to report real information.

[0113] In this step, we consider measuring the role of demand response users in promoting the consumption of new energy based on the VCG mechanism, and paying fees to demand response users based on this, so as to guide demand response users to report real information, thereby encouraging demand response users to actively provide accurate support for the consumption of new energy and reduce the loss of market efficiency caused by users' strategic quotations. Specifically, the unit fee paid to demand response users can be determined using the following calculation formula:

[0114]

[0115] In the formula, π d,t It is used to represent the unit fee paid to demand response user d at time t. It is used to characterize the total cost or total utility of the demand response trading market after removing the demand response user d. C i,-d A utility function or loss function used to characterize the non-demand response user d; It represents the set of loads that need to be transferred by the remaining demand response users after removing the demand response user d, expressed as a vector; The total market cost or total utility of all demand response users participating in the transaction; It is used to represent the total market cost or total utility remaining after removing user d when all demand response users participate in market transactions.

[0116] The effect of this solution is further explained below with reference to specific example data.

[0117] Based on a 10-unit system, the 24-hour load data of a certain place in my country is used as the initial load for solution. The installed capacity of wind power is 400MW. The unit penalty cost of wind abandonment and load shedding is set to 5000$ / MWh, reflecting the system's priority dispatch principle and reliability requirements for wind power. The initial load of the system is as follows Figure 2 As shown in the figure, the wind power forecast power is as follows: Figure 3 shown.

[0118] To illustrate the effectiveness of this solution, the results of the four modes are compared. The description of each mode is shown in Table 1 below.

[0119] Table 1 Mode definition description

[0120] name Schema Definition Mode 1 Only consider the traditional dispatch mode on the power generation side, without DR Mode 2 Dispatch mode that incorporates only transferable loads Mode 3 Dispatch mode that only incorporates interruptible loads Mode 4 Comprehensive consideration of the dispatching mode of interruptible load and transferable load

[0121] Table 2 below shows the compensation costs for demand response users under different demand response trading market clearing mechanisms under Mode 2. As can be seen from the table, the incentive price under the centralized clearing mode is higher than the incentive price under the VCG mechanism. The reason is that under the centralized clearing mode, due to the small number of demand response market participants, demand response users can effectively exercise market power to make strategic bids, thereby raising the incentive price. From the perspective of load transfer, it can also be seen that the VCG mechanism can effectively improve the enthusiasm of demand response users and thus absorb more renewable energy generation. From the perspective of the final fees paid to demand response users, although the fees ultimately paid to demand response users under the VCG mechanism are slightly higher than those under the centralized clearing mechanism, the VCG mechanism is superior to the centralized clearing mechanism in terms of improving user enthusiasm and new energy consumption.

[0122] Table 2 Comparison of different demand response market prices in Mode 2

[0123] Clearing Mechanism Centralized Clearance VCG Mechanism Incentive price (￥ / MWh) 168.4 143.5 Load transfer capacity (MW) 2.14 2.52 Payment Fee (￥) 360.4 361.6

[0124] Table 3 compares the costs under the four modes. It can be seen from the table that after integrating DR, the system operating costs are reduced to varying degrees compared with the case without DR, and the model that comprehensively considers the two types of DR has the lowest cost in all aspects.

[0125] Table 3 System operation cost comparison

[0126]

[0127] In the four modes, the planned output of the unit is as follows: Figure 4-7 As shown, Figure 8 The load curve of the system changes after the load can be transferred. It can be seen from Table 3 that under the wind power consumption mode based on the traditional unit combination, all new energy sources cannot be consumed, resulting in wind abandonment and no load shedding. Figure 4 It can be seen that due to the constraints of the minimum start / shutdown time and minimum technical output of the units, not all new energy can be absorbed; and due to the system backup demand, the G8 and G9 units are only turned on for one hour during operation, which increases the frequent start and stop of the units, which not only increases the start and stop costs of the system, but also increases the risk of mechanical damage to the units.

