A new energy power grid energy storage power station participates in auxiliary service bidding strategy optimization method

Abstract

A new energy power grid energy storage power station participates in auxiliary service bidding strategy optimization method, its steps are: step 1) the operating state parameters of new energy power grid energy storage power station access node are measured: step 2) measurement data normalization processing: step 3) the declared capacity of energy storage power station participating in auxiliary service bidding at t n+1 Time is calculated: step 4) the declared price of new energy power grid energy storage power station participating in auxiliary service bidding at t n+1 Time is calculated.The present application can optimize the declared capacity and declared price of energy storage power station participating in auxiliary service bidding, and can significantly improve the economy of energy storage power station participating in auxiliary service.

Description

Technical Field

[0001] This invention belongs to the field of electricity market in power systems, and particularly relates to an optimization method for bidding strategy of energy storage power stations participating in ancillary services in new energy power grids. Background Technology

[0002] With the introduction of dual-carbon targets and the continuous increase in installed capacity of renewable energy, the power system will gradually transform into a new type of power system dominated by new energy sources. However, on the one hand, due to the inherent randomness and volatility of clean energy sources such as wind and solar power, their high penetration rate poses a significant challenge to the safe, stable, and reliable operation of the power grid. On the other hand, due to the uncertainty and volatility of new energy output, the electricity pricing mechanism of the new power system will also exhibit significant volatility.

[0003] To enhance the safe and stable operation of the power system, energy storage devices can fully leverage the grid's resilience and provide strong support for the system's inertia and frequency stability. Furthermore, energy storage offers advantages such as bidirectional power regulation and rapid adjustment, allowing it to participate in ancillary service markets such as frequency and voltage regulation.

[0004] Compared to thermal power resources, energy storage resources possess faster regulation capabilities and superior frequency regulation performance. However, due to the high cost of energy storage systems, the economic viability of energy storage systems in assisting power system frequency and voltage regulation is difficult to assess, hindering their application in the power system. Reasonable economic returns are the foundation for the sustainable operation of energy storage power stations. Therefore, in new energy power grids that include wind power, thermal power, and other forms of power sources, how energy storage power stations can participate in ancillary service bidding, and how to determine their bid capacity and bid price, are critical issues that urgently need to be addressed. Currently, research on energy storage participation in the electricity market is in its early stages, and in-depth research has not yet been conducted on bidding models for energy storage participation in grid ancillary services.

[0005] In view of this, the present invention provides an optimization method for bidding strategies of new energy grid energy storage power stations participating in ancillary services, so as to meet the needs of energy storage power stations participating in the ancillary services market. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art by providing an optimization method for bidding strategies of new energy power grid energy storage stations participating in ancillary services, thereby determining the application capacity and application price of energy storage stations participating in the service market.

[0007] To solve the above-mentioned technical problems, the technical solution created by this invention is as follows:

[0008] Step 1) Measure the operating status parameters of the access node of the new energy grid energy storage power station:

[0009] At n fixed time intervals t1, t2, ..., t k ,...t n Where n is a natural number, k∈{1,2,…,n}, the voltage U of the i-th node in the new energy power grid is measured. i The wind power output P at the i-th node of the new energy power grid wt,i The thermal power output P at the i-th node of the new energy power grid TP,i The load P at the i-th node of the new energy power grid load,i The reactive power output ΔQ of the reactive power compensation device at the i-th node of the new energy power grid i :

[0010]

[0011] Step 2) Normalization of measurement data:

[0012] The voltage U of the i-th node in the new energy power grid i The wind power output P at the i-th node of the new energy power grid wt,i The thermal power output P at the i-th node of the new energy power grid TP,i The reactive power output ΔQ of the reactive power compensation device at the i-th node of the new energy power grid i The load P at the i-th node of the new energy power grid load,i The measurement data were normalized as follows:

[0013]

[0014] In the formula, U imax U imin For the voltage of the i-th node in the new energy power grid at t1, t2, ..., t k ,...t n The maximum and minimum values ​​among the measurements taken at these n times; P wt,imax P wt,imin For the wind power output of the i-th node in the new energy power grid at times t1, t2, ..., t k ,...t n The maximum and minimum values ​​among the measurements taken at these n times; P TP,imax P TP,imin For the thermal power output of the i-th node in the new energy power grid at times t1, t2, ..., t k ,...t n The maximum and minimum values ​​among the measurements taken at these n times. P load,imax P load,imin For the load of the i-th node in the new energy power grid at time t1, t2, ..., t k ,...t n The maximum and minimum values ​​among the measurements at these n times; ΔQ imax ΔQimin The reactive power output of the reactive power compensation device at the i-th node of the new energy power grid is at t1, t2, ..., t k ,...t n The maximum and minimum values ​​among the measurements taken at these n times.

