Virtual power plant collaborative optimization system and method considering electricity market transaction

Abstract

The invention provides a virtual power plant collaborative optimization system considering power market transactions, and the system comprises an objective function building module which is used for building an objective function enabling the market operation cost to be minimum; the constraint establishment module is used for establishing a demand balance constraint of the target function according to the demand power of the energy market and the demand power of the standby market, and establishing a thermal power generating unit operation constraint of the target function according to the operation condition of the thermal power generating unit, establishing a virtual power plant operation constraint of the target function according to an operation condition of a virtual power plant, and establishing a power flow constraint of the target function according to a transmission power limit of a bus; and the collaborative optimization module is used for solving the objective function. According to the method, the day-ahead energy market cost of the thermal power generating unit, the starting cost of the thermal power generating unit, the standby market cost of the thermal power equipment and the standby market cost of the virtual power plant are considered at the same time, so that the target function is solved under the actual condition, and the market operation cost is minimized.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual power plants, and in particular to a virtual power plant collaborative optimization system and method taking power market transactions into consideration. Background Art

[0002] The potential of cluster regulation on the load side of the power grid is growing. As an efficient and adjustable resource, virtual power plants can be used in the power market and reserve capacity resources to deal with potential active power imbalances in system operation to ensure the safety and stability of the power grid. Existing research and practice have proved that the reasonable allocation of reserve capacity can promote the coordination of the power grid and improve the economy and reliability of the power grid. In mature power markets abroad, auxiliary service resources such as frequency regulation and reserve are optimized together with the energy market, bringing more considerable economic benefits.

[0003] In recent years, technology and grid business models have developed rapidly. With the continuous maturity of communication technology and control technology, new entities such as virtual power plants have gradually emerged to provide regulation potential for power system flexibility. System operation flexibility refers to the ability to respond to changes in system net load by dispatching controllable resources.

[0004] In addition, the nationwide power market reform is conducive to the allocation of power resources on a larger scale, but the contradiction between the economic efficiency and reliability coordination of system operation will become increasingly prominent at the regional power grid level. In this context, it is necessary to consider building a coordinated optimization market for energy and backup auxiliary services between regions to achieve the rational use of energy and backup supplementary service resources, and to improve the economy and reliability of the system through resource mutual assistance between regions.

[0005] However, there are relatively few practices of China's power grid load-side flexible resources participating in the market. There is an urgent need to guide and encourage active participation in power grid supervision through market-based means. Summary of the invention

[0006] The purpose of the present invention is to address the defect in the prior art of lacking the coordinated participation of thermal power units and virtual power plants in power resource allocation through market-oriented means, and to provide a virtual power plant collaborative optimization system and method taking into account power market transactions.

[0007] The present invention provides a virtual power plant collaborative optimization system considering power market transactions, comprising:

[0008] An objective function establishment module, used to establish an objective function that minimizes the market operation cost according to the energy market bid power of the thermal power unit during the transaction period, the reserve market bid power of the thermal power unit during the transaction period, and the reserve market bid power of the virtual power plant during the transaction period;

[0009] A constraint establishment module, used to establish a demand balance constraint of the objective function according to the demand power of the energy market and the demand power of the reserve market, establish a thermal power unit operation constraint of the objective function according to the operating conditions of the thermal power unit, establish a virtual power plant operation constraint of the objective function according to the operating conditions of the virtual power plant, and establish a power flow constraint of the objective function according to the transmission power limit of the bus;

[0010] The collaborative optimization module is used to solve the objective function according to the demand balance constraints, the operation constraints of the thermal power units, the operation constraints of the virtual power plant, and the power flow constraints, and obtain the optimal value of the energy market bid power of the thermal power units during the transaction period, the optimal value of the reserve market bid power of the thermal power units during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period.

[0011] Furthermore, in the objective function establishment module, the objective function is established as follows:

[0012]

[0013] Among them, C i,t represents the energy market price of thermal power unit i during trading period t, P i,t represents the energy market bidding power of thermal power unit i during trading period t, represents the startup cost of thermal power unit i during transaction period t, represents the reserve market quotation of thermal power unit i during trading period t, represents the reserve market bidding power of thermal power unit i during trading period t, N th represents the number of thermal power units i in the system, T represents the number during the transaction, and N VPP represents the number of virtual power plants, represents the reserve market price of virtual power plant j during trading period t, represents the reserve market bidding power of virtual power plant j during trading period t.

[0014] Furthermore, in the constraint establishment module, the specific method for establishing the demand balance constraint of the objective function according to the demand power of the energy market and the reserve market is as follows:

[0015] Establish the first balancing constraint for spare demand:

[0016]

[0017] Among them, D t represents the energy market demand power during trading period t, T j,t represents the power of the tie line between virtual power plant j and the power demander during the transaction period t;

[0018] Establish a second balancing constraint for spare demand:

[0019]

[0020] Among them, R t represents the reserve market demand power during the transaction period t of the reserve market.

