System operation flexibility mining strategy based on flexible supply and demand indexes

Abstract

The invention belongs to the technical field of new energy, and provides a system operation flexibility mining strategy based on flexible supply and demand indexes. Comprising the following steps: 1) constructing a flexibility resource model; comprising construction of a micro gas turbine model, construction of an electric energy storage model and construction of a controllable load model. 2) establishing a power grid flexibility supply and demand index based on the power grid flexibility demand; the method has the beneficial effects that regulation and economic models of different flexible resources are established, then flexible supply and demand analysis is performed on the system, a difference value between flexible supply and demand is calculated, a flexible upward / downward supply and demand index is constructed, and a multi-objective function containing system flexibility missing degree, economic cost and peak load shifting is constructed based on the flexible upward / downward supply and demand index. Therefore, the operation flexibility and comprehensive benefits of the system are evaluated.

Description

Technical Field

[0001] The present invention belongs to the field of new energy technology and proposes a system operation flexibility mining strategy based on flexibility supply and demand indicators. Background Art

[0002] When operating, the power grid system often faces uncertain factors such as fluctuations in renewable energy, changes in electricity consumption behavior, and different market demands, which can cause problems such as imbalance in supply and demand and unstable operation. Therefore, conducting research on the exploration and improvement of system operation flexibility is of great significance to ensuring the stable operation of the system. Based on this, the present invention proposes a system operation flexibility mining strategy based on flexibility supply and demand indicators. First, a flexibility resource model including micro gas turbines, electric energy storage, and controllable loads is constructed to participate in system operation. Secondly, flexibility supply and demand indicators are established to study the improvement of system flexibility when multiple flexibility resources participate from the perspective of the system's upward and downward flexibility capacity. Then, based on the flexibility supply and demand indicators, a multi-objective function including system flexibility deficiency, economic cost, and peak shaving and valley filling is constructed to evaluate the comprehensive benefits and flexibility of system operation. Finally, the feasibility of the strategy proposed in the present invention is verified by analyzing the flexibility supply and demand indicators of the system under different scenarios. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to propose a system operation flexibility mining strategy based on flexibility supply and demand indicators, which is scientific, reasonable, efficient and practical.

[0004] A system operation flexibility mining strategy based on flexibility supply and demand indicators, which includes the following:

[0005] 1) Constructing a flexibility resource model, including the construction of a micro gas turbine model, an electric energy storage model, and a controllable load model;

[0006] 2) Establish grid flexibility supply and demand indicators based on grid flexibility requirements;

[0007] 3) Construct a multi-objective evaluation function based on the flexibility supply and demand indicators;

[0008] 4) Divide the operation scenarios;

[0009] 5) Select the power and load values ​​of each flexibility resource with the lowest flexibility loss in each operating scenario; compare and analyze the flexibility supply and demand indicators of the system under different scenarios; and verify that the proposed strategy can effectively and deeply explore the system operation flexibility.

[0010] Preferably, constructing the flexibility resource model includes the following steps:

[0011] Step 1: Construction of micro gas turbine model

[0012]

[0013] Where Z MT is the MT running fee, α t MT is the MT operation unit control cost at time t, is the MT output at time t, β MT is the MT participation, the value is [0.5,1], t start , t end The time for MT to be activated and deactivated;

[0014] Step 2: Building an electric energy storage model

[0015]

[0016] Where N SOC (t) is the amount of energy stored at time t; is the energy storage and release efficiency of the electric energy storage; PinSOC and Pout SOC are the energy storage and release power; s is the self-loss rate;

[0017] Step 3: Construction of controllable load model

[0018]

[0019] Where Z py , Z zy , Z xj They are respectively movable, transferable and capable of reducing load regulation costs; Z L is the total cost of controllable load regulation; py ,λ zy ,λ xj are the unit control costs of movable, transferable and reducible loads respectively; P i,t py and P i,t xj Power regulation for shiftable and reducible loads; P i,t zy 、P i,t zy* is the power before and after the transferable load regulation; n is the number of controllable loads involved.

