Auxiliary service market joint clearing method considering participation of virtual power plant in peak regulation and frequency modulation

Abstract

An auxiliary service market combined clearing method considering participation of a virtual power plant in peak regulation and frequency modulation comprises the following steps: firstly, establishing an auxiliary service market day-ahead combined clearing model, then establishing an auxiliary service market intra-day rolling combined clearing model, and finally, combining the models. And implementing a multi-time scale auxiliary service market joint clearing strategy considering participation of the virtual power plant in peak regulation and frequency modulation. On the basis of the existing auxiliary service market clearing technology, the virtual power plant serving as a market main body is added, the coupling characteristic of the peak regulation auxiliary service and the frequency modulation auxiliary service is considered, and detailed modeling of the coupling characteristic of the peak regulation and frequency modulation auxiliary service, the external characteristic of the virtual power plant and the peak regulation and frequency modulation comprehensive performance of the virtual power plant is achieved; when the method is implemented, the connection relation of the day-ahead and day-in markets is considered, a multi-time-scale auxiliary service market joint clearing strategy considering participation of the virtual power plant in peak regulation and frequency modulation is provided, and the economical efficiency and the utilization efficiency of the virtual power plant are improved.

Description

Technical Field

[0001] The present invention relates to the field of power system dispatching and trading, and in particular to a joint clearing method for ancillary service markets applied to virtual power plants taking into account their participation in peak load and frequency regulation. Background Art

[0002] At present, with the construction of my country's power grid system, the "dual carbon" goal and the continuous advancement of the construction of new power systems, the proportion of thermal power generation in the power system has been significantly reduced, the penetration rate of renewable energy has gradually increased, and the flexibility of the power system has decreased. In order to improve the power grid regulation capability and promote the consumption of new energy, flexible resources such as peak and frequency regulation are urgently needed to ensure the safe and stable operation of the power system. Therefore, the virtual power plant is adopted. The so-called virtual power plant can make the internal distributed energy cooperate and has no specific requirements for the geographical location and composition of distributed energy. Therefore, it has become an emerging regulation method with strong flexibility, high adaptability and good economy. At this stage, the virtual power plant is in a business form that mainly participates in the auxiliary service market and participates in the energy market as a supplement. Therefore, it is necessary to study the market transaction mechanism and optimization clearing model of virtual power plants participating in multi-variety auxiliary services.

[0003] Under existing technologies, in the power trading market, the clearing mechanism of electric energy and ancillary services is a key link to ensure the safe, economical and efficient operation of the power system. Joint clearing and independent clearing are two main clearing methods, each with different meanings and characteristics, which have a profound impact on the operation and development of the power market.

[0004] The joint clearing, as the name implies, refers to the unified optimization and clearing of electricity and ancillary services as a whole. Under the joint clearing mechanism, the power market operator will comprehensively consider the supply and demand of electricity and the demand for ancillary services, and determine the optimal combination of electricity and ancillary services through optimization algorithms to maximize the overall benefits of the power market. The main features of joint clearing include:

[0005] 1. Integrity: Joint clearing regards electric energy and ancillary services as an indivisible whole, and achieves coordination and balance between the two through unified optimization.

[0006] 2. Efficiency: Joint clearing can make full use of the supply and demand information and price signals of the electricity market to achieve optimal allocation and efficient utilization of power resources.

[0007] 3. Fairness: Joint clearing ensures fair competition and rights protection of all market players in electricity trading through an open and transparent market mechanism.

[0008] Under the existing technology, some research has been done on the market transaction mechanism and optimized clearing model of virtual power plants participating in multi-variety ancillary services, as follows:

[0009] 1. "Market Clearing Coordination Mechanism for Spot Electricity and Frequency Regulation Ancillary Services Including Independent Energy Storage" - Proceedings of the CSEE, 2020, 40(S1):167-180. This paper analyzes the selection of declaration parameters, the processing of real-time market optimization, and the calculation of the opportunity cost of providing frequency regulation ancillary services when independent energy storage participates in the market. It proposes a market clearing coordination mechanism for spot electricity and frequency regulation ancillary services including independent energy storage, and gives mathematical models of the sequential clearing and joint clearing mechanisms.

[0010] 2. "Joint clearing model of day-ahead electricity market and deep peak-shaving market" - China Electric Power, 2022, 55(02):138-144. This paper takes the integration of day-ahead electricity trading and deep peak-shaving trading in Northeast China in the full-power centralized bidding mode as the background, and takes the minimum sum of system electricity cost, startup cost, peak-shaving cost and new energy power restriction penalty cost as the objective function, and proposes a joint clearing model of day-ahead electricity market and deep peak-shaving service market.

[0011] 3. "Clearing Method of Electric Vehicle Load Participating in Frequency Regulation Auxiliary Service Market Considering Substitution Effect" - Electric Power Automation Equipment, 2022, 42(07): 111-119. This paper analyzes the market competitiveness of electric vehicles participating in the frequency regulation auxiliary service market, proposes a frequency regulation resource quotation correction method considering substitution effect, and establishes a sequential clearing and joint clearing model of the frequency regulation auxiliary service market and the electric energy market.