[0021] Furthermore, in the constraint establishment module, the specific method of establishing the thermal power unit operation constraint of the objective function according to the operation conditions of the thermal power unit is as follows:

[0022] The operation constraints of thermal power units include: the sum of the thermal power unit energy market bid power and the thermal power unit reserve market bid power meets the upper limit constraint of power output, the climbing speed constraint when the thermal power unit power increases or decreases, and the thermal power unit reserve market bid power meets the upper limit constraint of its thermal power unit power;

[0023] Establish the sum of the bid power of the thermal power unit energy market and the bid power of the thermal power unit reserve market to meet the upper limit constraint of power output:

[0024]

[0025] Among them, α i,t represents the startup and shutdown status of thermal power unit i during transaction period t, α i,t =0 means thermal power unit i is shut down, α i,t =1 means thermal power unit i is turned on, represents the maximum output power of thermal power unit i during transaction period t;

[0026] Establish the climbing speed constraint when the power of the thermal power unit increases or decreases:

[0027]

[0028] in, Indicates the maximum uphill climbing speed of the output power of thermal power unit i, Indicates the maximum downhill climbing speed of the output power of thermal power unit i, represents the minimum output power of thermal power unit i during transaction period t;

[0029] For each trading period t, the reserve market bidding power of the thermal power unit meets the power cap constraint of its thermal power unit:

[0030]

[0031] in, Indicates the upper limit of the maximum power output of thermal power unit i.

[0032] Furthermore, in the constraint establishment module, the specific method for establishing the virtual power plant operation constraints of the objective function according to the operating conditions of the virtual power plant is as follows:

[0033] The operating constraints of virtual power plants include: virtual power plant output power constraints, power constraints of adjustable flexible resources within virtual power plants, maximum capacity constraints for energy storage, electric vehicles, and interruptible loads, power output ramping constraints for virtual power plants, and power output ramping constraints for energy storage, electric vehicles, and interruptible loads in virtual power plants;

[0034] Virtual power plants need to meet output power constraints:

[0035]

[0036] in, and They represent the minimum and maximum output power and the maximum output power of virtual power plant j during transaction period t, represents the reference output power of virtual power plant j during transaction period t, represents the energy market bidding power of virtual power plant j in time period t;

[0037] In a virtual power plant, internal adjustable flexible resources are needed to meet power requirements:

[0038]

[0039] in, represents the bid power of energy storage in the reserve market, represents the bid power of electric vehicles in the reserve market, It represents the bid power of interruptible load in the reserve market;

[0040] In addition, energy storage, electric vehicles and interruptible loads need to meet maximum capacity constraints:

[0041]

[0042] in, and denote the maximum bid capacity of energy storage, electric vehicles and interruptible loads respectively;

[0043] The virtual power plant needs to meet the power output ramp constraints:

[0044]

[0045] in, and They represent the maximum uphill ramp speed and the maximum downhill ramp speed of the power output of virtual power plant j respectively;

[0046] Energy storage, electric vehicles and interruptible loads in virtual power plants need to meet power output ramp constraints:

[0047]

[0048] in, and represents the maximum uphill climbing speed of the energy storage, electric vehicles and interruptible load power output in the virtual power plant j, and represents the maximum downhill ramp speed of the energy storage, electric vehicles and interruptible load power output in the virtual power plant j.

[0049] Furthermore, in the constraint establishment module, the specific method of establishing the power flow constraint of the objective function according to the transmission power limit of the bus is as follows:

[0050]

[0051] in, represents the power flow transfer limit of bus l, G l-i G represents the distribution factor of the generator output power transmission from the node where the thermal power unit i is located to the bus l. l-j T represents the distribution factor of the generator output power transmission from the node where the tie line between virtual power plant j and the power demander is located outside the virtual power plant to the bus l, j,t represents the power of the tie line between the virtual power plant j and the power demander during time period t, G l-k represents the distribution factor of the generator output power transmission from any node k to bus l, D k,t represents the load value of node k in time period t, represents the bidding power of node m of the virtual power plant in the energy market in period t, G l-m represents the distribution factor of the generator output power transmission from node m of the virtual power plant to bus l, N represents the total number of nodes where unit i is located, N T represents the total number of contact lines between virtual power plant j and power demand parties, K represents the total number of nodes k, and N wp Represents the total number of nodes m of the virtual power plant.

[0052] In the collaborative optimization module, the objective function is solved according to the demand balance constraint, the operation constraint of the thermal power unit, the operation constraint of the virtual power plant, and the power flow constraint to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period. The specific method is:

[0053] The objective function, the demand balance constraint, the thermal power unit operation constraint, the virtual power plant operation constraint, and the power flow constraint are input into the CPLEX solver, and the energy market bid power of the thermal power unit during the transaction period, the reserve market bid power of the thermal power unit during the transaction period, and the reserve market bid power of the virtual power plant during the transaction period are set as variables for solving, so as to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period.

[0054] A virtual power plant collaborative optimization method considering power market transactions, comprising:

[0055] An objective function is established to minimize the market operation cost according to the energy market bidding power of thermal power units during the transaction period, the reserve market bidding power of thermal power units during the transaction period, and the reserve market bidding power of virtual power plants during the transaction period;

[0056] Establishing the demand balance constraint of the objective function according to the demand power of the energy market and the demand power of the reserve market, establishing the thermal power unit operation constraint of the objective function according to the operation conditions of the thermal power unit, establishing the virtual power plant operation constraint of the objective function according to the operation conditions of the virtual power plant, and establishing the power flow constraint of the objective function according to the transmission power limit of the bus;

[0057] The objective function is solved according to the demand balance constraints, thermal power unit operation constraints, virtual power plant operation constraints, and power flow constraints to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period.

