System demand response analysis method considering planning-operation regulation and control model

Abstract

The invention belongs to the technical field of new energy, and provides a system demand response analysis method considering a planning-operation regulation and control model, which comprises the following steps: determining a system wiring diagram and each branch parameter, and carrying out scene division; and constructing a demand response resource model: constructing a pumped storage device model, constructing an electricity price excitation load model and constructing an adjustable load model. According to the method, the system operation cost, the wind and light use and the peak clipping and valley filling effect are considered in the operation layer, so that the regulation and control process of the wind and light distributed power supply and the demand response resources is coordinated and optimized, the comprehensive benefits of system operation are improved, and the regulation and control potential of each resource is fully excavated.

Description

Technical Field

[0001] The present invention belongs to the field of new energy technology and proposes a system demand response analysis method considering a planning-operation control model. Background Art

[0002] The increase in the penetration rate of wind and solar distributed units in the power grid has increased the difficulty of the system in absorbing new energy. At the same time, under its influence, the system faces huge challenges in terms of power supply and demand balance, operational stability and economy. In order to ensure the reliability of power grid operation and meet energy supply needs, more and more demand response resources are put into operation in the power grid. At the same time, conducting research on demand response analysis can effectively configure various demand response resources in the system and fully explore their regulation potential. To this end, the present invention proposes a system demand response analysis method considering a planning-operation regulation model. First, various demand response resources in the system are classified and modeled. Then, a planning-operation regulation model is established. At the planning level, voltage stability indicators are considered to determine the access locations of wind and solar distributed power sources and demand response resources in the power grid. On the basis of the planning level, the operation level considers operating costs, wind and solar usage, and peak shaving and valley filling effects to coordinate and optimize the regulation process of wind and solar distributed power sources and demand response resources. Finally, by analyzing the system demand response situation before and after the planning-operation model participates in regulation, the effectiveness and feasibility of the proposed method in exploring the regulation potential of various demand response resources are verified. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to propose a system demand response analysis method considering the planning-operation control model, deeply explore the control potential of demand response resources, ensure reliable energy supply of the power grid, and be scientific, reasonable, efficient and practical.

[0004] A system demand response analysis method considering a planning-operation regulation model includes the following:

[0005] 1) Determine the system wiring diagram and branch parameters, and divide the scenarios, including the following steps:

[0006] Step 1: Only the demand-side response resources are considered, ignoring the planning-operation control model.

[0007] Step 2: Consider the participation of demand-side response resources and planning-operation control model at the same time.

[0008] 2) Build a demand response resource model.

[0009] Step 1: Construct a pumped storage device model.

[0010] The working state of the pumped storage device is mainly divided into the water filling state and the water discharge state, which correspond to the charging stage and the power generation stage respectively. The pumped storage device realizes the storage and release of electric energy through the mutual conversion of electric energy and water energy, which can alleviate the imbalance of power supply and demand in the system without affecting the stable operation of the system. The economic model is constructed as follows:

[0011]

[0012] Where, Γ CX is the operating cost of the pumped storage device, α X , α F are the electricity purchase price when the pumped storage device is in the charging stage and the electricity selling price when it is in the power generation stage, respectively. t X 、p t C are respectively the power consumption of the pumped storage device in the charging stage and the power generation in the power generation stage at time t, start X , t end X and t start C , t end C They are the start and end time of the charging phase and the start and end time of the power generation phase of the pumped storage device respectively.

[0013] Step 2: Construct an electricity price incentive load model.

[0014] Electricity price incentive load means that users actively adjust their electricity consumption time under the incentive of electricity price, and adjust it to the period with lower electricity price to reduce production and operation costs. Considering the characteristics of load in the power grid, it is divided into three categories: shiftable, transferable and curtailable. Its economic model is

[0015]

[0016] Where, Γ Z is the load operation cost of electricity price incentive, Γ i ZP , Γ i ZZ , Γ i ZX To encourage the operation cost of loads that can be translated, transferred, or reduced; Z is the time-of-use electricity price during period t; P i ZP 、p i,t ZX is the load that can be shifted and reduced during the t period, p i,t ZZ 、p i,t ZX*is the excitation load before and after transfer; n Z is the load quantity incentivized by the electricity price.

