Source-grid-load-storage collaborative optimization scheduling method and device for constructed island power grid, and medium

Abstract

The invention discloses a source-grid-load-storage collaborative optimization scheduling method and device for a network construction type island power grid, and a medium, and relates to the field of power grid scheduling, and the method comprises the steps: obtaining prediction data based on the power flow distribution condition of the network construction type island power grid, and comprehensively considering a carbon transaction and demand response mechanism, the method takes operation maintenance, wind and light abandoning penalty, energy storage life loss, demand response reduction load compensation and carbon transaction cost minimization of a network construction type island power grid as targets, and takes network construction type island power grid power balance, an equipment operation limit value, energy storage charging and discharging times and user satisfaction as constraints. Constructing a source-grid-load-storage collaborative optimization scheduling model of the constructed island power grid; and taking a set time length as a step length, solving the source-grid-load-storage collaborative optimization scheduling model of the constructed-grid-type island power grid by adopting a linear programming method, obtaining an optimal configuration scheme of each power generation device of the constructed-grid-type island power grid, and realizing source-grid-load-storage collaborative optimization scheduling of the constructed-grid-type island power grid. Safe and stable operation of the island power grid can be guaranteed.

Description

Technical Field

[0001] The present application relates to the field of power grid dispatching, and particularly to a collaborative optimal dispatching method, device, and medium for a network-forming island power grid source-network-load-storage system. Background Art

[0002] Affected by natural disasters such as extreme weather, once the connection channel between the end of the power system and the main grid is disconnected, an island power grid is formed. The island power grid has a small scale and a small moment of inertia of its own, which causes certain difficulties in the dispatching operation of the island power grid. If the dispatching control measures are improper, the island power grid may become unstable. At the same time, building an island microgrid with new energy as the main body is also one of the main development paths of the future new energy system. Therefore, designing a collaborative optimal dispatching method and scheme for an island power grid source-network-load-storage system has very important engineering practical value.

[0003] In recent years, with the increasing depletion of traditional energy and the increasingly prominent environmental problems, accelerating the development and utilization of new energy has become a global consensus. In the future new power system, new energy power generation such as wind and solar will be the main part, and most of the new energy power generation is distributed at the end of the power grid, forming a power system with a high proportion of new energy.

[0004] Therefore, in the end power grid with a high proportion of new energy, if a power grid connection channel fails, the dispatching operation of the island power grid is more difficult. At the same time, the island power grid with new energy as the main body is also one of the main ways for the development of the future new power system and new energy system. Up to now, there are few application scenarios for the collaborative optimal dispatching of island power grids with new energy as the theme, and the application is still in the theoretical research stage. Moreover, most of the existing new energy grid connection methods are grid-following control, which collects the frequency and phase output by the power grid through a phase-locked loop and does not have the ability to actively support voltage and frequency, and cannot ensure the safe and stable operation of the island power grid. Summary of the Invention

[0005] In order to solve the above existing problems, the present application provides a collaborative optimal dispatching method, device, and medium for a network-forming island power grid source-network-load-storage system.

[0006] To achieve the above object, the present application provides the following solutions:

[0007] In a first aspect, the present application provides a collaborative optimal dispatching method for a network-forming island power grid source-network-load-storage system, including:

[0008] Obtain the topological structure, grid parameters, and load prediction data of the network-forming island power grid, and obtain the power flow distribution of the network-forming island power grid according to the operation mode of the network-forming island power grid;

[0009] Based on the power flow distribution of the grid-type isolated island power grid, the forecast data with a resolution of a set time length within the new energy day-ahead dispatch period is obtained, and the carbon trading and demand response mechanisms are comprehensively considered. The operation and maintenance of the grid-type isolated island power grid, the penalty for wind and solar abandonment, the loss of energy storage life, the compensation for load reduction in demand response, and the minimum carbon trading cost are taken as the goals. The power balance of the grid-type isolated island power grid, the equipment operation limit, the number of energy storage charge and discharge times, and the user satisfaction are taken as constraints to construct a source-grid-load-storage collaborative optimization dispatching model for the grid-type isolated island power grid.

[0010] Taking the set time as the step length, a linear programming method is used to solve the grid-type isolated island power grid source-grid-load-storage collaborative optimization scheduling model to obtain an optimal configuration plan for each power generation equipment in the grid-type isolated island power grid;

[0011] Based on the optimized configuration scheme of each power generation equipment in the grid-type isolated island power grid, the coordinated optimized scheduling of the source, grid, load and storage of the grid-type isolated island power grid is realized.

