Method and system for simulating participation of new energy unit in electric power spot market

Abstract

The invention relates to a method and system for simulating participation of a new energy unit in an electric power spot market. The method comprises the following steps: firstly, constructing a power grid model of the new energy unit participating in the electric power spot market; analyzing and generating boundary data of the new energy unit in combination with the power grid model and external data; according to the actual output condition of the new energy unit, a market transaction participation mode of the new energy unit and unit quotation data are obtained; constructing a new energy unit participation market model, and configuring a corresponding market transaction rule; finally, SCUC, SCED and LMP algorithms are called, the new energy unit participation market model is subjected to simulation operation, a simulation operation result is obtained, the market operation result is analyzed and evaluated by introducing the evaluation index, and the method can comprehensively measure the influence of the new energy participation market on electricity price fluctuation of the electricity market, new energy consumption, electricity supply and the like.

Description

Technical Field

[0001] The invention relates to a method and a system for simulating new energy units to participate in a power spot market, belonging to the field of new energy participation in market operation. Background Art

[0002] The acceleration of the construction of new power systems and the large-scale development and utilization of new energy have brought a series of new challenges to the consumption of new energy and the development of the power market. The scarcity of flexible resources caused by the high proportion of new energy grid connection will become the main bottleneck restricting the improvement of new energy grid connection and consumption. At present, new energy has not yet fully participated in the power spot market, and the per-kilowatt-hour income is mainly based on the guaranteed purchase price. However, due to the randomness and uncertainty of the output of new energy, the operation of the power spot market has great risks, resulting in complex and changeable grid arrangement and power flow distribution, which will have a great impact on the operation of the power spot market and the power system, and also bring new risks and challenges to the regulation and management work under the power market environment; and due to the output characteristics of new energy, the trading methods and trading behaviors after participating in the power market are quite different from those of traditional thermal power, and the existing power market trading mechanism cannot meet the requirements of guaranteed consumption of new energy. On the premise of meeting the requirements of safe operation of the new power system, how to promote the participation of new energy in the market with reasonable trading methods and meet the requirements of new energy access and consumption are issues that need to be considered in the development of the power spot market under the current construction of the new power system environment. Summary of the invention

[0003] In order to solve the problems existing in the prior art, the present invention provides a simulation evaluation method for comprehensively measuring the various aspects of the impact of new energy participating in the electricity spot market.

[0004] In order to achieve the above object, the technical solution proposed by the present invention is: a method for simulating new energy units to participate in the electricity spot market, comprising the following steps:

[0005] Construct a grid model for new energy units participating in the electricity spot market;

[0006] Combine the power grid model and external data of the new energy unit to analyze and generate the boundary data of the new energy unit;

[0007] According to the actual output of new energy units, obtain the market transaction mode and unit quotation data of new energy units;

[0008] Construct a new energy unit market model that includes the power grid model, boundary data, unit quotation data and transaction mode of new energy units, and configure corresponding market transaction rules for the new energy unit market model;

[0009] Call SCUC, SCED and LMP algorithms to simulate the market model of new energy units and obtain simulation results;

[0010] Evaluation indicators are used to analyze and evaluate market operation results.

[0011] The grid model of the new energy unit is:

[0012]

[0013] Where P cmin , P fmin , P cmax , P fmax Respectively represent the minimum and maximum output of the unit, I c Indicates the state variable of the unit that cannot be shut down within the day, represents the state variable of the unit that can be shut down during the day for period t, They are the down-slope and up-slope rates of the unit respectively.

[0014] The boundary data is the boundary data required for new energy units to participate in the daily clearing of the electricity spot market, including forecast data, plan data, constraint data and market declaration information;

[0015] The forecast data includes system load curve and new energy unit output curve;

[0016] The planning data include the tie line operation plan, the fixed output plan curve of non-market units and the line maintenance plan;

[0017] The constraint data include system operation reserve, market unit initial status, market unit status constraint, market unit output constraint and section transmission limit;

[0018] The market declaration information is the output that the units participating in the spot market need to declare before the market is cleared and the price corresponding to the output in each stage.