[0012] 4. "Research on Joint Clearing Method of Electricity and Frequency Regulation Market Considering Dynamic Application of Multi-type Energy Storage Frequency Regulation Capacity" - Power System Technology, 2024, 48(07): 2833-2841. This paper analyzes the organizational form and pricing logic of energy storage participating in the electricity and frequency regulation markets, calculates the opportunity cost of frequency regulation resources based on the pre-clearing results of the electricity market, constructs the dynamic frequency regulation capacity application boundary, and establishes a frequency regulation market clearing model with the minimum total frequency regulation cost as the optimization goal.

[0013] However, it is found through practical application that the above-mentioned prior art has considerable limitations, as follows:

[0014] 1. Existing technologies rarely consider the coupling characteristics of peak-shaving ancillary services and frequency-regulation ancillary services, and there is little research on the joint clearing of peak-shaving and frequency-regulation markets;

[0015] 2. Existing technologies rarely consider virtual power plants as market entities, and lack the characterization of the external characteristics of virtual power plants and the comprehensive performance of virtual power plants in peak and frequency regulation in the optimization clearing model. Summary of the invention

[0016] In view of the problem that the coupling characteristics of peak-shaving ancillary services and frequency regulation ancillary services are less considered in the clearing technologies of the prior art, and the problem that virtual power plants as market entities are less considered in the clearing technologies, the present invention proposes a joint clearing method for the ancillary service market that considers the participation of virtual power plants in peak-shaving and frequency regulation. The present invention models the coupling characteristics of peak-shaving and frequency regulation ancillary services, the external characteristics of virtual power plants, and the comprehensive performance of virtual power plants in peak-shaving and frequency regulation, and proposes a technical solution for the multi-time-scale ancillary service market joint clearing strategy that considers the participation of virtual power plants in peak-shaving and frequency regulation.

[0017] The present invention provides a joint clearing method for ancillary service markets that considers the participation of virtual power plants in peak load and frequency regulation, and the specific steps are as follows:

[0018] 1) Establish a day-ahead joint clearing model for the ancillary services market;

[0019] 2) Establish an intraday rolling joint clearing model for the ancillary service market;

[0020] 3) Combine steps 1) and 2) to implement a multi-time-scale ancillary service market joint clearing strategy that considers the participation of virtual power plants in peak and frequency regulation.

[0021] According to the present invention, a joint clearing method for ancillary service market considering the participation of virtual power plants in peak-shaving and frequency regulation is characterized in that the step 1) of establishing a day-ahead joint clearing model for ancillary service market includes: 1.1) establishing a day-ahead joint clearing objective function, 1.2) establishing a day-ahead joint clearing comprehensive peak-shaving and frequency regulation performance index, and 1.3) establishing a day-ahead joint clearing constraint condition, a total of 3 parts.

[0022] According to a joint clearing method of ancillary service market considering the participation of virtual power plants in peak load and frequency regulation of the present invention, it is characterized in that the step 1.1) establishes a day-ahead joint clearing objective function, which is specifically:

[0023] The optimization goal is to minimize the clearing cost of day-ahead transactions in the ancillary service market. The objective function is as follows:

[0024]

[0025] Where: i is the number of the virtual power plant, i = 1, 2, ..., N; N is the total number of virtual power plants;

[0026] t is the trading period, t = 1, 2, …, T; T is the day-ahead optimization period;

[0027] C 1 is the day-ahead market clearing fee;

[0028] is the clearing cost of peak load trading of virtual power plant i during period t;

[0029] is the frequency regulation transaction clearing cost of virtual power plant i during period t;

[0030] In the above formula (1), the peak load transaction clearing fee is as follows:

[0031]

[0032] Where: is the peak-shaving quotation correction coefficient of virtual power plant i based on its historical peak-shaving performance;

[0033] Declare a price for the peak-shaving capacity of virtual power plant i during period t;

[0034] is the peak-shaving market winning bid capacity of virtual power plant i during period t;

[0035] In the above formula (1), the clearing fee of frequency modulation transaction is as follows:

[0036]

[0037] Where: is the frequency regulation quotation correction coefficient of virtual power plant i based on historical frequency regulation performance;

[0038] Declare a price for the frequency regulation capacity of virtual power plant i during period t;

[0039] The declared price for the frequency regulation mileage of virtual power plant i during period t;

[0040] s is the ratio of frequency modulation mileage to frequency modulation capacity;

[0041] is the winning bid capacity of virtual power plant i in the frequency regulation market during period t.

[0042] According to the present invention, a joint clearing method for ancillary service market considering the participation of virtual power plants in peak-shaving and frequency regulation is characterized in that the step 1.2) establishes a comprehensive peak-shaving and frequency regulation performance index for joint clearing on the day before, which is divided into five parts: response time index, regulation rate index, regulation accuracy index, comprehensive peak-shaving and frequency regulation performance index and peak-shaving and frequency regulation quotation correction coefficient, which are specifically:

[0043] 1) Response time indicators:

[0044]

[0045] Where: is the response time indicator of virtual power plant i participating in peak load regulation;

[0046] is the response time of virtual power plant i participating in peak load regulation;

[0047] The maximum response time for the virtual power plant to participate in peak load regulation;

[0048] is the response time indicator of virtual power plant i participating in frequency regulation;

[0049] is the response time of virtual power plant i participating in frequency regulation;

[0050] The maximum response time for a virtual power plant to participate in frequency regulation;

[0051] 2) Adjustment rate index:

[0052]

[0053] Where: is the regulation rate index of the virtual power plant i participating in the peak regulation;