[0020] Preferably, constructing the flexibility supply and demand indicator includes the following steps:

[0021] Step 1: Flexibility Supply and Demand Analysis

[0022] The grid flexibility demand is determined by the grid load P l,t Wind and solar power generation power P WV,t Determine the system flexibility requirement L NE,t It is expressed as follows:

[0023]

[0024] Where, P nl,t is the net load of the system. The direction of flexibility demand can be reflected by the time domain fluctuation of the net load. When the load demand of the system increases at time t+1, an upward flexibility demand will be generated. Indicates that when the load demand decreases at time t+1, an upward flexibility demand is generated. express;

[0025] According to the response characteristics of different forms of flexibility resources, the flexibility supply levels are constructed as follows:

[0026]

[0027] Where, is the upward / downward flexibility supply of the system at time t; the upward flexibility supply includes and They are the upward flexibility supply of micro gas turbine, electric energy storage and controllable load at time t; the downward flexibility supply includes and are the downward flexibility supply of micro gas turbine, electric energy storage and controllable load at time t respectively; are the gas turbine up / down ramp rate; P MT ,max,P MT ,min,P MT , t are the maximum output, minimum output and output of the gas turbine at time t respectively; P CN ,max,P FN ,max,P CN ,t、P FN , t is the maximum charging power, maximum supply power and charging / discharging power of the energy storage device at time t; E N,max 、E N,min 、E N,t The upper and lower limits of the energy storage device and the energy storage value at time t; η C ,η F is the charging / discharging efficiency of the energy storage device; P L ,max,P L ,min,P L , t is the maximum value, minimum value and actual adjustment amount of the controllable load;

[0028] Step 2: Consider the relationship between flexibility supply and demand, calculate the difference between flexibility supply and demand, and construct an upward / downward flexibility supply and demand indicator;

[0029]

[0030] Where, The upward / downward flexibility of the system supply and demand capacity. When it is greater than 0, it means that the system supply and demand capacity is sufficient. Otherwise, there is a lack of flexibility. When flexibility is insufficient, there will be a risk of shedding some loads or stopping some wind and solar power generation output.

[0031] In the case of insufficient grid flexibility, an upward / downward flexibility deficit metric is constructed based on the flexibility supply and demand indicators to quantify the extent of this deficiency:

[0032]

[0033] Where, L up , L dn They are the degree of upward and downward flexibility loss of the system respectively.

[0034] Preferably, the construction of the multi-objective evaluation function comprises the following steps:

[0035] Step 1: Constructing the F1 function of system flexibility loss

[0036] The upward / downward flexibility loss degree constructed based on the flexibility supply and demand indicators is weighted according to the proportion of upward and downward flexibility to obtain the total flexibility loss degree of the power grid system:

[0037]

[0038] Where κ is the weight coefficient, which is determined by the degree of upward / downward flexibility loss.

[0039] Step 2: Construction of economic cost function

[0040]

[0041] Where, α price,NE , α price,loss Penalty for wind and solar curtailment: electricity price and network loss fee, P NE 、P loss is the amount of wind and solar power curtailment and network loss power, Z N , Z NE , Z loss Energy storage regulation fees, network loss fees, and penalty fees for curtailing wind and solar power;

[0042] Step 3: Constructing the peak shaving and valley filling effect function

[0043]

[0044] Wherein, Δx1 is the peak cutting index, Δx2 is the valley filling index, and Δx3 is the peak cutting and valley filling index; x max 、x min To optimize the peak / valley value of net load in a day before operation, xmax *、x min *These are the peak / valley values ​​of net load during the day after optimization.

[0045] Preferably, performing the operation scenario division includes the following steps:

[0046] Step 1: Construct a low wind and solar penetration system, where only micro gas turbines and controllable loads are considered in the system;

[0047] Step 2: Construct a high wind-solar penetration scenario, where only micro gas turbines and controllable loads are considered in the system;

[0048] Step 3: Construct a scenario with high wind and solar penetration rates, while considering the participation of micro gas turbines, electric energy storage, and controllable loads.

[0049] Through the above design scheme, the present invention can bring the following beneficial effects: first, establish the control and economic model of different flexibility resources (micro gas turbines, electric energy storage and controllable loads), then analyze the flexibility supply and demand of the system, calculate the difference between flexibility supply and demand, and construct the upward / downward flexibility supply and demand index. Based on this, a multi-objective function including system flexibility deficiency, economic cost and peak shaving and valley filling is constructed to evaluate the flexibility and comprehensive benefits of system operation. Finally, a simulation is carried out using a certain power grid system as an example to solve the power regulation of flexibility resources, and the upward / downward flexibility supply and demand index of the system under different scenarios is compared and analyzed to verify the effectiveness and feasibility of the strategy proposed by the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0051] Figure 1 This is a flow chart of the system operation flexibility mining strategy based on flexibility supply and demand indicators of the present invention;

[0052] Figure 2 This is a framework diagram of a power grid system based on a system operation flexibility mining strategy based on flexibility supply and demand indicators of the present invention;

[0053] Figure 3 This is a wind and solar maximum output and load curve diagram of a system operation flexibility mining strategy based on flexibility supply and demand indicators of the present invention;