[0019] The transaction mode adopts a segmented declaration mode and a time-sharing declaration mode.

[0020] The market trading rules include quotation method, clearing basis, unit output reporting stage, upper / lower limit of reported price and settlement price method.

[0021] The optimization goal of the SCUC algorithm is:

[0022]

[0023] In the formula, T represents the total number of time periods, N represents the number of units, P represents the unit output, CP represents the unit operating cost, M represents the network power flow constraint relaxation penalty factor, NL and NS represent the number of lines and sections respectively, and SL represents the power flow relaxation variable. Among them, the subscripts i, t, l, and s represent the i-th unit, time period, line, and section; the superscripts + and - represent the forward and reverse directions respectively.

[0024] The optimization goal of the SCED algorithm is:

[0025]

[0026] The evaluation indicators include market fairness, market security, market economy and market environmental protection.

[0027] A system for simulating new energy units participating in the electricity spot market comprises a memory, a processor and a computer program. The computer program is stored in the memory and is configured to be executed by the processor to implement the above-mentioned method for simulating new energy units participating in the electricity spot market.

[0028] A computer-readable storage medium stores a computer program, which, when executed, controls a device where the computer-readable storage medium is located to execute the above-mentioned method for simulating new energy sources to participate in a spot electricity market.

[0029] The beneficial effects of the present invention are:

[0030] The present invention creates a new energy unit power grid model, then imports and analyzes external data, generates market boundary data, configures corresponding market trading rules, calls SCUC, SCED and LMP algorithms, simulates the participation of new energy in the electricity spot market, and finally establishes a market evaluation system based on the simulation results to comprehensively measure the impact of new energy participation in the market on electricity price fluctuations, new energy consumption, power supply, etc. in the power market, thereby providing scientific and economic development suggestions for the construction of new power systems under the market environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart of the present invention;

[0032] Figure 2 It is the declaration curve chart for segmented declaration;

[0033] Figure 3 It is the declaration curve chart of time-sharing declaration;

[0034] Figure 4 Schematic diagram of evaluation indicators. DETAILED DESCRIPTION

[0035] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] Embodiment 1

[0037] As shown in the figure, the method of simulating new energy units participating in the electricity spot market in this embodiment is as follows: Figure 1 As shown, the following steps are included:

[0038] Step 1: Construct a grid model of the new energy units (wind power, photovoltaic units) participating in the electricity spot market and other grid models of units participating in the market;

[0039] The power grid model converts the physical models of wind power, photovoltaic and other power system equipment into market models for clearing the electricity spot market based on the real operation data of the power grid. This embodiment constructs a topological model of new energy and other market participating units in the power grid model, and stores the physical parameters of the unit operation, including node information, rated capacity, minimum technical output, minimum operation / shutdown duration, etc. It supports the visualization of new energy unit models and corresponding parameters, and allows and provides flexible editing and adjustment of various equipment, parameters and market clearing parameters of the new energy model. The specific power grid models of each unit are as follows:

[0040] The models of coal-fired units, gas-fired units, and new energy units should meet the following requirements:

[0041]

[0042] Where P cmin , P fmin , P cmax , P fmax Respectively represent the minimum and maximum output of the unit, I c Indicates the state variable of the unit that cannot be shut down within the day, represents the state variable of the unit that can be shut down during the day for period t, They are the down-slope and up-slope rates of the unit respectively.

[0043] Hydropower units should meet the following requirements:

[0044]

[0045] Where P h min , P h max is the minimum and maximum output of the hydropower unit, Q hydro It is the daily power generation of the hydropower unit.

[0046] Pumped storage units should meet the following requirements:

[0047]

[0048] Where Pp,max is the installed capacity of the pumped storage unit, represents the state variable of the pumped storage unit for pumping or generating electricity during period t, λ p is the efficiency of the pumped storage unit.

[0049] Step 2: Combine the power grid model and external data of the new energy unit to analyze and generate the boundary data of the new energy unit;

[0050] Based on the unit, line and node models in the power grid model, by importing and parsing power grid section data or power grid planning state data such as BPA (Bonneville Power Administration power system simulation software) and GOPT (Grid Optimization Planning Tools, power planning and decision-making evaluation system), the boundary data in BPA and GOPT are matched with the power grid model to generate the boundary data of the new energy units.