[0054] is the regulation rate of virtual power plant i participating in peak load regulation;

[0055] The fastest regulation rate for virtual power plants to participate in peak load regulation;

[0056] is the regulation rate index of the virtual power plant i participating in frequency regulation;

[0057] is the frequency regulation rate of virtual power plant i;

[0058] The fastest frequency regulation rate for virtual power plants to participate in frequency regulation;

[0059] 3) Adjustment accuracy index:

[0060]

[0061]

[0062] Where: is the regulation accuracy index of the virtual power plant i participating in peak regulation;

[0063] is the regulation error of virtual power plant i participating in peak regulation;

[0064] is the maximum regulation error of the virtual power plant participating in peak regulation;

[0065] is the regulation accuracy index of the virtual power plant i participating in frequency regulation;

[0066] is the regulation error of virtual power plant i participating in frequency regulation;

[0067] is the maximum regulation error of the virtual power plant participating in frequency regulation;

[0068] 4) Comprehensive peak load regulation and frequency regulation performance indicators:

[0069]

[0070] m+n+l=1 (12)

[0071] Where: is the comprehensive peak load performance index of virtual power plant i;

[0072] is the comprehensive frequency regulation performance index of virtual power plant i;

[0073] m, n, and l are the weights of the response time index, the regulation rate index, and the regulation accuracy index, respectively;

[0074] 5) Peak load and frequency regulation quotation correction coefficient:

[0075]

[0076] According to the present invention, a joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation is characterized in that the step 1.3) establishes a joint clearing constraint condition for the day ahead, and the constraint condition is divided into: mutual exclusion constraint of peak load and frequency regulation, demand constraint of peak load and frequency regulation, capacity constraint of winning bid of peak load and frequency regulation, segmented quotation constraint of peak load market, upper and lower limit constraint of virtual power plant power, regulation rate constraint of virtual power plant and continuous regulation duration constraint of virtual power plant, a total of 7 parts, which are as follows:

[0077] 1) Peak shaving and frequency modulation mutually exclusive constraints:

[0078] A virtual power plant can only choose to participate in one of the peak load regulation market or the frequency regulation market at any one time, as follows:

[0079]

[0080] Where: is the peak-shaving market state variable of virtual power plant i in period t, which is 0 or 1, 1 means winning the bid, and 0 means not winning the bid;

[0081] is the frequency regulation market state variable of virtual power plant i in period t, which is 0 or 1, 1 means winning the bid, and 0 means not winning the bid;

[0082] 2) Peak load and frequency regulation requirements:

[0083]

[0084] Where: is the peak load capacity demand of the power grid during period t;

[0085] is the power grid frequency regulation capacity demand during period t;

[0086] is the power grid frequency regulation mileage requirement during period t;

[0087] 3) Peak load and frequency regulation bidding capacity constraints:

[0088]

[0089] Where: The minimum declared capacity for the peak-shaving market;

[0090] The minimum declared capacity for the frequency regulation market;

[0091] Declare capacity for the peak-shaving market of virtual power plant i during period t;

[0092] Declare capacity for the frequency regulation market of virtual power plant i in period t;

[0093] 4) Constraints on segmented quotation in the peak-shaving market:

[0094] Virtual power plants participate in the peak load regulation market by adopting segmented bidding, which is divided into 5 segments as follows:

[0095]

[0096] Where: These are the declared prices for the 1st, 2nd, 3rd, 4th and 5th segments of the peak-shaving capacity of virtual power plant i;

[0097] Using 5 variables that are either 0 or 1, the above equation is converted into a linear constraint as follows:

[0098]

[0099]

[0100] Where: All are 0 or 1 variables;

[0101] 5) Virtual power plant power upper and lower limit constraints:

[0102] The upper and lower frequency regulation capacities of the virtual power plant are the same, as follows:

[0103]

[0104] Where: is the power baseline of virtual power plant i during period t;

[0105] is the overall power upper limit of virtual power plant i during period t;

[0106] is the overall power lower limit of virtual power plant i during period t;

[0107] 6) Virtual power plant regulation rate constraints:

[0108]

[0109] Where: is the upper limit of the overall regulation rate of virtual power plant i during period t;

[0110] is the lower limit of the overall regulation rate of virtual power plant i during period t;

[0111] 7) Constraints on the continuous adjustment time of virtual power plants

[0112]

[0113] Where: is the maximum continuous adjustment time of virtual power plant i.

[0114] According to the present invention, a method for joint clearing of ancillary service market taking into account the participation of virtual power plants in peak load and frequency regulation is characterized in that the step 2) of establishing an intraday rolling joint clearing model of the ancillary service market includes: 2.1) establishing an intraday rolling joint clearing objective function and 2.2) establishing intraday rolling joint clearing constraints, a total of 2 parts.

[0115] According to a joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation of the present invention, it is characterized in that the intraday rolling joint clearing objective function of step 2.1) is established, which is specifically:

[0116] Based on the winning virtual power plant and its call period determined by the day-ahead clearing, further intraday rolling clearing is carried out, and the optimization goal is to minimize the intraday transaction clearing fee of the ancillary service market. The objective function is:

[0117]

[0118] Where: C 2 It is the intraday market clearing fee;

[0119] M is the intraday optimization period.