[0054] Figure 4 The present invention provides a Pareto solution set of a multi-objective function of a system operation flexibility mining strategy based on flexibility supply and demand indicators;

[0055] Figure 5 The present invention is a system operation flexibility mining strategy based on flexibility supply and demand indicators upward flexibility supply and demand indicators;

[0056] Figure 6 The present invention provides a system operation flexibility mining strategy based on flexibility supply and demand indicators to obtain downward flexibility supply and demand indicators. DETAILED DESCRIPTION

[0057] The present invention proposes a system operation flexibility mining strategy based on flexibility supply and demand indicators, combined with Figures 1 to 6 , including the following steps:

[0058] 1. Constructing a regional power grid system, the present invention is based on Figure 2 The following description will be given using the system framework diagram as an example.

[0059] 2. Construction of flexibility resource model

[0060] (1) Microturbine (MT) model construction

[0061]

[0062] Where Z MT is the MT running fee, α t MT is the MT operation unit control cost at time t, P t MT is the MT output at time t, β MT is the MT participation, the value is [0.5,1], t start , t end The time when MT is activated and deactivated.

[0063] (2) Construction of electric energy storage model

[0064]

[0065] Where N SOC (t) is the amount of energy stored at time t; For electrical energy storage, the efficiency of electrical energy storage and release; is the storage and release power of electric energy storage; s is the self-loss rate.

[0066] (3) Construction of controllable load model

[0067]

[0068] Where Z py , Z zy , Z xj They are respectively movable, transferable and capable of reducing load regulation costs; Z L is the total cost of controllable load regulation; py ,λ zy ,λ xj are the unit control costs of movable, transferable and reducible loads respectively; P i,tpy and P i,t xj Power regulation for shiftable and reducible loads; P i,t zy 、P i,t zy* is the power before and after the transferable load regulation; n is the number of controllable loads involved.

[0069] 3. Construction of flexibility supply and demand indicators

[0070] (1) Flexibility supply and demand analysis

[0071] The grid flexibility demand is determined by the grid load P l,t Wind and solar power generation power P WV,t Determine the system flexibility requirement L NE,t It is expressed as follows:

[0072]

[0073] Where, P nl,t The direction of flexibility demand can be reflected by the time domain fluctuation of net load. When the system load demand increases at time t+1, an upward flexibility demand will be generated. Indicates that when the load demand decreases at time t+1, an upward flexibility demand is generated. express.

[0074] According to the response characteristics of different forms of flexibility resources, the flexibility supply levels are constructed as follows:

[0075]

[0076] Where, is the upward / downward flexibility supply of the system at time t; the upward flexibility supply includes and They are the upward flexibility supply of micro gas turbine, electric energy storage and controllable load at time t; the downward flexibility supply includes and are the downward flexibility supply of micro gas turbine, electric energy storage and controllable load at time t respectively; are the gas turbine up / down ramp rate; P MT ,max,P MT ,min,P MT , t are the maximum output, minimum output and output of the gas turbine at time t respectively; P CN ,max,P FN ,max,P CN ,t、P FN, t is the maximum charging power, maximum supply power and charging / discharging power of the energy storage device at time t; E N,max 、E N,min 、E N,t The upper and lower limits of the energy storage device and the energy storage value at time t; η C ,η F is the charging / discharging efficiency of the energy storage device; P L ,max,P L ,min,P L , t is the maximum value, minimum value and actual adjustment amount of the controllable load that can be adjusted.

[0077] (2) Considering the relationship between flexibility supply and demand, calculate the difference between flexibility supply and demand, and construct flexibility upward / downward supply and demand indicators.

[0078]

[0079] Where, This represents the system's upward / downward flexibility in supply and demand. When it is greater than 0, it indicates sufficient flexibility; otherwise, flexibility is insufficient. Insufficient flexibility can lead to the risk of shedding some load or halting some wind and solar power generation.

[0080] In the case of insufficient grid flexibility, an upward / downward flexibility deficit metric is constructed based on the flexibility supply and demand indicators to quantify the extent of this deficiency:

[0081]

[0082] Where, L up , L dn They are the degree of upward and downward flexibility loss of the system respectively.

[0083] 4. Construction of multi-objective evaluation function

[0084] (1) Construction of the F1 function for system flexibility loss

[0085] The upward / downward flexibility loss degree constructed based on the flexibility supply and demand indicators is weighted according to the proportion of upward and downward flexibility to obtain the total flexibility loss degree of the power grid system:

[0086]

[0087] Where κ is the weight coefficient, which is determined by the degree of upward / downward flexibility loss.