[0051] BPA and GOPT data contain the boundary data necessary for new energy units to participate in the daily clearing of the electricity spot market. Through data governance, the data structure required for algorithm clearing is formed, which constitutes power system forecast data, planning data, constraint data and market declaration information, and supports visual display and editing of market boundary numbers.

[0052] Prediction data include system load curve and new energy unit output curve;

[0053] Planning data include tie-line operation plan, fixed output plan curve of non-market units and line maintenance plan;

[0054] Constraint data include system operation reserve, market unit initial status, market unit status constraints, market unit output constraints and section transmission limits;

[0055] Market declaration information refers to the output that units participating in the spot market need to declare before the market is cleared and the price corresponding to the output at each stage, forming a price-output declaration curve.

[0056] Step 3: According to the actual output of new energy units, obtain the market transaction model and unit quotation data of new energy units.

[0057] There are three typical modes for new energy to participate in electricity spot trading: quotation based on quantity, quotation based on quantity without quotation, and contract for difference. However, in the quotation based on quantity without quotation mode, new energy only participates in the market as a price taker, and in the contract for difference mode, the fluctuation of market electricity price does not affect the income of new energy. Therefore, both modes are not conducive to cultivating the market competitiveness of new energy, and at the same time, they compress the profit space of conventional units and reduce their enthusiasm for participating in the market.

[0058] In view of the fact that the output of new energy generating units is volatile, random and greatly affected by weather changes, this embodiment adopts two types of declaration methods for new energy generating units to participate in market transactions: segmented declaration and time-sharing declaration in the quantity and quotation mode.

[0059] Segmented declaration means that the new energy units divide the output limit to the rated capacity into several segments, and the declared price increases with the number of declared segments, showing a monotonous non-decreasing trend. The characteristic of this mode is that the new energy uses the same declaration curve throughout the day, such as Figure 2 shown.

[0060] Time-sharing declaration is to divide the whole day into different periods, and the new energy units declare quantity and price information in each period. The characteristic of this mode is that new energy can flexibly use different quotation strategies according to the supply and demand relationship of the system. The declaration curve is as follows: Figure 3 shown.

[0061] Step 4: Construct a new energy unit participation market model that includes the power grid model, boundary data, unit quotation data and transaction mode of the new energy unit, and configure corresponding market transaction rules for the new energy unit participation market model.

[0062] After completing the construction of the power grid model and the generation of market boundary data analysis, this embodiment configures market trading rules, such as using node electricity prices as the basis for market settlement, and calling the clearing algorithm to simulate the clearing of new energy participating in the electricity spot market. Market trading rules are used to manage the order and parameter information of different trading varieties of new energy participating in the spot market (day-ahead, real-time market), including quotation method, clearing basis, unit output declaration section number, upper / lower limit of declared price, settlement price method, etc.

[0063] Step 5: Call the safety constrained unit commitment (SCUC), safety constrained economic dispatch (SCED) and node power price calculation (LMP) clearing algorithms to simulate the new energy unit participation in the market model and obtain the simulation results.

[0064] The SCUC algorithm is based on the system load forecast for each period in the future and the quotation information of power generation companies. Under the premise of meeting the constraints of the units and the power grid, the SCUC algorithm takes the minimum power purchase cost of the entire network on the planned trading day as the optimization goal, and gives the unit combination with the best power generation cost. The optimization goals of the SCUC algorithm for the day-ahead and real-time power spot market are as follows:

[0065]

[0066] In the formula, T represents the total number of time periods, N represents the number of units, P represents the unit output, CP represents the unit operating cost, M represents the network power flow constraint relaxation penalty factor, NL and NS represent the number of lines and sections respectively, and SL represents the power flow relaxation variable. Among them, the subscripts i, t, l, and s represent the i-th unit, time period, line, and section; the superscripts + and - represent the forward and reverse directions respectively.