[0012] Optionally, the grid-type island power grid source-grid-load-storage collaborative optimization scheduling model is expressed as:

[0013]

[0014] In the formula, T represents the dispatching period, X represents the number of power grid equipment, and X WF represents the number of wind turbines in the power grid, X PV represents the number of photovoltaic power generation systems, X bat represents the number of grid energy storage batteries, X L Indicates the number of grid loads; c i’,t is the operation and maintenance cost of the i'th production equipment in the power grid at time t, P i’,t is the output power of the i'th production equipment at time t; c i”WF,t is the penalty cost of wind power abandonment of the ith wind turbine generator at time t, P i”WF,t is the reported power of the ith wind turbine generator set at time t, P′ i”WF,t is the actual output power of the ith wind turbine generator set at time t; c i”’PV,t is the penalty cost of abandonment of the PV system of the ith group at time t, P i”’PV,t is the reported power of the PV system of the i-th group at time t, P′ i”’PV,t is the actual output power of the 'i'th photovoltaic system at time t; c i””bat,t is the initial investment cost of the i-th energy storage battery, L ibat,t is the life loss ratio of the energy storage battery; c i””’L,t is the compensation price for reducing load at the i-th load at time t, P i””’L,t is the load power of the ith load before the demand response at time t, P′ i””’L,tis the load power of the ith load after the demand response at time t; c CE,t is the carbon emission cost at time t, β CEO,t is the carbon emissions at time t, β CEc,t is the carbon capture amount at time t, β CEr,t is the carbon quota at time t, and F is the objective function.

[0015] Optionally, the new energy day-ahead scheduling period is 24 hours before the new energy day; the set duration is 15 minutes.

[0016] Optionally, the process of solving the grid-type island power grid source-grid-load-storage collaborative optimization scheduling model using a linear programming method with the set time length as a step length to obtain an optimal configuration scheme for each power generation equipment in the grid-type island power grid further includes:

[0017] Real-time detection of the operating status of the grid-type isolated power grid, acquisition of power load data, and real-time acquisition of forecast data for new energy within m hours of the day;

[0018] Compare the forecast data of new energy for m hours within a day with the forecast data of new energy with a resolution of a set duration within the day-ahead dispatch period to obtain the comparison deviation;

[0019] Based on the comparison deviation, the grid-type island power grid source-grid-load-storage collaborative optimization scheduling model is adopted, and the set time length is used as the calculation step length to correct the optimal configuration plan of each power generation equipment of the grid-type island power grid in real time and rollingly, so as to obtain the optimal scheduling plan of the new energy within m hours of the day;

[0020] According to the optimal dispatching plan of new energy within m hours of the day, the optimal configuration plan of each power generation equipment of the grid-forming island power grid is adjusted in real time to obtain the final optimal configuration plan of each power generation equipment of the grid-forming island power grid.

[0021] Optionally, the power balance of the grid-type island power grid is expressed as:

[0022]

[0023] Where P i and Q i are the active power and reactive power injected into node i by the island power grid respectively; U i and U j are the voltage amplitudes of nodes i and j respectively; θ ij is the voltage phase difference between node i and node j; G ij and B ij are the real and imaginary parts of the elements in the i-th row and j-th column in the node admittance matrix respectively; n is the number of nodes.

[0024] Optionally, the equipment operation limit constraints include: energy storage battery constraints, energy storage battery charge state constraints, thermal power unit output power constraints, gas turbine generator unit output power constraints, wind farm output power constraints, photovoltaic power station output power constraints, power system node voltage limit constraints, and power system transmission line transmission power constraints.

[0025] Optionally, the user satisfaction constraint is expressed as:

[0026]

[0027] Where P iLc,t is the amount of power load interrupted at time t; P i””’L,t is the load power of the ith load before the demand response at time t, S e For user satisfaction.

[0028] Optionally, a segmented compensation price is used to determine demand response load reduction compensation.

[0029] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-mentioned grid-type island power grid source-grid-load-storage collaborative optimization scheduling method.

[0030] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-mentioned grid-type island power grid source-grid-load-storage collaborative optimization scheduling method.