[0015] Step 3) Calculate t n+1 The capacity of the instantaneous energy storage power station participating in the ancillary service bidding:

[0016] Step 3.1) Calculate the influence coefficient α of thermal power unit output on the declared capacity of energy storage power station participating in ancillary services. as .

[0017] The impact coefficient of thermal power unit output on the declared capacity of energy storage power stations for ancillary services is calculated using the following formula:

[0018]

[0019] In the formula, m represents the number of new energy grid nodes.

[0020] Step 3.2) Calculate t n+1 The declared capacity P of the energy storage power station participating in the ancillary services bidding. ES,as :

[0021] P ES,as =α as P ES (4)

[0022] In the formula, P ES This refers to the rated capacity of the energy storage power station.

[0023] Step 4) Calculate t n+1 The bid price for the grid-connected energy storage power station of Shike New Energy to participate in the ancillary service bidding:

[0024] Step 4.1) Calculate the impact factor β of voltage fluctuation on the bid price of energy storage power stations participating in ancillary service bidding. as :

[0025]

[0026] Step 4.2) Calculate the impact factor β of load fluctuation on the bid price of energy storage power stations participating in ancillary service bidding. other :

[0027]

[0028] Step 4.3) Calculate t n+1 The bid price e for the energy storage power station to participate in the ancillary services bidding price,as :

[0029]

[0030] In the formula, e price For the on-grid tariff of new energy, ω1 and ω2 are the weighting coefficients of voltage fluctuation on the bid price of energy storage power stations participating in ancillary service bidding and power fluctuation on the bid price of energy storage power stations participating in ancillary service bidding, respectively, and ω1+ω2=1.

[0031] The beneficial effects of this invention are:

[0032] This invention provides an optimization method for the bidding strategy of energy storage power stations participating in ancillary services in the new energy grid, which calculates the bidding capacity and bidding price of energy storage power stations participating in ancillary services in the new energy grid.

[0033] Real-time monitoring of the voltage at new energy grid nodes, wind power output, thermal power output, load at new energy grid nodes, and reactive power output of reactive power compensation devices in new energy grids, and calculations based on the monitoring parameters, can optimize the bidding capacity and bidding price of energy storage power stations participating in ancillary services, and can significantly improve the economics of energy storage power stations participating in ancillary services. Attached Figure Description

[0034] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0035] To better understand this invention, the following embodiments further illustrate its content; however, the scope of this invention is not limited to the embodiments described below. Those skilled in the art can make various modifications or alterations to this invention, and these equivalent forms are also within the scope defined by the claims listed in this application.

[0036] like Figure 1 As shown in the figure, an embodiment of the present invention provides an optimization method for bidding strategy of energy storage power stations participating in ancillary services in a new energy power grid, the steps of which are as follows:

[0037] Step 1: Measure the operating status parameters of the access node of the new energy grid energy storage power station:

[0038] In this embodiment, the operating status parameters of the access node of the new energy power grid energy storage station in a certain region are measured and monitored. The measurement time interval is 5 minutes, and the accuracy of the parameters affecting the new energy power grid is relatively high within this time.

[0039] Selecting the number of new energy grid nodes m=3, and the rated capacity P of the energy storage power station ES =30MW, renewable energy grid connection price e price=0.6 yuan / kWh, measuring the node voltage U of 3 nodes in the new energy power grid i The nodal wind power output P of 3 nodes wt,i Thermal power output P at 3 nodes TP,i The load demand power P of the three nodes loadi The reactive power output ΔQ of the reactive power compensation device with 3 nodes i If the number of measurements is 5, i.e., n=5, then the measurement data results at the 5 times t1, t2, t3, t4, and t5 are as follows:

[0040]

[0041] Step 2: Normalization of measurement data:

[0042] Based on the measurement data from formula (8), the voltage U of the three nodes of the new energy power grid corresponding to n=5 measurement times is calculated. i and the maximum value U in all node voltage data imax Minimum value U imin The wind power output P at the three nodes of the new energy power grid wt The maximum value P among i and all node voltage data wt,imax Minimum value P wt,imin The thermal power output P at the three nodes of the new energy power grid TP,i and the maximum value P among all node voltage data TP,imax Minimum value P TP,imin The i-th node P of the new energy power grid load,i The maximum value P among all load data load,imax Minimum value P load,imin The reactive power output ΔQ of the reactive power compensation devices at the three nodes of the new energy power grid i and the maximum value ΔQ in the reactive power output data of all node reactive power compensation devices. imax Minimum value ΔQ imin Then, the collected data is normalized according to formula (3), and the data processing results are as follows:

[0043]

[0044] Step 3: Calculate t n+1 The capacity of the instantaneous energy storage power station participating in the ancillary service bidding:

[0045] Step 3.1: Calculate the influence coefficient α of thermal power unit output on the capacity of energy storage power station participating in ancillary service bidding. as .