[0067] The bidding requirements for generators in SCUC include the following factors:

[0068] 1) Quotation for startup of generator sets;

[0069] 2) Quotation for starting the generator set;

[0070] 3) Quotation for slight increase in electricity of generator sets;

[0071] 4) The rate of change of output of the generator set during start-up, shutdown and normal operation;

[0072] 5) Minimum continuous running time, minimum continuous shutdown time, and maximum start and shutdown times of the generator set;

[0073] 6) The power span range on the power generation unit quotation curve must include the declared highest and lowest power output points; the power generation quotation curve can be different in each bidding period.

[0074] The bidding results of SCUC must meet the following factors:

[0075] 1) System load requirements;

[0076] 2) Safety of lines and transmission sections;

[0077] 3) Generators can include economic dispatch, self-start, self-dispatch, non-participation and other options;

[0078] 4) Economic dispatch of units, which determines whether to start the unit and the amount of power generation to be cleared based on the quotation;

[0079] 5) Self-starting units require the operation of the generating units to be guaranteed and the power generation clearance volume to be determined based on the quotation;

[0080] 6) Self-dispatching units, which decide their own power generation and are willing to accept any market price.

[0081] 7) SCUC is solved using a mixed integer programming (MIP) algorithm, which can take into account the accurate modeling of flexible operating units in the power market, including combined cycle units, pumped storage units, etc.

[0082] The SCED algorithm executes the Security Constrained Economic Dispatch (SCED) procedure based on the unit start and stop plan determined by the SCUC algorithm. Under the conditions of meeting multiple constraints such as power generation and consumption balance, power grid safety, and unit operation requirements, the total power purchase cost on the planned trading day is minimized, and the output of each unit in each period of time is optimized. The optimization objectives of the SCED algorithm in the real-time power spot market are as follows:

[0083]

[0084] The SCED program needs to meet the following factors:

[0085] 1) Consider all transmission sections and line constraints in the power grid;

[0086] 2) Consider practical constraints such as smooth unit output curve;

[0087] 3) Execute centralized bidding based on the quotations of various market participants;

[0088] 4) The bidding results include the active output levels of all units in the system;

[0089] 5) The program can provide shadow prices for power generation and consumption balance and transmission constraints.

[0090] 6) Unit startup and line constraints at different time scales

[0091] The LMP algorithm is based on the calculation results of SCED, according to the marginal unit price cleared in the spot market, taking into account the node network loss information and line congestion information of the power grid, and calculates and determines the node marginal electricity price of each node every 15 minutes. The node marginal electricity price contains 3 components, namely, the node marginal electricity price = boundary power price + marginal congestion price + marginal network loss price:

[0092] 1) Marginal electricity price

[0093] Unconstrained unified marginal cost of electricity purchase for the entire network without considering grid congestion and network losses.

[0094] 2) Marginal congestion price

[0095] The marginal cost component of node electricity purchase caused by grid congestion.

[0096] 3) Marginal network loss price

[0097] Marginal costs due to power transmission losses.

[0098] The node electricity price calculation function supports the node electricity price calculation needs of different market models such as zone electricity price and node electricity price.

[0099] Step 6: Based on the results of the new energy market operation, refer to the existing market evaluation indicators, use market fairness, market security, market economy and market environmental protection and other evaluation indicators to conduct a comprehensive analysis and evaluation of the new energy market. After the evaluation, the market trading rules can be adjusted based on the evaluation results to obtain market trading rules that are more suitable for the target units. Specific market evaluation indicators are as follows: Figure 4 As shown, the calculation schemes of the indicators are all existing technologies and will not be further described here.

[0100] Embodiment 2

[0101] This embodiment provides a system for simulating new energy units participating in the electricity spot market, including a memory, a processor, and a computer program. The computer program is stored in the memory and is configured to be executed by the processor to implement the method of simulating new energy units participating in the electricity spot market in embodiment one.

[0102] This embodiment also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method of simulating new energy participating in the electricity spot market in embodiment one.