[0017] Step 3: Build a controllable load model.

[0018] The controllable load is regulated by the power grid and participates in the operation of the system. Its control capacity and time period are determined by the dispatching method. The load can be redistributed within the allowed time period, and some can be appropriately reduced. According to the form of participation in regulation, it can also be divided into three categories: shiftable, transferable, and curtailable.

[0019]

[0020] Where, Γ S is the operating cost of the adjustable load, Γ i SP , Γ i SZ , Γ i SX It can translate the load, transfer the load, and reduce the load operation cost; S is the time-of-use electricity price during period t; P i SP 、p i,t SX is the load that can be shifted or reduced during period t, p i,t SZ 、p i,t SX* The load can be adjusted before and after transfer; n S The number of adjustable loads.

[0021] 3) Build a planning-operation control model.

[0022] Step 1: Construct a planning-level control model.

[0023] The integration of wind and solar distributed power sources and demand response resources will cause certain voltage deviations in the grid. To consider the voltage stability of the grid operation, the voltage stability index is constructed as follows:

[0024]

[0025] Where a is the system node number, nodes i and j are the input and output terminals respectively; R i 、X i is the impedance value of the branch; Q j is the reactive power on the branch. Calculate the voltage stability index N of all nodes α , N αThe larger the node, the worse the voltage stability. The smaller N is, the better the system voltage stability performance. In order to reduce the system voltage limit problem caused by the access of wind and solar distributed power sources and demand response resources, priority is given to accessing places with good voltage stability.

[0026] Step 2: Build an operation layer control model.

[0027] On the premise of ensuring system voltage stability at the planning level, the operation level considers system operating costs, wind and solar usage, and peak shaving and valley filling effects to coordinate and optimize the regulation process of wind and solar distributed power sources and demand response resources, improve the comprehensive benefits of system operation, and fully tap the regulation potential of various resources.

[0028] (1) Operating cost F1, calculated as follows:

[0029]

[0030] (2) Wind and solar utilization rate, calculated as follows:

[0031]

[0032] Where, T is 24 hours, P w (t), P v (t) is the output power of wind and solar distributed power generation, p aw (t), p av (t) is the wind and solar distributed power generation used in the power grid.

[0033] (3) Peak shaving and valley filling effect, calculated as follows:

[0034]

[0035] Where, ΔP XF , ΔP TG , ΔP are peak shaving effect, valley filling effect, and peak shaving and valley filling effect respectively; are the maximum and minimum values ​​before load curve optimization, These are the maximum and minimum values ​​after load curve optimization.

[0036] 4) Use algorithms to solve the model.

[0037] Step 1: When the load demand is at its peak and the system energy supply is insufficient, the pumped storage device supplements the energy supply shortfall by generating electricity, and the incentive load and adjustable load are partially transferred to other time periods through translation, transferability, and reduction operations;

[0038] Step 2: When the load demand is at a low point and the system curtailment of wind and solar power is high, the pumped storage device absorbs the wind and solar resources by charging, and the load performs corresponding operations to shift the peak load to this period;

[0039] Step 3: Input the system parameters, wind and solar distributed power supply power, and demand response resource power into the algorithm, use MATLAB to solve it, and obtain the power of various resources and system load response in each scenario. By comparing and analyzing the simulation results, the effectiveness and feasibility of the method proposed in this invention are verified.