[0046] The impact coefficient of thermal power unit output on the declared capacity of energy storage power stations for ancillary services is calculated using the following formula:

[0047]

[0048] Step 3.2: Calculate t n+1 The declared capacity P of the instantaneous energy storage power station participating in the ancillary service bidding ES,as :

[0049] The influence coefficient α of thermal power unit output on the capacity of energy storage power stations participating in ancillary service bidding. as Multiplying this by the capacity of the energy storage power station yields the bid capacity P for the energy storage power station to participate in the ancillary services bidding. ES,as :

[0050] P ES,as =α fw P ES (4)

[0051] In the formula, P ES This refers to the rated capacity of the energy storage power station.

[0052] Step 4: Calculate t n+1 The bid price for the grid-connected energy storage power station of Shike New Energy to participate in the ancillary service bidding:

[0053] Step 4.1: Calculate the impact factor β of voltage fluctuation on the bid price of energy storage power stations participating in ancillary service bidding. as :

[0054]

[0055] Step 4.2: Calculate the impact factor β of load fluctuation on the bid price of energy storage power stations participating in ancillary service bidding. other :

[0056]

[0057] Step 4.3: Calculate t n+1 The bid price e for the energy storage power station to participate in the ancillary services bidding price,as :

[0058] The impact factor β of voltage fluctuations on the bid price of energy storage power stations participating in ancillary service bidding. as The impact factor β of load fluctuation on the bid price of energy storage power stations participating in ancillary service bidding. other Based on the actual operating status of the new energy power grid, the weights of the two influencing factors are set as ω1 = 0.5 and ω2 = 0.5, thus obtaining the application price e for the application capacity of the energy storage power station participating in ancillary services. price,as :

[0059]

[0060] The above are merely embodiments of the present invention and are not intended to limit the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for optimizing the bidding strategy of energy storage power stations participating in ancillary services in a new energy power grid, characterized in that, The steps are as follows: Step 1) Measure the operating status parameters of the access node of the new energy grid energy storage power station: Specifically: exist A fixed time interval ,in For natural numbers, Measuring the first new energy power grid Node voltage New energy power grid i Wind power output at each node New energy power grid i Thermal power output at each node New energy power grid i Node load New energy power grid i Reactive power output of each node reactive power compensation device : （1）； Step 2) Normalization of measurement data: Specifically: New energy power grid Node voltage New energy power grid Wind power output at each node New energy power grid Thermal power output at each node New energy power grid i Reactive power output of each node reactive power compensation device New energy power grid i Node load The measurement data were normalized as follows: （2） In the formula, , For the first new energy power grid i The voltage at each node is this n The maximum and minimum values ​​among the measurements at each time point; , For the first new energy power grid i The wind power output of each node is this n The maximum and minimum values ​​among the measurements at each time point; , For the first new energy power grid i The thermal power output of each node is this n The maximum and minimum values ​​among the measurements at each time point; , For the first new energy power grid i The load of each node is this n The maximum and minimum values ​​among the measurements at each time point; , For the first new energy power grid i The reactive power output of the reactive power compensation device at each node is... this n The maximum and minimum values ​​among the measurements at each time point; Step 3) Calculation The capacity of the instantaneous energy storage power station participating in the ancillary service bidding: Specifically: Step 3.1) Calculate the impact coefficient of thermal power unit output on the declared capacity of energy storage power station participating in ancillary services. ; The impact coefficient of thermal power unit output on the declared capacity of energy storage power stations for ancillary services is calculated using the following formula: （3） In the formula, m This refers to the number of nodes in the new energy power grid. Step 3.2) Calculation The capacity of energy storage power stations participating in the ancillary services bidding process : （4） In the formula, This refers to the rated capacity of the energy storage power station; Step 4) Calculation The bid price submitted by the new energy grid energy storage power station for participating in the ancillary services bidding; Specifically: Step 4.1) Calculate the impact factor of voltage fluctuation on the bid price of energy storage power stations participating in ancillary service bidding. : （5） Step 4.2) Calculate the impact factor of load fluctuation on the bid price of energy storage power stations participating in ancillary service bidding. : （6） Step 4.3) Calculation Bidding price for ancillary services of a time-storage energy storage power station : （7） In the formula, For the on-grid tariff of new energy, , These are the weighting coefficients of voltage fluctuations and power fluctuations on the bid price of energy storage power stations participating in ancillary services bidding, respectively. .

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