[0128] from Figure 8 It can be seen from Figure 2 that the response of the transferable load to the electricity price smoothes the load curve. Figure 5 It can be seen that in mode 2, all wind power is absorbed. Figure 5 and Figure 4 It can be seen that in mode 2 (the fluctuation of unit output in different periods is small, and due to the effect of "shifting peaks and filling valleys", the peak period (such as Figure 5 The reduction of load during the period from 18:00 to 20:00 (mid-day) reduces the start-up and shutdown and output of higher-cost units, reduces the start-up and shutdown costs and power generation costs of the system, and thus reduces the overall operating costs of the system.

[0129] Comparing the cost of modes 1, 2, and 3 in Table 3, the number of operating units and the start-up and shutdown costs of the system in mode 3 are reduced compared with mode 1. The standby provided by the interruptible load replaces part of the unit standby, thereby reducing the number of units started to provide standby (G8, G9). This can also be confirmed by the reduction in the system start-up and shutdown costs. However, the interruptible load does not affect the load curve. Affected by the load change amplitude, combined with Figure 4 , 5 6, it can be seen that the unit output variation is still larger than that of mode 2. Further comparison shows that although the load curves of mode 1 and mode 3 are the same, the interruptible load to provide backup can avoid the start-up operation of generator sets G8 and G9.

[0130] Mode 4 comprehensively considers the role of transferable load in smoothing the load curve and interruptible load in providing backup and reducing costs. Figure 7 It can be seen that under mode 4, the power generation output fluctuation is the smallest, and the startup and operation of higher-cost units (G8 and G9) are effectively avoided, and the power generation cost and start-up and shutdown costs are the lowest.

[0131] A comprehensive comparative analysis of the four modes shows that both transferable loads and interruptible loads can play a role in reducing system operating costs and promoting wind power consumption. However, by comparing the two DR projects, it is obvious that in terms of reducing system operating costs and promoting wind power consumption, the role of interruptible loads as a demand response project is far less than that of transferable loads. Analyzing from the essence of the two demand response projects, as mentioned above, the participation of interruptible loads in demand response is in the form of users responding to interruption of part of the power supply, and only load reduction is done; in the operation of power grids containing new energy, the reason for abandoning wind and solar power is often due to the sudden increase in the output of new energy such as wind and solar power, resulting in "power generation > power consumption" in system operation. At this time, if there is only interruptible loads as a demand response, the effect of promoting the consumption of new energy is not obvious; transferable loads are users who decide the response time and method according to the price, and compared with interruptible loads, the load adjustment method is more flexible. When the output of new energy increases suddenly, users of transferable loads can increase the output to consume the newly generated new energy. Therefore, in terms of promoting the consumption of new energy, the role of transferable loads is higher than that of interruptible loads.

[0132] The present specification also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed in a computer, the computer is caused to execute a method in any one of the embodiments in the specification.

[0133] The present specification also provides a computing device, including a memory and a processor, wherein executable codes are stored in the memory, and when the processor executes the executable codes, a method in any embodiment of the present specification is implemented.

[0134] Since the device embodiments provided by the present invention are based on the same inventive concept as the method embodiments of this specification, the specific contents can be found in the description of the method embodiments of this specification and will not be repeated here.

[0135] The modules or units in the device of the embodiment of the present invention can be combined, divided and deleted according to actual needs. The above disclosure is only the preferred embodiment of the present invention, and of course it cannot be used to limit the scope of the rights of the present invention. Those skilled in the art can understand that all or part of the processes of the above embodiment are implemented, and the equivalent changes made according to the claims of the present invention still fall within the scope of the invention.

Claims

1. A method for promoting new energy consumption through an incentive-compatible demand response trading market, characterized in that: include: Obtain grid topology information, generator set operation data, load data and new energy data; According to the grid topology information, generator set operation data, load data and new energy data, an objective function is established with the goal of minimizing the electricity purchase cost; Taking power balance constraint, unit operation constraint, reserve constraint and demand response constraint as constraint conditions of the objective function, solving the objective function to obtain the result of new energy consumption; wherein the result of new energy consumption includes the total amount of transferred load; The total amount of transferred load is issued to demand response users, so that each demand response user can report to the system; The incentive fees paid to demand response users are determined based on their role in promoting the consumption of new energy, so as to guide each demand response user to report true information.