[0040] Through the above-mentioned design scheme, the present invention can bring the following beneficial effects: First, a demand-side resource economic model is established based on the control characteristics of the pumped storage device, the electricity price incentive load and the adjustable load itself. A planning-operation control model is constructed, and the impact of the access of wind and solar distributed power sources and demand response resources on the grid voltage is considered at the planning level, and a voltage stability index is established. In order to avoid the problem of system voltage exceeding the limit, access is given priority to places with small voltage stability indicators. At the operation level, the system operating cost, wind and solar usage, and peak shaving and valley filling effects are considered in order to coordinate and optimize the control process of wind and solar distributed power sources and demand response resources, improve the comprehensive benefits of system operation, and fully tap the control potential of various resources. Finally, the power and system load response of various resources before and after the participation of the planning-operation control model are solved by simulation, and the effectiveness and feasibility of the method proposed in the present invention are verified by comparative analysis of the simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0042] Figure 1 This is a solution process of a system demand response analysis method considering a planning-operation control model of the present invention;

[0043] Figure 2 This is a node system wiring diagram of a system demand response analysis method considering a planning-operation control model of the present invention;

[0044] Figure 3 Schematic diagram of wind and solar output on a typical day according to a system demand response analysis method considering a planning-operation control model of the present invention;

[0045] Figure 4 This is a node voltage stability index distribution diagram of a system demand response analysis method considering a planning-operation control model of the present invention;

[0046] Figure 5 This invention discloses a system demand response analysis method considering a planning-operation control model and a system time sequence power and load response diagram. DETAILED DESCRIPTION

[0047] The present invention provides a system demand response analysis method considering the planning-operation control model, combined with Figures 1 to 5 , including the following steps:

[0048] 1. Determine the system wiring diagram and each branch parameter. Figure 2 The following description will be given using the system framework diagram as an example. The scenario division includes the following steps:

[0049] Step 1: Only the demand-side response resources are considered, ignoring the planning-operation control model.

[0050] Step 2: Consider the participation of demand-side response resources and planning-operation control model at the same time.

[0051] 2. Build a demand response resource model.

[0052] Step 1: Construct a pumped storage device model.

[0053] The working state of the pumped storage device is mainly divided into the water filling state and the water discharge state, which correspond to the charging stage and the power generation stage respectively. The pumped storage device realizes the storage and release of electric energy through the mutual conversion of electric energy and water energy, which can alleviate the imbalance of power supply and demand in the system without affecting the stable operation of the system. The economic model is constructed as follows:

[0054]

[0055] Where, Γ CX is the operating cost of the pumped storage device, α X , α F are the electricity purchase price when the pumped storage device is in the charging stage and the electricity selling price when it is in the power generation stage, respectively. t X 、p t C are respectively the power consumption of the pumped storage device in the charging stage and the power generation in the power generation stage at time t, start X , t end X and t start C , t end C They are the start and end time of the charging phase and the start and end time of the power generation phase of the pumped storage device respectively.

[0056] Step 2: Construct an electricity price incentive load model.

[0057] Electricity price incentive load means that users actively adjust their electricity consumption time under the incentive of electricity price, and adjust it to the period with lower electricity price to reduce production and operation costs. Considering the characteristics of load in the power grid, it is divided into three categories: shiftable, transferable and curtailable. Its economic model is

[0058]

[0059] Where, ΓZ is the load operation cost of electricity price incentive, Γ i ZP , Γ i ZZ , Γ i ZX To encourage the operation cost of loads that can be translated, transferred, or reduced; Z is the time-of-use electricity price during period t; P i ZP 、p i,t ZX is the load that can be shifted and reduced during the t period, p i,t ZZ 、p i,t ZX* is the excitation load before and after transfer; n Z is the load quantity incentivized by the electricity price.

[0060] Step 3: Build a controllable load model.

[0061] The controllable load is regulated by the power grid and participates in the operation of the system. Its control capacity and time period are determined by the dispatching method. The load can be redistributed within the allowed time period, and some can be appropriately reduced. According to the form of participation in regulation, it can also be divided into three categories: shiftable, transferable, and curtailable.

[0062]

[0063] Where, Γ S is the operating cost of the adjustable load, Γ i SP , Γ i SZ , Γ i SX It can translate the load, transfer the load, and reduce the load operation cost; S is the time-of-use electricity price during period t; P i SP 、p i,t SX is the load that can be shifted or reduced during period t, p i,t SZ 、p i,t SX* The load can be adjusted before and after transfer; n S The number of adjustable loads.