[0058] A computer-readable medium having a computer program / instruction stored thereon, wherein the computer program / instruction executes the above-mentioned virtual power plant collaborative optimization method considering electricity market transactions when running.

[0059] A computer program product includes a computer program / instruction, which, when executed by a processor, implements the above-mentioned virtual power plant collaborative optimization method considering electricity market transactions.

[0060] The beneficial effects of the present invention are:

[0061] 1. The present invention simultaneously considers the day-ahead energy market cost of thermal power units, the startup cost of thermal power units, the standby market cost of thermal power equipment and the standby market cost of virtual power plants, and accordingly establishes an objective function that minimizes the market cost. Then, according to actual conditions, a virtual power plant, thermal power units, market demand balance and power flow constraints are established, so that the objective function is solved under actual conditions. Finally, under the condition of considering market transaction factors, the market operation cost is minimized under the synergistic effect of thermal power units and virtual power plants.

[0062] 2. When establishing the operating constraints of the virtual power plant, the operating constraints of three internal resources, namely energy storage, electric vehicles and interruptible loads, are taken into account, and the allocation of available power resources in the region is adjusted, which has a significant effect on reducing market operating costs.

[0063] 3. Power flow constraints are established so that the power load of the bus can vary within a controllable range, neither too large nor too small. The virtual power plant participates in market transactions within the constraints, which improves the quality of electricity and ensures stable power supply in the region. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 This is a system block diagram of the present invention.

[0065] Figure 2 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0066] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0067] Example 1

[0068] refer to Figure 1 , a virtual power plant collaborative optimization system considering power market transactions, including:

[0069] An objective function establishment module, used to establish an objective function that minimizes the market operation cost according to the energy market bid power of the thermal power unit during the transaction period, the reserve market bid power of the thermal power unit during the transaction period, and the reserve market bid power of the virtual power plant during the transaction period;

[0070] A constraint establishment module, used to establish a demand balance constraint of the objective function according to the demand power of the energy market and the demand power of the reserve market, establish a thermal power unit operation constraint of the objective function according to the operating conditions of the thermal power unit, establish a virtual power plant operation constraint of the objective function according to the operating conditions of the virtual power plant, and establish a power flow constraint of the objective function according to the transmission power limit of the bus;

[0071] The collaborative optimization module is used to solve the objective function according to demand balance constraints, thermal power unit operation constraints, virtual power plant operation constraints, and power flow constraints, and obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the standby market bid power of the thermal power unit during the transaction period, and the optimal value of the standby market bid power of the virtual power plant during the transaction period. The virtual power plant is configured according to these three optimal values, which can reduce market operating costs.

[0072] (1) Since the market cost mainly comes from four aspects: the day-ahead energy market cost of thermal power units, the startup cost of thermal power units, the reserve market cost of thermal power equipment and the reserve market cost of virtual power plants, the objective function is established as follows:

[0073]

[0074] Among them, C i,t represents the energy market price of thermal power unit i during trading period t, P i,t represents the energy market bidding power of thermal power unit i during trading period t, represents the startup cost of thermal power unit i during transaction period t, represents the reserve market quotation of thermal power unit i during trading period t, represents the reserve market bidding power of thermal power unit i during trading period t, N th represents the number of thermal power units i in the system, T represents the number during the transaction, and N VPP represents the number of virtual power plants, represents the reserve market price of virtual power plant j during trading period t, represents the reserve market bidding power of virtual power plant j during trading period t.

[0075] (2) In the demand balance constraint establishment module, the specific method for establishing the demand balance constraint of the objective function according to the demand power of the energy market and the reserve market is as follows:

[0076] Since in the energy market, the total bid amount of thermal power units and virtual power plants needs to meet the day-ahead market load demand issued by the dispatching control center, the first balance constraint of the reserve demand is established:

[0077]

[0078] Among them, D t represents the energy market demand power during trading period t, T j,t represents the power of the tie line between virtual power plant j and the power demander during the transaction period t;

[0079] Since the total bid power of thermal power units and virtual power plants in the reserve market needs to be greater than or equal to the reserve market demand power, the second balance constraint of reserve demand is established:

[0080]

[0081] Among them, R t represents the reserve market demand power during the transaction period t of the reserve market.

[0082] (3) In the constraint establishment module, the specific method for establishing the thermal power unit operation constraint of the objective function according to the operation conditions of the thermal power unit is as follows:

[0083] For the thermal power units participating in the optimization, the sum of their energy market bid power and reserve market bid power meets the upper limit constraint of power output:

[0084]

[0085] Among them, α i,t represents the startup and shutdown status of thermal power unit i during transaction period t, α i,t =0 means thermal power unit i is shut down, α i,t =1 means thermal power unit i is turned on, represents the maximum output power of thermal power unit i during transaction period t;

[0086] Establish the climbing speed constraint when the power of the thermal power unit increases or decreases:

[0087]

[0088] in, Indicates the maximum uphill climbing speed of the output power of thermal power unit i, Indicates the maximum downhill climbing speed of the output power of thermal power unit i, represents the minimum output power of thermal power unit i during transaction period t;

[0089] For each trading period t, the reserve market bidding power of thermal power units should meet its upper limit constraint:

[0090]

[0091] in, Indicates the upper limit of the maximum power output of thermal power unit i.