[0031] According to the specific embodiments provided in this application, this application has the following technical effects:

[0032] The present application provides a method, device and medium for coordinated optimization scheduling of source, grid, load and storage of grid-type isolated power grid. Aiming at the problem of difficulty in scheduling of isolated power grids with a high proportion of new energy terminals, it is proposed to use grid-type technology to improve the scheduling level of isolated power grids, take the network topology of grid-type isolated power grid as a platform, analyze the flow distribution characteristics of grid-type isolated power grids, and build a basic framework of "source-grid-load-storage" optimization scheduling from both supply and demand sides. Combined with the forecast data with a resolution of set duration in the new energy day-ahead scheduling period, comprehensively consider carbon trading and user satisfaction, and the operation and maintenance of grid-type isolated power grid, wind and solar abandonment penalties, energy storage life loss, demand response load reduction compensation and carbon trading cost minimization as the goal, with the power balance of grid-type isolated power grid, equipment operation limit, energy storage charge and discharge times and user satisfaction as constraints, a coordinated optimization scheduling model of source, grid, load and storage of grid-type isolated power grid with the ability to actively support voltage and frequency is constructed, and then the optimal configuration plan of each power generation equipment of grid-type isolated power grid is obtained, and the coordinated optimization scheduling of source, grid, load and storage of grid-type isolated power grid is realized to ensure the safe and stable operation of the isolated power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 A schematic diagram of a flow chart of a method for coordinated optimization and dispatching of source, grid, load and storage in a grid-connected isolated power grid provided in an embodiment of the present application;

[0035] Figure 2 A schematic diagram of a two-level collaborative optimization scheduling process for day-ahead and intra-day provided in an embodiment of the present application;

[0036] Figure 3 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0038] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0039] In an exemplary embodiment, the present application provides a method for coordinated optimization scheduling of source, grid, load and storage of a grid-type isolated power grid. The method is executed by a computer device, which can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to a server as an example for explanation. Figure 1 As shown, the method includes:

[0040] Step 101: Obtain the topological structure, grid parameters and load forecast data of the meshed island grid, and obtain the power flow distribution of the meshed island grid according to the operation mode of the meshed island grid. The meshed island grid is referred to as the island grid or grid below.

[0041] Step 102: Based on the power flow distribution of the grid-type isolated island power grid, obtain the forecast data with a resolution of the set time length during the day-ahead dispatch period of the new energy, and comprehensively consider the carbon trading and demand response mechanisms, with the operation and maintenance of the grid-type isolated island power grid, the penalty for wind and solar abandonment, the loss of energy storage life, the compensation for demand response load reduction, and the minimum carbon trading cost as the goals, and with the power balance of the grid-type isolated island power grid, the equipment operation limit, the number of energy storage charge and discharge, and the user satisfaction as the constraints, construct a grid-type isolated island power grid source-grid-load-storage collaborative optimization dispatch model. Among them, the grid-type isolated island power grid source-grid-load-storage collaborative optimization dispatch model is expressed as:

[0042]

[0043] In the formula, T represents the dispatching period, X represents the number of power grid equipment, and X WF represents the number of wind turbines in the power grid, X PV represents the number of photovoltaic power generation systems, X bat represents the number of grid energy storage batteries, X L Indicates the number of grid loads; c i’,t is the operation and maintenance cost of the i'th production equipment in the power grid at time t, P i’,t is the output power of the i'th production equipment at time t; c i”WF,t is the penalty cost of wind power abandonment of the ith wind turbine generator at time t, P i”WF,t is the reported power of the ith wind turbine generator set at time t, P′ i”WF,t is the actual output power of the ith wind turbine generator set at time t; c i”’PV,t is the penalty cost of abandonment of the PV system of the ith group at time t, P i”’PV,t is the reported power of the PV system of the i-th group at time t, P′ i”’PV,t is the actual output power of the 'i'th photovoltaic system at time t; c i””bat,t is the initial investment cost of the i-th energy storage battery, L ibat,tis the life loss ratio of the energy storage battery; c i””’L,t is the compensation price for reducing load at the i-th load at time t, P i””’L,t is the load power of the ith load before the demand response at time t, P′ i””’L,t is the load power of the ith load after the demand response at time t; c CE,t is the carbon emission cost at time t, β CEO,t is the carbon emissions at time t, β CEc,t is the carbon capture amount at time t, β CEr,t is the carbon quota at time t, and F is the objective function.

[0044] For example, in order to achieve coordinated optimization and dispatching of isolated power grids 24 hours before the day, forecast data with a resolution of 15 minutes for new energy sources within 24 hours before the day can be obtained.

[0045] Step 103: With the set time length as the step length, a linear programming method is used to solve the grid-forming island power grid source-grid-load-storage collaborative optimization scheduling model to obtain an optimal configuration plan for each power generation equipment in the grid-forming island power grid.

[0046] For example, when the linear programming method is used to solve the problem with a step size of 15 minutes, the optimal configuration scheme of each power generation equipment in the isolated power grid is obtained, which is 96 optimal configuration schemes within the previous 24 hours.