[0120] According to the present invention, a joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation is characterized in that the step 2.2) establishes intraday rolling joint clearing constraints, which are divided into: peak load and frequency regulation demand constraints, peak load and frequency regulation winning capacity constraints, peak load market segmented quotation constraints, virtual power plant power upper and lower limit constraints and virtual power plant regulation rate constraints, a total of 5 parts, as follows:

[0121] 1) Peak load and frequency regulation requirements:

[0122]

[0123] 2) Peak load and frequency regulation bidding capacity constraints:

[0124]

[0125] 3) Constraints on segmented quotation in the peak-shaving market:

[0126]

[0127] 4) Virtual power plant power upper and lower limit constraints:

[0128]

[0129] 5) Virtual power plant regulation rate constraints:

[0130]

[0131] According to the present invention, a joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation is characterized in that the step 3) is combined with step 1) and step 2) to implement a multi-time scale joint clearing strategy for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation. The specific steps of the implementation are as follows:

[0132] 1) Confirm the operating parameters of the virtual power plant, including upper and lower limits, regulation rate, and continuous regulation time;

[0133] 2) In the day-ahead market, the virtual power plant predicts and reports the benchmark output curve or power consumption curve for the next day;

[0134] 3) The dispatch center releases the peak load and frequency regulation requirements for the next day;

[0135] 4) Virtual power plants provide quotation based on the day-ahead volume for the peak load regulation market and the frequency regulation market;

[0136] 5) Establish the objective function of the day-ahead joint clearing optimization problem according to equations (1)-(14);

[0137] 6) Establish the constraint conditions of the day-ahead joint clearing optimization problem according to equations (15)-(32);

[0138] 7) Solve the problem using a commercial solver;

[0139] 8) Output the winning virtual power plant, winning capacity and marginal unified clearing price, and the dispatch center publishes the day-ahead clearing results;

[0140] 9) In the intraday market, the dispatch center releases the peak load and frequency regulation requirements for the next 4 hours;

[0141] 10) Based on the day-ahead clearing results, the virtual power plant makes daily quotation for the peak load regulation market and the frequency regulation market;

[0142] 11) According to formula (33), the objective function of the intraday rolling joint clearing optimization problem is established;

[0143] 12) According to equations (34) to (43), establish the constraints of the intraday rolling joint clearing optimization problem;

[0144] 13) Solve the problem using a commercial solver;

[0145] 14) Output the winning virtual power plant, winning capacity and marginal unified clearing price, and the dispatch center publishes the intraday clearing results;

[0146] 15) Determine whether the intraday rolling optimization clearing is completed. If not, return to step 9.9). If yes, end the intraday rolling optimization clearing.

[0147] According to the present invention, a joint clearing method for ancillary service markets taking into account the participation of virtual power plants in peak load and frequency regulation is characterized in that the commercial solver is specifically a gurobi solver.

[0148] The gurobi solver has faster optimization speed and accuracy. At the same time, the gurobi solver is also suitable for the field of power management as a planning optimizer.

[0149] The present invention provides a joint clearing method for ancillary service markets that takes into account the participation of virtual power plants in peak shaving and frequency regulation. Aiming at the scenario in which virtual power plants participate in peak shaving and frequency regulation ancillary services, the coupling characteristics of peak shaving and frequency regulation ancillary services, external characteristics of virtual power plants, and comprehensive performance of virtual power plants in peak shaving and frequency regulation are modeled. Considering the connection between the day-ahead and intraday markets, a multi-time-scale joint clearing strategy for ancillary service markets that takes into account the participation of virtual power plants in peak shaving and frequency regulation is proposed.

[0150] The following beneficial effects are achieved by using the joint clearing method of the auxiliary service market considering the participation of virtual power plants in peak load and frequency regulation according to the present invention:

[0151] 1. The present invention adopts a joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation. Based on the existing ancillary service market clearing technology, the virtual power plant is added as a market subject, the coupling characteristics of peak load and frequency regulation ancillary services are considered, and the detailed modeling of the coupling characteristics of peak load and frequency regulation ancillary services, the external characteristics of virtual power plants and the comprehensive performance of peak load and frequency regulation of virtual power plants is realized;

[0152] 2. When implementing the joint clearing method of the ancillary service market that takes into account the participation of virtual power plants in peak-shaving and frequency regulation, the present invention takes into account the connection between the day-ahead and intraday markets, proposes a multi-time-scale joint clearing strategy for the ancillary service market that takes into account the participation of virtual power plants in peak-shaving and frequency regulation, further characterizes the external characteristics of virtual power plants and the comprehensive performance of virtual power plants in peak-shaving and frequency regulation, and improves the economy and utilization efficiency of virtual power plants. BRIEF DESCRIPTION OF THE DRAWINGS

[0153] Figure 1 This is a specific flow chart of a joint clearing method for ancillary service markets that takes into account the participation of virtual power plants in peak and frequency regulation according to the present invention. DETAILED DESCRIPTION

[0154] The following, in conjunction with the accompanying drawings and embodiments, further describes the technical means, creative features, objectives and effects achieved by the joint clearing method for ancillary service markets that takes into account the participation of virtual power plants in peak and frequency regulation of the present invention.