[0064] 3. Build a planning-operation control model.

[0065] Step 1: Construct a planning-level control model.

[0066] The integration of wind and solar distributed power sources and demand response resources will cause certain voltage deviations in the grid. To consider the voltage stability of the grid operation, the voltage stability index is constructed as follows:

[0067]

[0068] Where a is the system node number, nodes i and j are the input and output terminals respectively; R i 、X i is the impedance value of the branch; Q j is the reactive power on the branch. Calculate the voltage stability index N of all nodes α , N α The larger the node, the worse the voltage stability. The smaller N is, the better the system voltage stability performance. In order to reduce the system voltage limit problem caused by the access of wind and solar distributed power sources and demand response resources, priority is given to accessing places with good voltage stability.

[0069] Step 2: Build an operation layer control model.

[0070] On the premise of ensuring system voltage stability at the planning level, the operation level considers system operating costs, wind and solar usage, and peak shaving and valley filling effects to coordinate and optimize the regulation process of wind and solar distributed power sources and demand response resources, improve the comprehensive benefits of system operation, and fully tap the regulation potential of various resources.

[0071] 1) Operating cost F1, calculated as follows:

[0072]

[0073] 2) Wind and solar energy utilization rate, calculated as follows:

[0074]

[0075] Where, T is 24 hours, P w (t), P v (t) is the output power of wind and solar distributed power generation, p aw (t), p av (t) is the wind and solar distributed power generation used in the power grid.

[0076] 3) Peak shaving and valley filling effect, calculated as follows:

[0077]

[0078] Where, ΔP XF , ΔP TG , ΔP are peak shaving effect, valley filling effect, and peak shaving and valley filling effect respectively; are the maximum and minimum values ​​before load curve optimization, These are the maximum and minimum values ​​after load curve optimization.

[0079] 4. Use algorithms to solve the model.

[0080] Step 1: When the load demand is at its peak and the system energy supply is insufficient, the pumped storage device supplements the energy supply shortfall by generating electricity, and the incentive load and adjustable load are partially transferred to other time periods through translation, transferability, and reduction operations;

[0081] Step 2: When the load demand is at a low point and the system curtailment of wind and solar power is high, the pumped storage device absorbs the wind and solar resources by charging, and the load performs corresponding operations to shift the peak load to this period;

[0082] Step 3: Input the system parameters, wind and solar distributed power supply power, and demand response resource power into the algorithm, use MATLAB to solve it, and obtain the power of various resources and system load response in each scenario. By comparing and analyzing the simulation results, the effectiveness and feasibility of the method proposed in this invention are verified.

[0083] In-depth analysis Figures 4-5 The experimental results show that:

[0084] Depend on Figure 4 It can be seen that through the calculation of voltage stability index, it can be seen that when the wind and solar distributed power sources are connected to nodes 31 and 41 respectively, and the pumped storage units, electricity price incentive loads, and adjustable loads are connected to nodes 19, 64, 3, 7, 51, 70, 12, and 36 respectively, the system voltage over-limit problem caused by their connection can be effectively solved to ensure the stability of system operation. Figure 5 The system timing power and load response before and after the planning-operation control model is involved is given by Figure 5It can be seen that before the regulation model was implemented, the system's demand response resource configuration was not rational. To fully realize its regulation potential, the system's energy output from renewable energy sources such as wind and solar power differed from the load's energy consumption, resulting in certain curtailment issues. After the regulation model was implemented, during the nighttime energy consumption low period from 24:00 to 5:00, the pumped storage device increased its charging power, effectively absorbing and storing curtailed wind and solar power in the system. Simultaneously, the incentive load and controllable loads operated to shift loads from other periods to this low energy consumption period. During the peak energy consumption period from 5:00 PM to 9:00 PM, the pumped storage device increased its discharge power to supplement energy supply, while the incentive load and controllable loads operated to reduce or partially shift peak loads to other periods. By rationally allocating demand response resources, the renewable energy curve, including wind and solar power output, more closely aligned with the load curve, effectively addressing the imbalance in system power supply and demand and improving the system's peak shaving and valley filling capabilities. Experimental results comparing the system's sequential power and load responses before and after the planning-operation regulation model was implemented validated the effectiveness and feasibility of the proposed method in tapping the regulatory potential of various demand response resources.