[0047] Step 104: based on the optimal configuration scheme of each power generation equipment in the grid-forming isolated island power grid, the coordinated optimal dispatch of the source, grid, load and storage of the grid-forming isolated island power grid is realized.

[0048] By implementing the above steps 101 to 104, the present application can efficiently utilize the wind and solar energy of the isolated power grid, combine the load forecast data of the isolated power grid during the day-ahead dispatch period, and use the network topology of the isolated power grid as a platform to analyze the power flow distribution characteristics of the isolated power grid, and build a basic framework for "source-grid-load-storage" optimization dispatch from both the supply and demand sides. Comprehensively considering carbon trading and user satisfaction, with the operation and maintenance of the grid-type isolated power grid, the penalty for wind and solar abandonment, the loss of energy storage life, the compensation for demand response and load reduction, and the minimum carbon trading cost as the goals, and with the power balance of the grid-type isolated power grid, the equipment operation limit, the number of energy storage charge and discharge times, and the user satisfaction as constraints, a source-grid-load-storage collaborative optimization dispatching model for the grid-type isolated power grid is constructed to ensure the safe and stable operation of the isolated power grid. In addition, the present application also has the advantages of simple implementation plan and great engineering use value.

[0049] In another exemplary embodiment of the present application, in order to further achieve the purpose of economic, low-carbon and reliable operation of the isolated island power grid, in this embodiment, the power balance of the grid-type isolated island power grid is expressed as:

[0050]

[0051] Where P i and Q i are the active power and reactive power injected into the island grid into node i respectively. i and U j are the voltage amplitudes at node i and node j respectively. ij is the voltage phase difference between node i and node j. G ij and B ij are the real and imaginary values ​​of the elements in the i-th row and j-th column of the node admittance matrix, respectively. n is the number of nodes.

[0052] Furthermore, the equipment operation limit constraints may include: energy storage battery constraints, energy storage battery charge state constraints, thermal power unit output power constraints, gas turbine generator unit output power constraints, wind farm output power constraints, photovoltaic power station output power constraints, power system node voltage limit constraints, and power system transmission line transmission power constraints, where:

[0053] (1) The energy storage battery constraint is expressed as:

[0054] -P max-charge ≤P ibat,t ≤-P max-discharge .

[0055] In the formula, -P max-charge is the maximum charging power of the energy storage battery, -P max-discharge is the maximum discharge power of the energy storage battery. ibat,t is the power of the energy storage battery.

[0056] (2) The state of charge constraint of the energy storage battery is expressed as:

[0057] SOC min ≤SOC(t)≤SOC max .

[0058] In the formula, SOC min SOC is the lower limit of the state of charge of the energy storage battery. max is the upper limit of the state of charge of the energy storage battery. SOC(t) is the state of charge of the energy storage battery at time t.

[0059] The energy storage battery has energy balance in one cycle:

[0060] SOC(t=0)=SOC(t=T).

[0061] (3) The output power constraints of thermal power units, gas turbine generator sets, wind farms and photovoltaic power stations are expressed as:

[0062]

[0063] Where P Gi,t is the output power of the thermal power unit at time t, P Gi,min , P Gi,max are the upper and lower limits of thermal power unit output power, P GTi,t The output power of the gas turbine unit at time t, P GTi,min , P GTi,max are the upper and lower limits of gas turbine unit output power, P WFi,t , P PVi,t are the output power of wind turbine and photovoltaic power generation system at time t, P WFi,max , P PVi,max are the maximum output powers of wind turbines and photovoltaic power generation systems respectively.

[0064] (4) The voltage limit constraint of the power system node is expressed as:

[0065] U i,min ≤U i,t ≤U i,max .

[0066] Where U i,t Represents the voltage of node i at time t. U i,max and U i,min Represents the maximum and minimum voltages of node i.

[0067] (5) Transmission power constraints of power system transmission lines:

[0068] |P ij,t |≤P ij,max .

[0069] Where P ij,t P represents the line transmission power at time t. ij,max Indicates the maximum power transmitted by the line.

[0070] In another exemplary embodiment of the present application, in order to improve the power supply reliability of the isolated power grid, it is necessary to reduce part of the electric load in extreme scenarios to maintain the power balance of the system, and it is necessary to compensate for the reduced load. Based on this, there are:

[0071]

[0072] Where P iLs,t is the amount of electric load transferred at time t, transfer-in is positive and transfer-out is negative. iLc,t P is the amount of power load interrupted at time t. iLs,t,min and P iLs,t,max are the maximum and minimum transferable values ​​of the electric load at time t respectively. iLc,t,max It is the maximum interruptible value of the electric load at time t.