[0092] (4) In the constraint establishment module, the specific method for establishing the virtual power plant operation constraints of the objective function based on the operating conditions of the virtual power plant is as follows:

[0093] The virtual power plant operation constraints for collaborative optimization of virtual power plants considering electricity market transactions include output constraints of virtual power plants, operation constraints of internal adjustable flexible resources, operation constraints of energy storage, electric vehicles and interruptible loads, ramping constraints of virtual power plants, and ramping constraints of energy storage, electric vehicles and interruptible loads;

[0094] In the reserve market, virtual power plants and thermal power units jointly participate in market bidding. The virtual power plant constraints that need to be met mainly come from the physical constraints of the external output of the virtual power plant and the technical output constraints of various resources within the virtual power plant; the virtual power plant needs to meet the output power constraints:

[0095]

[0096] in, and They represent the minimum and maximum output power and the maximum output power of virtual power plant j during transaction period t, represents the reference output power of virtual power plant j during transaction period t, represents the energy market bidding power of virtual power plant j in time period t;

[0097] In a virtual power plant, internal adjustable flexible resources are needed to meet power requirements:

[0098]

[0099] in, represents the bid power of energy storage in the reserve market, represents the bid power of electric vehicles in the reserve market, Indicates the bid power of interruptible load in the reserve market. Interruptible load refers to the load part that can be interrupted by power users during peak hours or emergency situations of the power grid through signing economic contracts (agreements). This measure is intended to ensure the stable operation of the power grid and help balance the supply and demand of electricity; a general term for a type of load;

[0100] In addition, energy storage, electric vehicles and interruptible loads need to meet maximum capacity constraints:

[0101]

[0102]

[0103] in, and denote the maximum bid capacity of energy storage, electric vehicles and interruptible loads respectively;

[0104] The virtual power plant needs to meet the power output ramp constraints:

[0105]

[0106] in, and They represent the maximum uphill ramp speed and the maximum downhill ramp speed of the power output of virtual power plant j respectively;

[0107] Energy storage, electric vehicles and interruptible loads in virtual power plants need to meet power output ramp constraints:

[0108]

[0109] in, and represents the maximum uphill climbing speed of the energy storage, electric vehicles and interruptible load power output in the virtual power plant j, and represents the maximum downhill ramp speed of the energy storage, electric vehicles and interruptible load power output in the virtual power plant j.

[0110] (5) In the constraint establishment module, the specific method for establishing the power flow constraint of the objective function according to the transmission power limit of the bus is as follows:

[0111]

[0112] in, represents the power flow transfer limit of bus l, G l-i G represents the distribution factor of the generator output power transmission from the node where the thermal power unit i is located to the bus l. l-j T represents the distribution factor of the generator output power transmission from the node where the tie line between virtual power plant j and the power demander is located outside the virtual power plant to the bus l, j,t represents the power of the tie line between the virtual power plant j and the power demander during time period t, G l-k represents the distribution factor of the generator output power transmission from any node k to bus l, D k,t represents the load value of node k in time period t, represents the bidding power of node m of the virtual power plant in the energy market in period t, G l-m represents the distribution factor of the generator output power transmission from node m of the virtual power plant to bus l, N represents the total number of nodes where unit i is located, N T represents the total number of contact lines between virtual power plant j and power demand parties, K represents the total number of nodes k, and N wp Represents the total number of nodes m of the virtual power plant.

[0113] (6) In the collaborative optimization module, the objective function is solved according to the demand balance constraint, the operation constraint of the thermal power unit, the operation constraint of the virtual power plant, and the power flow constraint to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period. The specific method is:

[0114] The objective function, the demand balance constraint, the thermal power unit operation constraint, the virtual power plant operation constraint, and the power flow constraint are input into the CPLEX solver, and the energy market bid power of the thermal power unit during the transaction period, the reserve market bid power of the thermal power unit during the transaction period, and the reserve market bid power of the virtual power plant during the transaction period are set as variables for solving, so as to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period.

[0115] Experimental analysis

[0116] A multi-region system consisting of three IEEE-30 bus systems and six virtual power plants is designed as a case to verify the correctness and applicability of the collaborative optimization model with the participation of virtual power plants. The thermal power units and virtual power plants on the load represent the joint participation in the reserve market. In the day-ahead market, the energy and reserve markets are jointly optimized and cleared, and the market clearing period is 15 minutes.

[0117] There are three types of load-side resources in the virtual power plant: energy storage, electric vehicles and interruptible loads. Six virtual power plants are set up in the multi-regional system, and each IEEE-30 bus system has two virtual power plants. The thermal power units and virtual power plants on the load represent joint participation in the reserve ancillary service market.