[0103] Verification Example

[0104] Taking the application scenario of large-scale renewable energy generation as an example, a provincial power grid model is selected, and the maximum daily load is set to about 120,000MW. Renewable energy generation accounts for about 15-25% of the full-day load, and the interconnection line transmission power is about 20-25% of the load. New energy uses 0 price, peak-flat-valley electricity price, and on-grid electricity price as the electricity market declaration price to participate in the market, and other types of units participate in the market declaration based on fuel costs. The simulation method described in Example 1 is carried out. The results show that when new energy is declared at 0 price, on-grid electricity price, and peak-flat-valley electricity price, the overall consumption rate of new energy shows a downward trend. It is recommended to set a certain proportion of new energy electricity as a guaranteed consumption and set the peak-flat-valley electricity price declaration. This can not only avoid the volatility of market prices caused by the output characteristics of new energy, but also ensure the investment income of new energy power generators.

[0105] The technical solutions of the present invention are not limited to the above-mentioned embodiments, and any technical solutions obtained by equivalent replacement methods fall within the scope of protection required by the present invention.

Claims

1. A method for simulating new energy units to participate in the electricity spot market, characterized in that: The steps include: Construct a grid model for renewable energy units participating in the electricity spot market; Combine the power grid model and external data of the new energy unit to analyze and generate the boundary data of the new energy unit; According to the actual output of new energy units, obtain the market transaction mode and unit quotation data of new energy units; Construct a new energy unit market model that includes the power grid model, boundary data, unit quotation data and transaction mode of new energy units, and configure corresponding market transaction rules for the new energy unit market model; Call SCUC, SCED and LMP algorithms to simulate the market model of new energy units and obtain simulation results; Evaluation indicators are used to analyze and evaluate market operation results.

2. The method for simulating new energy to participate in the electricity spot market according to claim 1, characterized in that: The grid model of the new energy unit is: Where P cmin , P fmin , P cmax , P fmax Respectively represent the minimum and maximum output of the unit, I c Indicates the state variable of the unit that cannot be shut down within the day, represents the state variable of the unit that can be shut down during the day for period t, They are the down-slope and up-slope rates of the unit respectively.

3. The method for simulating new energy to participate in the electricity spot market according to claim 1, characterized in that: The boundary data is the boundary data required for new energy units to participate in the daily clearing of the electricity spot market, including forecast data, plan data, constraint data and market declaration information; The forecast data includes system load curve and new energy unit output curve; The planning data include the tie line operation plan, the fixed output plan curve of non-market units and the line maintenance plan; The constraint data include system operation reserve, market unit initial status, market unit status constraint, market unit output constraint and section transmission limit; The market declaration information is the output that the units participating in the spot market need to declare before the market is cleared and the price corresponding to the output in each stage.

4. The method for simulating new energy to participate in the electricity spot market according to claim 1, characterized in that: The transaction mode adopts a segmented declaration mode and a time-sharing declaration mode.

5. The method for simulating new energy to participate in the electricity spot market according to claim 1, characterized in that: The market trading rules include quotation method, clearing basis, unit output reporting stage, upper / lower limit of reported price and settlement price method.

6. The method for simulating new energy to participate in the electricity spot market according to claim 1, characterized in that: The optimization goal of the SCUC algorithm is: In the formula, T represents the total number of time periods, N represents the number of units, P represents the unit output, CP represents the unit operating cost, M represents the network power flow constraint relaxation penalty factor, NL and NS represent the number of lines and sections respectively, and SL represents the power flow relaxation variable. Among them, the subscripts i, t, l, and s represent the i-th unit, time period, line, and section; the superscripts + and - represent the forward and reverse directions respectively.

7. The method for simulating new energy to participate in the electricity spot market according to claim 6, characterized in that: The optimization goal of the SCED algorithm is:

8. The method for simulating new energy to participate in the electricity spot market according to claim 1, characterized in that: The evaluation indicators include market fairness, market security, market economy and market environmental protection.

9. A system for simulating new energy units participating in the electricity spot market, characterized in that: It comprises a memory, a processor and a computer program, wherein the computer program is stored in the memory and is configured to be executed by the processor to implement the method of simulating new energy participating in the electricity spot market as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed, controls the device where the computer-readable storage medium is located to execute the method for simulating new energy to participate in the electricity spot market as described in any one of claims 1 to 8.

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