[0085] 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 demand response analysis method considering a planning-operation control model, characterized in that: The following steps are involved: Determine the system wiring diagram and branch parameters, and divide the scenarios; Constructing a demand response resource model: including constructing a pumped storage device model, a price incentive load model, and a controllable load model; Constructing a planning-operation control model: This includes constructing a planning-level control model and an operation-level control model. When load demand is at its peak and the system energy supply is insufficient, the pumped storage device supplements the energy supply shortfall through power generation, and the incentive load and adjustable load are partially transferred to other time periods through translation, transferability, and reduction operations. When load demand is at a low point and the system curtailment of wind and solar power is high, the pumped storage device absorbs wind and solar power resources through charging, and the load performs corresponding operations to transfer the peak load to this period. The system parameters, wind and solar distributed power generation power, and demand response resource power are input into the algorithm and solved using MATLAB to obtain the power of various resources and system load response in each scenario. The effectiveness and feasibility of the method proposed in this invention are verified by comparing and analyzing the simulation results.

2. A system demand response analysis method considering a planning-operation control model according to claim 1, characterized in that: Building a demand response resource model includes the following steps: Step 1: Build a pumped storage device model Where, Γ CX is the operating cost of the pumped storage device, α X , α F are the electricity purchase price when the pumped storage device is in the charging stage and the electricity selling price when it is in the power generation stage, respectively. t X 、p t C are respectively the power consumption of the pumped storage device in the charging stage and the power generation in the power generation stage at time t, start X , t end X and t start C , t end C They are the start and end time of the charging phase of the pumped storage device and the start and end time of the power generation phase; Step 2: Constructing a load model with electricity price incentives Where, Γ Z is the load operation cost of electricity price incentive, Γ i ZP , Γ i ZZ , Γ i ZX To encourage the operation cost of loads that can be translated, transferred, or reduced; Z is the time-of-use electricity price during period t; P i ZP 、p i,t ZX is the load that can be shifted and reduced during the t period, p i,t ZZ 、p i,t ZX* is the excitation load before and after transfer; n Z The quantity of loads that are incentivized by the electricity price; Step 3: Build a controllable load model Where, Γ S is the operating cost of the adjustable load, Γ i SP , Γ i SZ , Γ i SX It can translate the load, transfer the load, and reduce the load operation cost; S is the time-of-use electricity price during period t; P i SP 、p i,t SX is the load that can be shifted or reduced during period t, p i,t SZ 、p i,t SX* The load can be adjusted before and after transfer; n S The number of adjustable loads.

3. The system demand response analysis method considering the planning-operation control model according to claim 1 is characterized in that: The construction of the planning-operation control model includes the following steps: Step 1: Build a planning-level control model The integration of wind and solar distributed power sources and demand response resources will cause certain voltage deviations in the grid. To consider the voltage stability of the grid operation, the voltage stability index is constructed as follows: Where a is the system node number, nodes i and j are the input and output terminals respectively; R i 、X i is the impedance value of the branch; Q j is the reactive power on the branch; calculate the voltage stability index N of all nodes α , N α The larger the node, the worse the voltage stability; Step 2: Build an operation layer control model Including 1) operating cost F1, calculated as follows: 2) Wind and solar energy utilization rate, calculated as follows: Where, T is 24 hours, P w (t), P v (t) is the output power of wind and solar distributed power generation, p aw (t), p av (t) The amount of electricity generated by wind and solar distributed power sources used by the power grid; 3) Peak shaving and valley filling effect, calculated as follows: Where, ΔP XF , ΔP TG , ΔP are peak shaving effect, valley filling effect, and peak shaving and valley filling effect respectively; are the maximum and minimum values ​​before load curve optimization, These are the maximum and minimum values ​​after load curve optimization.

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