[0118] The capacity demand of the reserve ancillary service market is usually determined by the peak load, which is obtained by multiplying the peak load by a proportional factor. The participation of the virtual power plant and its internal resources in the reserve market is based on the daily load reference output curve, and its capacity after participating in the reserve ancillary service market cannot exceed the operating limit. The main operating parameters of the virtual power plant and load-side resources refer to the actual virtual power plant station, as shown in Table 1.

[0119] Table 1 Main operating parameters of virtual power plants in multi-region systems

[0120]

[0121] Energy storage, electric vehicles and interruptible loads in the virtual power plant have separate ramp rate constraints in each trading period, and the maximum ramp rate of each load resource participating in the reserve market cannot exceed their respective physical limits. Table 2 gives the main ramp rate parameters of the load-side resources in the virtual power plant.

[0122] Table 2 Main parameters of resources in virtual power plant

[0123]

[0124] The bidding parameters of each virtual power plant in the reserve market are shown in Table 3. In this case, the six virtual power plants use the same bidding strategy in each trading period.

[0125] Table 3 Quotation parameters of virtual power plants in multi-region systems

[0126]

[0127] Substituting the above parameters into the objective function and constraints of this embodiment, the data in Table 4 are obtained, which gives the market cost of the multi-regional system in different scenarios with and without virtual power plants participating in the reserve ancillary service market. It can be seen that load-side adjustable resources such as virtual power plants are of great significance for reducing the operating cost of the reserve market and replacing thermal power resources to provide cleaner electricity. The participation of virtual power plants in the reserve market effectively reduces the market operating cost and improves the flexibility of the power system.

[0128] Table 4. Market operation costs for different scenarios in a multi-region system

[0129]

[0130]

[0131] Through analysis, it can be seen that the participation of virtual power plants in the reserve market effectively reduces market operating costs and improves the flexibility of the power system.

[0132] Example 2

[0133] refer to Figure 2 , a virtual power plant collaborative optimization method considering power market transactions, including:

[0134] An objective function is established to minimize the market operation cost according to the energy market bidding power of thermal power units during the transaction period, the reserve market bidding power of thermal power units during the transaction period, and the reserve market bidding power of virtual power plants during the transaction period;

[0135] Establishing the demand balance constraint of the objective function according to the demand power of the energy market and the demand power of the reserve market, establishing the thermal power unit operation constraint of the objective function according to the operation conditions of the thermal power unit, establishing the virtual power plant operation constraint of the objective function according to the operation conditions of the virtual power plant, and establishing the power flow constraint of the objective function according to the transmission power limit of the bus;

[0136] The objective function is solved according to the demand balance constraints, thermal power unit operation constraints, virtual power plant operation constraints, and power flow constraints to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the standby market bid power of the thermal power unit during the transaction period, and the optimal value of the standby market bid power of the virtual power plant during the transaction period. The virtual power plant is configured according to these three optimal values, which can reduce market operating costs.

[0137] (1) Since the market cost mainly comes from four aspects: the day-ahead energy market cost of thermal power units, the startup cost of thermal power units, the reserve market cost of thermal power equipment and the reserve market cost of virtual power plants, the objective function is established as follows:

[0138]

[0139] Among them, C i,t represents the energy market price of thermal power unit i during trading period t, P i,t represents the energy market bidding power of thermal power unit i during trading period t, represents the startup cost of thermal power unit i during transaction period t, represents the reserve market quotation of thermal power unit i during trading period t, represents the reserve market bidding power of thermal power unit i during trading period t, N th represents the number of thermal power units i in the system, T represents the number during the transaction, and N VPP represents the number of virtual power plants, represents the reserve market price of virtual power plant j during trading period t, represents the reserve market bidding power of virtual power plant j during trading period t.

[0140] (2) The specific method of establishing the demand balance constraint of the objective function according to the demand power of the energy market and the reserve market is as follows:

[0141] Since in the energy market, the total bid amount of thermal power units and virtual power plants needs to meet the day-ahead market load demand issued by the dispatching control center, the first balance constraint of the reserve demand is established:

[0142]

[0143] Among them, D trepresents the energy market demand power during trading period t, T j,t represents the power of the tie line between virtual power plant j and the power demander during the transaction period t;

[0144] Since the total bid power of thermal power units and virtual power plants in the reserve market needs to be greater than or equal to the reserve market demand power, the second balance constraint of reserve demand is established:

[0145]

[0146] Among them, R t represents the reserve market demand power during the transaction period t of the reserve market.

[0147] (3) The specific method of establishing the thermal power unit operation constraint of the objective function according to the operation conditions of the thermal power unit is as follows:

[0148] For the thermal power units participating in the optimization, the sum of their energy market bid power and reserve market bid power meets the upper limit constraint of power output:

[0149]

[0150] Among them, α i,t represents the startup and shutdown status of thermal power unit i during transaction period t, α i,t =0 means thermal power unit i is shut down, α i,t =1 means thermal power unit i is turned on, represents the maximum output power of thermal power unit i during transaction period t;

[0151] Establish the climbing speed constraint when the power of the thermal power unit increases or decreases:

[0152]

[0153] in, Indicates the maximum uphill climbing speed of the output power of thermal power unit i, Indicates the maximum downhill climbing speed of the output power of thermal power unit i, represents the minimum output power of thermal power unit i during transaction period t;

[0154] For each trading period t, the reserve market bidding power of thermal power units should meet its upper limit constraint:

[0155]

[0156] in, Indicates the upper limit of the maximum power output of thermal power unit i.