[0155] Embodiment:

[0156] like Figure 1 As shown in the figure, a joint clearing method for ancillary service market considering the participation of virtual power plants in peak load regulation and frequency regulation is proposed. The specific steps are as follows:

[0157] 1) Establish a day-ahead joint clearing model for the ancillary services market;

[0158] 2) Establish an intraday rolling joint clearing model for the ancillary service market;

[0159] 3) Combine steps 1) and 2) to implement a multi-time-scale ancillary service market joint clearing strategy that considers the participation of virtual power plants in peak and frequency regulation.

[0160] Step 1) establishes a day-ahead joint clearing model for the ancillary service market, including: 1.1) establishing a day-ahead joint clearing objective function, 1.2) establishing a day-ahead joint clearing comprehensive peak-shaving and frequency-regulating performance index, and 1.3) establishing day-ahead joint clearing constraints, a total of 3 parts.

[0161] Step 1.1) Establish the joint clearing objective function for the day ahead, which is as follows:

[0162] The optimization goal is to minimize the clearing cost of day-ahead transactions in the ancillary service market. The objective function is as follows:

[0163]

[0164] Where: i is the number of the virtual power plant, i = 1, 2, ..., N; N is the total number of virtual power plants;

[0165] t is the trading period, t = 1, 2, …, T; T is the day-ahead optimization period;

[0166] C 1 is the day-ahead market clearing fee;

[0167] is the clearing cost of peak load trading of virtual power plant i during period t;

[0168] is the frequency regulation transaction clearing cost of virtual power plant i during period t;

[0169] In the above formula (1), the peak load transaction clearing fee is as follows:

[0170]

[0171] Where: is the peak-shaving quotation correction coefficient of virtual power plant i based on its historical peak-shaving performance;

[0172] Declare a price for the peak-shaving capacity of virtual power plant i during period t;

[0173] is the peak-shaving market winning bid capacity of virtual power plant i during period t;

[0174] In the above formula (1), the clearing fee of frequency modulation transaction is as follows:

[0175]

[0176] Where: is the frequency regulation quotation correction coefficient of virtual power plant i based on historical frequency regulation performance;

[0177] Declare a price for the frequency regulation capacity of virtual power plant i during period t;

[0178] The declared price for the frequency regulation mileage of virtual power plant i during period t;

[0179] s is the ratio of frequency modulation mileage to frequency modulation capacity;

[0180] is the winning bid capacity of virtual power plant i in the frequency regulation market during period t.

[0181] Step 1.2) Establish the comprehensive peak-shaving and frequency-shaving performance index of joint clearing on the day ahead. The index is divided into five parts: response time index, regulation rate index, regulation accuracy index, comprehensive peak-shaving and frequency-shaving performance index and peak-shaving and frequency-shaving quotation correction coefficient, which are as follows:

[0182] 1) Response time indicators:

[0183]

[0184] Where: is the response time indicator of virtual power plant i participating in peak load regulation;

[0185] is the response time of virtual power plant i participating in peak load regulation;

[0186] The maximum response time for the virtual power plant to participate in peak load regulation;

[0187] is the response time indicator of virtual power plant i participating in frequency regulation;

[0188] is the response time of virtual power plant i participating in frequency regulation;

[0189] The maximum response time for a virtual power plant to participate in frequency regulation;

[0190] 2) Adjustment rate index:

[0191]

[0192] Where: is the regulation rate index of the virtual power plant i participating in the peak regulation;

[0193] is the regulation rate of virtual power plant i participating in peak load regulation;

[0194] The fastest regulation rate for virtual power plants to participate in peak load regulation;

[0195] is the regulation rate index of the virtual power plant i participating in frequency regulation;

[0196] is the frequency regulation rate of virtual power plant i;

[0197] The fastest frequency regulation rate for virtual power plants to participate in frequency regulation;

[0198] 3) Adjustment accuracy index:

[0199]

[0200] Where: is the regulation accuracy index of the virtual power plant i participating in peak regulation;

[0201] is the regulation error of virtual power plant i participating in peak regulation;

[0202] is the maximum regulation error of the virtual power plant participating in peak regulation;

[0203] is the regulation accuracy index of the virtual power plant i participating in frequency regulation;

[0204] is the regulation error of virtual power plant i participating in frequency regulation;

[0205] is the maximum regulation error of the virtual power plant participating in frequency regulation;

[0206] 4) Comprehensive peak load regulation and frequency regulation performance indicators:

[0207]

[0208] m+n+l=1 (12)

[0209] Where: is the comprehensive peak load performance index of virtual power plant i;

[0210] is the comprehensive frequency regulation performance index of virtual power plant i;

[0211] m, n, and l are the weights of the response time index, the regulation rate index, and the regulation accuracy index, respectively;

[0212] 5) Peak load and frequency regulation quotation correction coefficient:

[0213]

[0214] Step 1.3) Establish the joint clearing constraints on the day ahead. The constraints are divided into: peak-shaving and frequency-shaving mutual exclusion constraints, peak-shaving and frequency-shaving demand constraints, peak-shaving and frequency-shaving winning capacity constraints, peak-shaving market segmented quotation constraints, virtual power plant power upper and lower limit constraints, virtual power plant regulation rate constraints and virtual power plant continuous regulation time constraints, a total of 7 parts, as follows:

[0215] 1) Peak shaving and frequency modulation mutually exclusive constraints:

[0216] A virtual power plant can only choose to participate in one of the peak load regulation market or the frequency regulation market at any one time, as follows:

[0217]

[0218] Where: is the peak-shaving market state variable of virtual power plant i in period t, which is 0 or 1, 1 means winning the bid, and 0 means not winning the bid;