[0088] (2) Construction of economic cost function

[0089]

[0090] Where, αprice,NE , α price,loss Penalty electricity price and network loss fee for curtailing wind and solar power, P NE 、P loss is the amount of wind and solar power curtailment and network loss power, Z N , Z NE , Z loss These include electric energy storage regulation costs, network loss costs, and penalty fees for curtailing wind and solar power.

[0091] (3) Construction of peak shaving and valley filling effect function

[0092]

[0093] Wherein, Δx1 is the peak cutting index, Δx2 is the valley filling index, and Δx3 is the peak cutting and valley filling index; x max 、x min To optimize the peak / valley value of net load in a day before operation, x max *、x min * represents the peak / valley value of the net load within a day after optimized operation. Δv3 is selected as the peak shaving and valley filling evaluation indicator in this paper.

[0094] 5. Divide the operation scenarios

[0095] (1) When the wind and solar penetration rate is low (taking the wind and solar penetration rate as an example, it is less than 20%), only the micro gas turbine and the controllable load are considered in the system.

[0096] (2) When the wind and solar penetration rate is high, only the micro gas turbine and controllable load are considered in the system.

[0097] (3) When the wind and solar penetration rates are high, consider the participation of micro gas turbines, electric energy storage and controllable loads;

[0098] 6. Use algorithms to solve

[0099] (1) Select the power and load values ​​of each flexible resource with the lowest flexibility loss in each operation scenario

[0100] (2) Comparative analysis of system flexibility supply and demand indicators in different scenarios

[0101] (3) Verify that the proposed strategy can effectively and deeply explore the system operation flexibility.

[0102] In-depth analysis Figures 4-6 The experimental results show that:

[0103] Depend on Figure 4 It can be seen that with the reduction of economic costs under the participation of various flexibility resources in regulation, the flexibility loss degree and peak-valley difference of the system are reduced. Figures 5-6As can be seen, in scenario 1, due to the low penetration of wind and solar power, the system's regulation capacity is insufficient or excessive, especially during peak demand periods. This can lead to excessive wind and solar power curtailment or load shedding. Scenario 2 increases the system's wind and solar power penetration, providing a certain degree of system flexibility. This significantly increases both upward and downward flexibility, reducing conventional unit output, lowering system economic costs by 0.7%, reducing flexibility deficit by 1.6%, and reducing the system's peak-to-valley variation by 3.13%. Scenario 3 increases the system's wind and solar power penetration while also incorporating electric energy storage and increasing the types of flexible resources involved. This further increases the system's flexible regulation capacity and promotes the absorption of renewable energy. In this scenario, the system's flexibility deficit is reduced by 4.3% compared to scenario 2, and the system's peak-to-valley variation is reduced by 4.09%. As shown above, by comparing and analyzing system flexibility supply and demand indicators under different wind and solar power penetration rates and different types of flexible resources involved, we can better understand the system's adjustable flexibility margin under different scenarios, further explore system flexibility, and fully leverage the advantages of interactive regulation between source, load, and storage, effectively storing and distributing clean energy and reducing system carbon emissions.

[0104] The calculation conditions, legends, etc. in the embodiments of the present invention are only used to further illustrate the present invention and are not exhaustive and do not constitute a limitation on the scope of protection of the claims. Those skilled in the art can conceive of other substantially equivalent alternatives based on the inspiration gained from the examples of the present invention without creative work, and all of them are within the scope of protection of the present invention.

Claims

1. A system operation flexibility mining strategy based on flexibility supply and demand indicators, characterized by: The following steps are involved: 1) Build a flexibility resource model; Including the construction of micro gas turbine model, electric energy storage model and controllable load model; 2) Establish grid flexibility supply and demand indicators based on grid flexibility requirements; 3) Construct a multi-objective evaluation function based on the flexibility supply and demand indicators; 4) Divide the operation scenarios; 5) Select the power and load values ​​of each flexibility resource with the lowest flexibility loss in each operating scenario; compare and analyze the flexibility supply and demand indicators of the system under different scenarios; and verify that the proposed strategy can effectively and deeply explore the system operation flexibility.