[0157] (4) The specific method of establishing the virtual power plant operation constraints of the objective function is as follows:

[0158] The virtual power plant operation constraints for collaborative optimization of virtual power plants considering electricity market transactions include output constraints of virtual power plants, operation constraints of internal adjustable flexible resources, operation constraints of energy storage, electric vehicles and interruptible loads, ramping constraints of virtual power plants, and ramping constraints of energy storage, electric vehicles and interruptible loads;

[0159] In the reserve market, virtual power plants and thermal power units jointly participate in market bidding. The virtual power plant constraints that need to be met mainly come from the physical constraints of the external output of the virtual power plant and the technical output constraints of various resources within the virtual power plant; the virtual power plant needs to meet the output power constraints:

[0160]

[0161] in, and They represent the minimum and maximum output power and the maximum output power of virtual power plant j during transaction period t, represents the reference output power of virtual power plant j during transaction period t, represents the energy market bidding power of virtual power plant j in time period t;

[0162] In a virtual power plant, internal adjustable flexible resources are needed to meet power requirements:

[0163]

[0164] in, represents the bid power of energy storage in the reserve market, represents the bid power of electric vehicles in the reserve market, Indicates the bid power of interruptible load in the reserve market. Interruptible load refers to the load part that can be interrupted by power users during peak hours or emergency situations of the power grid through signing economic contracts (agreements). This measure is intended to ensure the stable operation of the power grid and help balance the supply and demand of electricity; a general term for a type of load;

[0165] In addition, energy storage, electric vehicles and interruptible loads need to meet maximum capacity constraints:

[0166]

[0167] in, and denote the maximum bid capacity of energy storage, electric vehicles and interruptible loads respectively;

[0168] The virtual power plant needs to meet the power output ramp constraints:

[0169]

[0170] in, and They represent the maximum uphill ramp speed and the maximum downhill ramp speed of the power output of virtual power plant j respectively;

[0171] Energy storage, electric vehicles and interruptible loads in virtual power plants need to meet power output ramp constraints:

[0172]

[0173] in, and represents the maximum uphill climbing speed of the energy storage, electric vehicles and interruptible load power output in the virtual power plant j, and represents the maximum downhill ramp speed of the energy storage, electric vehicles and interruptible load power output in the virtual power plant j.

[0174] (5) The specific method of establishing the power flow constraint of the objective function according to the transmission power limit of the bus is as follows:

[0175]

[0176] in, represents the power flow transfer limit of bus l, G l-i G represents the distribution factor of the generator output power transmission from the node where the thermal power unit i is located to the bus l. l-j T represents the distribution factor of the generator output power transmission from the node where the tie line between virtual power plant j and the power demander is located outside the virtual power plant to the bus l, j,t represents the power of the tie line between the virtual power plant j and the power demander during time period t, G l-k represents the distribution factor of the generator output power transmission from any node k to bus I, D k,t represents the load value of node k in time period t, represents the bidding power of node m of the virtual power plant in the energy market in period t, G l-m represents the distribution factor of the generator output power transmission from node m of the virtual power plant to bus l, N represents the total number of nodes where unit i is located, N T represents the total number of contact lines between virtual power plant j and power demand parties, K represents the total number of nodes k, and N wp Represents the total number of nodes m of the virtual power plant.

[0177] (6) The specific method for solving the objective function according to the demand balance constraint, the thermal power unit operation constraint, the virtual power plant operation constraint, and the power flow constraint to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period is:

[0178] The objective function, the demand balance constraint, the thermal power unit operation constraint, the virtual power plant operation constraint, and the power flow constraint are input into the CPLEX solver, and the energy market bid power of the thermal power unit during the transaction period, the reserve market bid power of the thermal power unit during the transaction period, and the reserve market bid power of the virtual power plant during the transaction period are set as variables for solving, so as to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period.

[0179] Experimental analysis

[0180] A multi-region system consisting of three IEEE-30 bus systems and six virtual power plants is designed as a case to verify the correctness and applicability of the collaborative optimization model with the participation of virtual power plants. The thermal power units and virtual power plants on the load represent the joint participation in the reserve market. In the day-ahead market, the energy and reserve markets are jointly optimized and cleared, and the market clearing period is 15 minutes.

[0181] There are three types of load-side resources in the virtual power plant: energy storage, electric vehicles and interruptible loads. Six virtual power plants are set up in the multi-regional system, and each IEEE-30 bus system has two virtual power plants. The thermal power units and virtual power plants on the load represent joint participation in the reserve ancillary service market.

[0182] The capacity demand of the reserve ancillary service market is usually determined by the peak load, which is obtained by multiplying the peak load by a proportional factor. The participation of the virtual power plant and its internal resources in the reserve market is based on the daily load reference output curve, and its capacity after participating in the reserve ancillary service market cannot exceed the operating limit. The main operating parameters of the virtual power plant and load-side resources refer to the actual virtual power plant station, as shown in Table 1.