[0219] is the frequency regulation market state variable of virtual power plant i in period t, which is 0 or 1, 1 means winning the bid, and 0 means not winning the bid;

[0220] 2) Peak load and frequency regulation requirements:

[0221]

[0222] Where: is the peak load capacity demand of the power grid during period t;

[0223] is the power grid frequency regulation capacity demand during period t;

[0224] is the power grid frequency regulation mileage requirement during period t;

[0225] 3) Peak load and frequency regulation bidding capacity constraints:

[0226]

[0227] Where: The minimum declared capacity for the peak-shaving market;

[0228] The minimum declared capacity for the frequency regulation market;

[0229] Declare capacity for the peak-shaving market of virtual power plant i during period t;

[0230] Declare capacity for the frequency regulation market of virtual power plant i in period t;

[0231] 4) Constraints on segmented quotation in the peak-shaving market:

[0232] Virtual power plants participate in the peak load regulation market by adopting segmented bidding, which is divided into 5 segments as follows:

[0233]

[0234] Where: These are the declared prices for the 1st, 2nd, 3rd, 4th and 5th segments of the peak-shaving capacity of virtual power plant i;

[0235] Using 5 variables that are either 0 or 1, the above equation is converted into a linear constraint as follows:

[0236]

[0237] Where: All are 0 or 1 variables;

[0238] 5) Virtual power plant power upper and lower limit constraints:

[0239] The upper and lower frequency regulation capacities of the virtual power plant are the same, as follows:

[0240]

[0241] Where: is the power baseline of virtual power plant i during period t;

[0242] is the overall power upper limit of virtual power plant i during period t;

[0243] is the overall power lower limit of virtual power plant i during period t;

[0244] 6) Virtual power plant regulation rate constraints:

[0245]

[0246] Where: is the upper limit of the overall regulation rate of virtual power plant i during period t;

[0247] is the lower limit of the overall regulation rate of virtual power plant i during period t;

[0248] 7) Constraints on the continuous adjustment time of virtual power plants

[0249]

[0250] Where: is the maximum continuous adjustment time of virtual power plant i.

[0251] Step 2) establishes an intraday rolling joint clearing model for the ancillary service market, including: 2.1) establishing an intraday rolling joint clearing objective function and 2.2) establishing intraday rolling joint clearing constraints, a total of 2 parts.

[0252] Step 2.1) establishes the intraday rolling joint clearing objective function, which is specifically:

[0253] Based on the winning virtual power plant and its call period determined by the day-ahead clearing, further intraday rolling clearing is carried out, and the optimization goal is to minimize the intraday transaction clearing fee of the ancillary service market. The objective function is:

[0254]

[0255] Where: C 2 It is the intraday market clearing fee;

[0256] M is the intraday optimization period.

[0257] Step 2.2) establishes the intraday rolling joint clearing constraints, which are divided into five parts: peak-shaving and frequency-regulation demand constraints, peak-shaving and frequency-regulation winning capacity constraints, peak-shaving market segmented quotation constraints, virtual power plant power upper and lower limit constraints and virtual power plant regulation rate constraints, as follows:

[0258] 1) Peak load and frequency regulation requirements:

[0259]

[0260] 2) Peak load and frequency regulation bidding capacity constraints:

[0261]

[0262] 3) Constraints on segmented quotation in the peak-shaving market:

[0263]

[0264] 4) Virtual power plant power upper and lower limit constraints:

[0265]

[0266] 5) Virtual power plant regulation rate constraints:

[0267]

[0268] Step 3) combines steps 1) and 2) to implement a multi-time scale ancillary service market joint clearing strategy that considers the participation of virtual power plants in peak and frequency regulation. The specific steps of this implementation are as follows:

[0269] 1) Confirm the operating parameters of the virtual power plant, including upper and lower limits, regulation rate, and continuous regulation time;

[0270] 2) In the day-ahead market, the virtual power plant predicts and reports the benchmark output curve or power consumption curve for the next day;

[0271] 3) The dispatch center releases the peak load and frequency regulation requirements for the next day;

[0272] 4) Virtual power plants provide quotation based on the day-ahead volume for the peak load regulation market and the frequency regulation market;

[0273] 5) Establish the objective function of the day-ahead joint clearing optimization problem according to equations (1)-(14);

[0274] 6) Establish the constraint conditions of the day-ahead joint clearing optimization problem according to equations (15)-(32);

[0275] 7) Solve the problem using a commercial solver;

[0276] 8) Output the winning virtual power plant, winning capacity and marginal unified clearing price, and the dispatch center publishes the day-ahead clearing results;

[0277] 9) In the intraday market, the dispatch center releases the peak load and frequency regulation requirements for the next 4 hours;

[0278] 10) Based on the day-ahead clearing results, the virtual power plant makes daily quotation for the peak load regulation market and the frequency regulation market;

[0279] 11) According to formula (33), the objective function of the intraday rolling joint clearing optimization problem is established;

[0280] 12) According to equations (34) to (43), establish the constraints of the intraday rolling joint clearing optimization problem;

[0281] 13) Solve the problem using a commercial solver;

[0282] 14) Output the winning virtual power plant, winning capacity and marginal unified clearing price, and the dispatch center publishes the intraday clearing results;

[0283] 15) Determine whether the intraday rolling optimization clearing is completed. If not, return to step 9.9). If yes, end the intraday rolling optimization clearing.