2. A system operation flexibility mining strategy based on flexibility supply and demand indicators according to claim 1, characterized in that: Building a flexibility resource model includes the following steps: Step 1: Construction of micro gas turbine model Where Z MT is the MT running fee, α t MT is the MT operation unit control cost at time t, P t MT is the MT output at time t, β MT is the MT participation, the value is [0.5,1], t start , t end The time for MT to be activated and deactivated; Step 2: Building an electric energy storage model Where N SOC (t) is the amount of energy stored at time t; is the energy storage and release efficiency of the electric energy storage; Pin SOC and Pout SOC are the energy storage and release power; s is the self-loss rate; Step 3: Construction of controllable load model Where Z py 、Z zy 、Z xj They are respectively movable, transferable and capable of reducing load regulation costs; Z L Total cost of regulating controllable loads; λ py ,λ zy ,λ xj are the unit control costs of movable, transferable and reducible loads respectively; P i,t py and P i,t xj Power regulation for shiftable and reducible loads; P i,t zy 、P i,t zy* is the power before and after the transferable load regulation; n is the number of controllable loads involved.

3. The system operation flexibility mining strategy based on flexibility supply and demand indicators according to claim 1 is characterized in that: Constructing a flexibility supply and demand indicator involves the following steps: Step 1: Flexibility Supply and Demand Analysis The grid flexibility demand is determined by the grid load P l,t Wind and solar power generation power P WV,t Determine the system flexibility requirement L NE,t It is expressed as follows: Where, P nl,t is the net load of the system. The direction of flexibility demand can be reflected by the time domain fluctuation of the net load. When the load demand of the system increases at time t+1, an upward flexibility demand will be generated. Indicates that when the load demand decreases at time t+1, an upward flexibility demand is generated. express; According to the response characteristics of different forms of flexibility resources, the flexibility supply levels are constructed as follows: Where, is the upward / downward flexibility supply of the system at time t; the upward flexibility supply includes and They are the upward flexibility supply of micro gas turbine, electric energy storage and controllable load at time t; the downward flexibility supply includes and are the downward flexibility supply of micro gas turbine, electric energy storage and controllable load at time t respectively; are the gas turbine up / down ramp rate; P MT,max 、P MT,min 、P MT,t are the maximum output, minimum output and output of the gas turbine at time t respectively; P CN,max 、P FN,max 、P CN,t 、P FN,t E is the maximum charging power, maximum supply power and charging / discharging power of the energy storage device at time t; N,max 、E N,min 、E N,t are the upper and lower limits of energy storage and the energy storage value at time t; ηC and ηF are the charging / discharging efficiency of the energy storage device; P L,max 、P L,min 、P L,t The maximum and minimum adjustable values ​​of the controllable load and the actual adjustment amount of the controllable load; Step 2: Consider the relationship between flexibility supply and demand, calculate the difference between flexibility supply and demand, and construct an upward / downward flexibility supply and demand indicator; Where, The upward / downward flexibility of the system supply and demand capacity. When it is greater than 0, it means that the system supply and demand capacity is sufficient. Otherwise, there is a lack of flexibility. When flexibility is insufficient, there will be a risk of shedding some loads or stopping some wind and solar power generation output. In the case of insufficient grid flexibility, an upward / downward flexibility deficit metric is constructed based on the flexibility supply and demand indicators to quantify the extent of this deficiency: Where, L up 、L dn They are the degree of upward and downward flexibility loss of the system respectively.

4. The system operation flexibility mining strategy based on flexibility supply and demand indicators according to claim 1 is characterized in that: The multi-objective evaluation function construction comprises the following steps: Step 1: Constructing the F1 function of system flexibility loss The upward / downward flexibility loss degree constructed based on the flexibility supply and demand indicators is weighted according to the proportion of upward and downward flexibility to obtain the total flexibility loss degree of the power grid system: Where κ is the weight coefficient, which is determined by the degree of upward / downward flexibility loss. Step 2: Construction of economic cost function Where, α price,NE , α price,loss Penalty electricity price and network loss fee for curtailing wind and solar power, P NE 、P loss is the amount of wind and solar power curtailment and network loss power, Z N 、Z NE 、Z loss Energy storage regulation fees, network loss fees, and penalty fees for curtailing wind and solar power; Step 3: Constructing the peak shaving and valley filling effect function Wherein, Δx1 is the peak cutting index, Δx2 is the valley filling index, and Δx3 is the peak cutting and valley filling index; x max 、x min To optimize the peak / valley value of net load in a day before operation, x max *、x min *These are the peak / valley values ​​of net load during the day after optimization.

5. The system operation flexibility mining strategy based on flexibility supply and demand indicators according to claim 1 is characterized in that: The operation scenario division includes the following steps: Step 1: Construct a low wind and solar penetration system, where only micro gas turbines and controllable loads are considered in the system; Step 2: Construct a high wind-solar penetration scenario, where only micro gas turbines and controllable loads are considered in the system; Step 3: Construct a scenario with high wind and solar penetration rates, while considering the participation of micro gas turbines, electric energy storage, and controllable loads.

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