[0183] Table 1 Main operating parameters of virtual power plants in multi-region systems

[0184]

[0185] Energy storage, electric vehicles and interruptible loads in the virtual power plant have separate ramp rate constraints in each trading period, and the maximum ramp rate of each load resource participating in the reserve market cannot exceed their respective physical limits. Table 2 gives the main ramp rate parameters of the load-side resources in the virtual power plant.

[0186] Table 2 Main parameters of resources in virtual power plant

[0187]

[0188] The bidding parameters of each virtual power plant in the reserve market are shown in Table 3. In this case, the six virtual power plants use the same bidding strategy in each trading period.

[0189] Table 3 Quotation parameters of virtual power plants in multi-region systems

[0190]

[0191] Substituting the above parameters into the objective function and constraints of this embodiment, the data in Table 4 are obtained, which gives the market cost of the multi-regional system in different scenarios with and without virtual power plants participating in the reserve ancillary service market. It can be seen that load-side adjustable resources such as virtual power plants are of great significance for reducing the operating cost of the reserve market and replacing thermal power resources to provide cleaner electricity. The participation of virtual power plants in the reserve market effectively reduces the market operating cost and improves the flexibility of the power system.

[0192] Table 4. Market operation costs for different scenarios in a multi-region system

[0193] plan Market operation cost (ten thousand yuan) No virtual power plant 637.56 6 virtual power plants 634.88

[0194] Through analysis, it can be seen that the participation of virtual power plants in the reserve market effectively reduces market operating costs and improves the flexibility of the power system.

[0195] Example 3

[0196] A computer-readable medium having a computer program stored thereon, wherein the computer program executes the virtual power plant collaborative optimization method considering electricity market transactions in Example 2 when running.

[0197] Example 4

[0198] A computer program product includes a computer program / instruction, which, when executed by a processor, implements the virtual power plant collaborative optimization method considering electricity market transactions in Example 2.

[0199] The contents not described in detail in this specification belong to the prior art known to those skilled in the art. It should be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0200] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0201] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0202] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0203] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit its protection scope. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that after reading the present invention, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the pending claims of the invention.

Claims

1. A virtual power plant collaborative optimization system considering power market transactions, characterized in that: include: An objective function establishment module, used to establish an objective function that minimizes the market operation cost according to the energy market bid power of the thermal power unit during the transaction period, the reserve market bid power of the thermal power unit during the transaction period, and the reserve market bid power of the virtual power plant during the transaction period; A constraint establishment module, used to establish a demand balance constraint of the objective function according to the demand power of the energy market and the demand power of the reserve market, establish a thermal power unit operation constraint of the objective function according to the operating conditions of the thermal power unit, establish a virtual power plant operation constraint of the objective function according to the operating conditions of the virtual power plant, and establish a power flow constraint of the objective function according to the transmission power limit of the bus; The collaborative optimization module is used to solve the objective function according to the demand balance constraints, the operation constraints of the thermal power units, the operation constraints of the virtual power plant, and the power flow constraints, and obtain the optimal value of the energy market bid power of the thermal power units during the transaction period, the optimal value of the reserve market bid power of the thermal power units during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period.

2. The virtual power plant collaborative optimization system considering power market transactions according to claim 1 is characterized by: In the objective function establishment module, the objective function is established as follows: Among them, C i,t represents the energy market price of thermal power unit i during trading period t, P i,t represents the energy market bidding power of thermal power unit i during trading period t, represents the startup cost of thermal power unit i during transaction period t, represents the reserve market quotation of thermal power unit i during trading period t, represents the reserve market bidding power of thermal power unit i during trading period t, N th represents the number of thermal power units i in the system, T represents the number during the transaction, and N VPP represents the number of virtual power plants, represents the reserve market price of virtual power plant j during trading period t, represents the reserve market bidding power of virtual power plant j during trading period t.

3. The virtual power plant collaborative optimization system considering power market transactions according to claim 2 is characterized by: In the constraint establishment module, the specific method of establishing the demand balance constraint of the objective function according to the demand power of the energy market and the reserve market is as follows: Establish the first balancing constraint for spare demand: Among them, D t represents the energy market demand power during trading period t, T j,t represents the power of the tie line between virtual power plant j and the power demander during the transaction period t; Establish a second balancing constraint for spare demand: Among them, R t represents the reserve market demand power during the transaction period t of the reserve market.

4. The virtual power plant collaborative optimization system considering power market transactions according to claim 3 is characterized by: In the constraint establishment module, the specific method for establishing the thermal power unit operation constraint of the objective function according to the operation conditions of the thermal power unit is as follows: The operating constraints of thermal power units include: The sum of the power bid in the energy market of the thermal power unit and the power bid in the reserve market of the thermal power unit meets the upper limit constraint of the power output, the ramp speed constraint when the power of the thermal power unit increases or decreases, and the power bid in the reserve market of the thermal power unit meets the upper limit constraint of the power of the thermal power unit; Establish the sum of the bid power of the thermal power unit energy market and the bid power of the thermal power unit reserve market to meet the upper limit constraint of power output: Among them, α i,t represents the startup and shutdown status of thermal power unit i during transaction period t, α i,t =0 means thermal power unit i is shut down, α i,t =1 means thermal power unit i is turned on, represents the maximum output power of thermal power unit i during transaction period t; Establish the climbing speed constraint when the power of the thermal power unit increases or decreases: in, Indicates the maximum uphill climbing speed of the output power of thermal power unit i, Indicates the maximum downhill climbing speed of the output power of thermal power unit i, represents the minimum output power of thermal power unit i during transaction period t; For each trading period t, the reserve market bidding power of the thermal power unit meets the power cap constraint of its thermal power unit: in, Indicates the upper limit of the maximum power output of thermal power unit i.