[0284] In this embodiment, the above steps are performed by a commercial solver, and the commercial solver is specifically a gurobi solver.

[0285] It should be noted that in the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0286] In addition, those skilled in the art should recognize that the above embodiments are only used to illustrate the present application, and are not used to limit the present application. As long as they are within the spirit of the present application, any changes or modifications to the above embodiments will fall within the scope of the claims of the present application.

Claims

1. A joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation, the specific steps of which are as follows: 1) Establish a day-ahead joint clearing model for the ancillary services market; 2) Establish an intraday rolling joint clearing model for the ancillary service market; 3) Combine steps 1) and 2) to implement a multi-time-scale ancillary service market joint clearing strategy that considers the participation of virtual power plants in peak and frequency regulation.

2. A joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation as claimed in claim 1, characterized in that: The step 1) of establishing a day-ahead joint clearing model for the ancillary service market comprises three parts: 1.1) establishing a day-ahead joint clearing objective function, 1.2) establishing a day-ahead joint clearing comprehensive peak-shaving and frequency-regulating performance index, and 1.3) establishing day-ahead joint clearing constraints.

3. A joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation as claimed in claim 2, characterized in that: The step 1.1) establishes the day-ahead joint clearing objective function, which is specifically: The optimization goal is to minimize the clearing cost of day-ahead transactions in the ancillary service market. The objective function is as follows: Where: i is the number of the virtual power plant, i = 1, 2, ..., N; N is the total number of virtual power plants; t is the trading period, t = 1, 2, …, T; T is the day-ahead optimization period; C1 is the day-ahead market clearing cost; is the clearing cost of peak load trading of virtual power plant i during period t; is the frequency regulation transaction clearing cost of virtual power plant i during period t; In the above formula (1), the peak load transaction clearing fee is as follows: Where: is the peak-shaving quotation correction coefficient of virtual power plant i based on its historical peak-shaving performance; Declare a price for the peak-shaving capacity of virtual power plant i during period t; is the peak-shaving market winning bid capacity of virtual power plant i during period t; In the above formula (1), the clearing fee of frequency modulation transaction is as follows: Where: is the frequency regulation quotation correction coefficient of virtual power plant i based on historical frequency regulation performance; Declare a price for the frequency regulation capacity of virtual power plant i during period t; The declared price for the frequency regulation mileage of virtual power plant i during period t; s is the ratio of frequency modulation mileage to frequency modulation capacity; is the winning bid capacity of virtual power plant i in the frequency regulation market during period t.

4. A joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation as claimed in claim 2, characterized in that: The step 1.2) establishes the comprehensive peak-shaving and frequency-regulating performance index of the joint clearing on the day ahead, which is divided into five parts: response time index, regulation rate index, regulation accuracy index, comprehensive peak-shaving and frequency-regulating performance index and peak-shaving and frequency-regulating quotation correction coefficient, which are specifically: 4.1) Response time indicators: Where: is the response time indicator of virtual power plant i participating in peak load regulation; is the response time of virtual power plant i participating in peak load regulation; The maximum response time for the virtual power plant to participate in peak load regulation; is the response time indicator of virtual power plant i participating in frequency regulation; is the response time of virtual power plant i participating in frequency regulation; The maximum response time for a virtual power plant to participate in frequency regulation; 4.2) Adjustment rate index: Where: is the regulation rate index of the virtual power plant i participating in the peak regulation; is the regulation rate of virtual power plant i participating in peak load regulation; The fastest regulation rate for virtual power plants to participate in peak load regulation; is the regulation rate index of the virtual power plant i participating in frequency regulation; is the frequency regulation rate of virtual power plant i; The fastest frequency regulation rate for virtual power plants to participate in frequency regulation; 4.3) Adjustment accuracy index: Where: is the regulation accuracy index of the virtual power plant i participating in peak regulation; is the regulation error of virtual power plant i participating in peak load regulation; is the maximum regulation error of the virtual power plant participating in peak regulation; is the regulation accuracy index of the virtual power plant i participating in frequency regulation; is the regulation error of virtual power plant i participating in frequency regulation; is the maximum regulation error of the virtual power plant participating in frequency regulation; 4.4) Comprehensive peak load regulation and frequency regulation performance indicators: m+n+l=1 (12) Where: is the comprehensive peak load performance index of virtual power plant i; is the comprehensive frequency regulation performance index of virtual power plant i; m, n, and l are the weights of the response time index, the regulation rate index, and the regulation accuracy index, respectively; 4.5) Peak load and frequency regulation quotation correction coefficient:

5. A joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation as claimed in claim 2, characterized in that: The step 1.3) establishes the day-ahead joint clearing constraint conditions, which are divided into: peak-shaving and frequency-regulation mutual exclusion constraint, peak-shaving and frequency-regulation demand constraint, peak-shaving and frequency-regulation winning capacity constraint, peak-shaving market segmented quotation constraint, virtual power plant power upper and lower limit constraint, virtual power plant regulation rate constraint and virtual power plant continuous regulation time constraint, a total of 7 parts, as follows: 5.1) Peak shaving and frequency modulation mutually exclusive constraints: A virtual power plant can only choose to participate in one of the peak load regulation market or the frequency regulation market at any one time, as follows: Where: is the peak-shaving market state variable of virtual power plant i in period t, which is 0 or 1, 1 means winning the bid, and 0 means not winning the bid; is the frequency regulation market state variable of virtual power plant i in period t, which is 0 or 1, 1 means winning the bid, and 0 means not winning the bid; 5.2) Peak load and frequency regulation requirements: Where: is the peak load capacity demand of the power grid during period t; is the power grid frequency regulation capacity demand during period t; is the power grid frequency regulation mileage requirement during period t; 5.3) Peak load and frequency regulation bidding capacity constraints: Where: The minimum declared capacity for the peak-shaving market; The minimum declared capacity for the frequency regulation market; Declare capacity for the peak-shaving market of virtual power plant i during period t; Declare capacity for the frequency regulation market of virtual power plant i in period t; 5.4) Constraints on segmented bidding in the peak-shaving market: Virtual power plants participate in the peak load regulation market by adopting segmented bidding, which is divided into 5 segments as follows: Where: These are the declared prices for the 1st, 2nd, 3rd, 4th and 5th segments of the peak-shaving capacity of virtual power plant i; Using 5 variables that are either 0 or 1, the above equation is converted into a linear constraint as follows: Where: All are 0 or 1 variables; 5.5) Virtual power plant power upper and lower limit constraints: The upper and lower frequency regulation capacities of the virtual power plant are the same, as follows: Where: is the power baseline of virtual power plant i during period t; is the overall power upper limit of virtual power plant i during period t; is the overall power lower limit of virtual power plant i during period t; 5.6) Virtual power plant regulation rate constraints: Where: is the upper limit of the overall regulation rate of virtual power plant i during period t; is the lower limit of the overall regulation rate of virtual power plant i during period t; 5.7) Constraints on the continuous adjustment time of virtual power plants Where: T i max is the maximum continuous adjustment time of virtual power plant i.

6. A joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation as claimed in claim 1, characterized in that: The step 2) of establishing an intraday rolling joint clearing model for the auxiliary service market includes: 2.1) establishing an intraday rolling joint clearing objective function and 2.2) establishing intraday rolling joint clearing constraints, a total of 2 parts.

7. A joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation as claimed in claim 6, characterized in that: The step 2.1) of establishing the intraday rolling joint clearing objective function is specifically: Based on the winning virtual power plant and its call period determined by the day-ahead clearing, further intraday rolling clearing is carried out, and the optimization goal is to minimize the intraday transaction clearing fee of the ancillary service market. The objective function is: Where: C2 is the intraday market clearing cost; M is the intraday optimization period.

8. A method for joint clearing of ancillary service markets considering the participation of virtual power plants in peak load and frequency regulation as claimed in claim 6, characterized in that the step 2.2) establishes intraday rolling joint clearing constraints, which are divided into: peak load and frequency regulation demand constraints, peak load and frequency regulation winning capacity constraints, peak load market segmented quotation constraints, virtual power plant power upper and lower limit constraints and virtual power plant regulation rate constraints, a total of 5 parts, as follows: 8.1) Peak load and frequency regulation requirements: 8.2) Peak load and frequency regulation bidding capacity constraints: 8.3) Constraints on segmented bidding in the peak-shaving market: 8.4) Virtual power plant power upper and lower limit constraints: 8.5) Virtual power plant regulation rate constraints:

9. A joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation as claimed in claim 1, characterized in that: The step 3) is combined with the step 1) and the step 2) to implement a multi-time scale ancillary service market joint clearing strategy considering the participation of virtual power plants in peak load and frequency regulation. The specific steps of the implementation are as follows: 9.1) Confirm the operating parameters of the virtual power plant, including upper and lower limits, regulation rate, and continuous regulation time; 9.2) In the day-ahead market, the virtual power plant predicts and reports the benchmark output curve or power consumption curve for the next day; 9.3) The dispatch center releases the peak load and frequency regulation requirements for the next day; 9.4) Virtual power plants provide quotation for peak load and frequency regulation markets on a day-ahead basis; 9.5) According to equations (1)-(14), the objective function of the day-ahead joint clearing optimization problem is established; 9.6) According to equations (15)-(32), establish the constraints of the day-ahead joint clearing optimization problem; 9.7) Solve the problem using a commercial solver; 9.8) Output the winning virtual power plant, winning capacity and marginal unified clearing price, and the dispatch center publishes the day-ahead clearing results; 9.9) In the intraday market, the dispatch center releases the peak load and frequency regulation requirements for the next 4 hours; 9.10) Based on the day-ahead clearing results, the virtual power plant makes daily quotation for the peak load and frequency regulation markets; 9.11) According to formula (33), the objective function of the intraday rolling joint clearing optimization problem is established; 9.12) According to equations (34) to (43), establish the constraints of the intraday rolling joint clearing optimization problem; 9.13) Solve the problem using a commercial solver; 9.14) Output the winning virtual power plant, winning capacity and marginal unified clearing price, and the dispatch center publishes the intraday clearing results; 9.15) Determine whether the intraday rolling optimization clearing is completed. If not, return to step 9.9). If yes, end the intraday rolling optimization clearing.

10. A joint clearing method for ancillary service market considering the participation of virtual power plants in peak load and frequency regulation as claimed in claim 9, characterized in that: The commercial solver in step 9.7) and step 9.13) is specifically a gurobi solver.

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