2. The method for promoting new energy consumption through an incentive-compatible demand response trading market according to claim 1, characterized in that: The objective function established includes: Among them, minF uc is the objective function, T is the set of scheduling periods, N g is a collection of conventional generator sets, D IL is the set of users participating in the interruptible load, f(p n,t ) is the power generation cost function, p n,t is the output of generator set n at time t, which is the decision variable; g n,t is the startup cost of generator set n at time t, and is the decision variable; is the spare capacity provided by interruptible load user d at time t, which is the decision variable; is the capacity compensation unit cost of interruptible load user d; The capacity cost for interruptible load response; C pena They are the unit penalty cost for wind curtailment and the unit penalty cost for load shedding respectively; are wind power abandonment and load shedding respectively, and are decision variables.

3. The method for promoting new energy consumption through an incentive-compatible demand response trading market according to claim 2, characterized in that: The power balance constraints include: Among them, L t is the initial load of the system, is the response load of user d participating in the transferable load at time t; W t To forecast the output of wind power, 4. The method for promoting new energy consumption through an incentive-compatible demand response trading market according to claim 3, characterized in that: The unit operation constraints include: output limit, unit climbing constraint, unit minimum start and stop time constraint and start and stop cost constraint; The output limit is expressed as: In the formula, μ n,t A 0-1 decision variable representing the startup state of the unit, where 1 represents the unit running; and They are the minimum output limit and maximum output limit of the unit respectively; The unit climbing constraint is expressed as: In the formula, They are the hourly up-climbing capacity and down-climbing capacity of the generator respectively; The minimum start and stop time constraint of the unit is expressed as: Where D n and O n are the minimum downtime and minimum start-up time of unit n respectively; The start-stop cost constraint is expressed as: In the formula, G n is the start-up and shutdown cost of unit n.

5. The method for promoting new energy consumption through an incentive-compatible demand response trading market according to claim 4, characterized in that: The reserve constraints include: positive spinning reserve constraints and negative spinning reserve constraints; The positive spinning reserve constraint is expressed as: In the formula, is the positive spinning reserve provided by unit n at time t, Positive spinning reserve demand for wind power; The negative spinning reserve constraint is expressed as: In the formula, is the negative spinning reserve provided by unit n at time t, Negative spinning reserve demand for wind power.

6. The method for promoting new energy consumption through an incentive-compatible demand response trading market according to claim 5, characterized in that: The demand response constraint includes a transferable load related constraint, which is expressed as: In the formula, α1 and β1 are the first and second coefficients of the utility function, α2 and β2 are the first and second coefficients of the loss function, respectively. The utility function used to characterize the users of transferable load, The loss function used to characterize the users of transferable load, Used to characterize the capacity constraints of users who can shift load.

7. The method for promoting new energy consumption through an incentive-compatible demand response trading market according to claim 5, characterized in that: The demand response constraint also includes an interruptible load response capacity constraint, which is expressed as: In the formula, is a 0-1 decision variable representing the call state of interruptible load user d, and are the lower and upper response limits of user d participating in the interruptible load.

8. The method for promoting new energy consumption through an incentive-compatible demand response trading market according to claim 6, characterized in that: When each demand response user submits a report to the system, it includes: When there is excess wind power output, each transferable load user reports it to the system in the form of the utility function; When the system output is insufficient, each transferable load user reports it to the system in the form of the loss function.

9. The method for promoting new energy consumption through an incentive-compatible demand response trading market according to claim 6, characterized in that: The incentive fee paid to the demand response user is determined based on the promotion effect of the demand response user on the consumption of new energy, including: The unit fee paid to demand response customers is determined using the following calculation: In the formula, π d,t It is used to represent the unit fee paid to demand response user d at time t. It is used to characterize the total cost or total utility of the demand response trading market after removing the demand response user d. It represents the set of loads that need to be transferred by the remaining demand response users after removing the demand response user d, expressed as a vector; The total market cost or total utility of all demand response users participating in the transaction; It is used to represent the total market cost or total utility remaining after removing user d when all demand response users participate in market transactions.

10. A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the method for promoting new energy consumption through an incentive-compatible demand response trading market as described in any one of claims 1 to 9.

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