5. The virtual power plant collaborative optimization system considering power market transactions according to claim 4 is characterized by: In the constraint establishment module, the specific method of establishing the virtual power plant operation constraints of the objective function based on the operating conditions of the virtual power plant is as follows: The operating constraints of virtual power plants include: virtual power plant output power constraints, power constraints of adjustable flexible resources within virtual power plants, maximum capacity constraints for energy storage, electric vehicles, and interruptible loads, power output ramping constraints for virtual power plants, and power output ramping constraints for energy storage, electric vehicles, and interruptible loads in virtual power plants; Establish virtual power plant output power constraints: in, and They represent the minimum and maximum output power and the maximum output power of virtual power plant j during transaction period t, represents the reference output power of virtual power plant j during transaction period t, represents the energy market bidding power of virtual power plant j in time period t; Establishing power constraints for adjustable flexible resources within a virtual power plant: in, represents the bid power of energy storage in the reserve market, represents the bid power of electric vehicles in the reserve market, It represents the bid power of interruptible load in the reserve market; Establish maximum capacity constraints for energy storage, electric vehicles, and interruptible loads: in, and denote the maximum bid capacity of energy storage, electric vehicles and interruptible loads respectively; Establish the power output ramp constraint of the virtual power plant: in, and They represent the maximum uphill ramp speed and the maximum downhill ramp speed of the power output of virtual power plant j respectively; Establishing power output ramping constraints for energy storage, electric vehicles, and interruptible loads in a virtual power plant: in, and represents the maximum uphill climbing speed of the energy storage, electric vehicles and interruptible load power output in the virtual power plant j, and represents the maximum downhill ramp speed of the energy storage, electric vehicles and interruptible load power output in the virtual power plant j.

6. The virtual power plant collaborative optimization system considering power market transactions according to claim 5 is characterized by: In the constraint establishment module, the specific method of establishing the power flow constraint of the objective function according to the transmission power limit of the bus is as follows: in, represents the power flow transfer limit of bus l, G l-i G represents the distribution factor of the generator output power transmission from the node where the thermal power unit i is located to the bus l. l-j T represents the distribution factor of the generator output power transmission from the node where the tie line between virtual power plant j and the power demander is located outside the virtual power plant to the bus l, j,t represents the power of the tie line between the virtual power plant j and the power demander during time period t, G l-k represents the distribution factor of the generator output power transmission from any node k to bus l, D k,t represents the load value of node k in time period t, represents the bidding power of node m of the virtual power plant in the energy market in period t, G l-m represents the distribution factor of the generator output power transmission from node m of the virtual power plant to bus l, N represents the total number of nodes where unit i is located, N T represents the total number of contact lines between virtual power plant j and power demand parties, K represents the total number of nodes k, and N wp Represents the total number of nodes m of the virtual power plant.

7. The virtual power plant collaborative optimization system considering power market transactions according to claim 6 is characterized by: In the collaborative optimization module, the objective function is solved according to the demand balance constraint, the operation constraint of the thermal power unit, the operation constraint of the virtual power plant, and the power flow constraint to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period. The specific method is: The objective function, the demand balance constraint, the thermal power unit operation constraint, the virtual power plant operation constraint, and the power flow constraint are input into the CPLEX solver, and the energy market bid power of the thermal power unit during the transaction period, the reserve market bid power of the thermal power unit during the transaction period, and the reserve market bid power of the virtual power plant during the transaction period are set as variables for solving, so as to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period.

8. A virtual power plant collaborative optimization method considering power market transactions, characterized in that: include: An objective function is established to minimize the market operation cost according to the energy market bidding power of thermal power units during the transaction period, the reserve market bidding power of thermal power units during the transaction period, and the reserve market bidding power of virtual power plants during the transaction period; Establishing the demand balance constraint of the objective function according to the demand power of the energy market and the demand power of the reserve market, establishing the thermal power unit operation constraint of the objective function according to the operation conditions of the thermal power unit, establishing the virtual power plant operation constraint of the objective function according to the operation conditions of the virtual power plant, and establishing the power flow constraint of the objective function according to the transmission power limit of the bus; The objective function is solved according to the demand balance constraints, thermal power unit operation constraints, virtual power plant operation constraints, and power flow constraints to obtain the optimal value of the energy market bid power of the thermal power unit during the transaction period, the optimal value of the reserve market bid power of the thermal power unit during the transaction period, and the optimal value of the reserve market bid power of the virtual power plant during the transaction period.

9. A computer-readable medium having a computer program / instruction stored thereon, wherein the computer program / instruction, when run, executes the virtual power plant collaborative optimization method considering electricity market transactions as described in claim 7.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method for collaborative optimization of virtual power plants taking into account electricity market transactions as described in claim 7 is implemented.

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