[0073] In another exemplary embodiment of the present application, the demand response mechanism may cause dissatisfaction and discomfort to users, so user satisfaction needs to be used as a constraint indicator. Based on this, the user satisfaction constraint adopted above can be expressed as:

[0074]

[0075] In the formula, S e For user satisfaction.

[0076] In another exemplary embodiment of the present application, in order to improve the real-time and economic efficiency of the optimized configuration of electric energy and realize the economic, low-carbon and reliable operation of the isolated power grid, the optimized scheduling scheme can also be corrected in real time during the implementation of the above step 103. Based on this, the process of correcting the optimized scheduling scheme includes:

[0077] Step 1: Real-time detection of the operating status of the grid-type island power grid, acquisition of power load data, and real-time acquisition of forecast data for m hours of new energy within a day. For example, acquisition of forecast data for 4 hours of new energy within a day.

[0078] Step 2: Compare the forecast data of new energy for m hours in a day with the forecast data of new energy with a resolution of a set duration during the day-ahead scheduling period to obtain a comparison deviation.

[0079] Step 3: Based on the comparison deviation, the grid-type island power grid source-grid-load-storage collaborative optimization scheduling model is adopted, and the set time is used as the calculation step length to correct the optimal configuration plan of each power generation equipment in the grid-type island power grid in real time and rollingly, and obtain the optimal scheduling plan of new energy within m hours of the day.

[0080] For example, the forecast data of new energy for m hours within a day is compared with the forecast data of 24 hours before the previous day. According to the deviation of the comparison data, based on the constructed grid-type isolated power grid source-grid-load-storage collaborative optimization scheduling model, with a calculation step of 15 minutes, the configuration plan of the optimized scheduling is corrected in real time, and the optimized scheduling plan for 4 hours within a day is further obtained, giving 16 optimal configuration plans within the day.

[0081] The rolling method is used to correct the optimal scheduling plan for the 4 hours in a day in real time. With a rolling cycle of 15 minutes, the optimal configuration plan for the next 4 hours is obtained by rolling, that is, the final optimal scheduling plan for the 4 hours in a day is obtained.

[0082] Step 4: According to the optimal dispatching plan of the new energy source for m hours in a day, the optimal configuration plan of each power generation equipment of the grid-forming island power grid is adjusted in real time to obtain the final optimal configuration plan of each power generation equipment of the grid-forming island power grid.

[0083] For example, Figure 2From the two-level collaborative optimization dispatching methods given, it can be seen that the optimization configuration scheme correction process provided by this application can mainly include two parts, namely, the two-level optimization dispatching 24 hours a day and 4 hours a day. When dispatching 24 hours a day, the dispatching center needs to obtain the new energy power forecast data 24 hours a day, the load forecast data 24 hours a day, and the network topology of the isolated island microgrid, and construct an optimized dispatching model for the isolated island power grid 24 hours a day (i.e., a network-building isolated island power grid source-grid-load-storage collaborative optimization dispatching model for the optimized dispatching of the isolated island power grid 24 hours a day).

[0084] When the isolated power grid is in production and operation on the same day, the key operating status parameters of the isolated power grid are detected in real time, including load parameters, network topology, power supply equipment status, energy storage system charge status and new energy station operation status. According to the measured load, compared with the load forecast data of the day before 24 hours, combined with the forecast data of the new energy output of the day within 4 hours, according to the established 24 hours optimization dispatch model of the isolated power grid, the 4 hours optimization dispatch plan within the day is re-solved. The dispatch plan of the day before 24 hours is based on the resolution of 15 minutes, and a total of 96 optimization dispatch results are given, forming the energy dispatch plan of the day before 24 hours. The optimization dispatch plan of the day within 4 hours is also solved with a resolution of 15 minutes. The optimization dispatch model of the day within 4 hours is solved, and a total of 16 optimization results are given, forming the energy optimization dispatch plan of the day within 4 hours. The 4 hours dispatch within the day should be combined with the forecast of the new energy output within the day, with a rolling cycle of 15 minutes, and the optimal configuration plan for the next 4 hours is obtained. In this way, the coordinated optimization dispatch plan of the isolated power grid within the day is completed.

[0085] In another exemplary embodiment of the present application, incorporating carbon emission trading into optimized scheduling is a key step in achieving low carbon. In this embodiment, the daily carbon quota is reset to zero and cannot be accumulated. The total carbon quota in a scheduling cycle is:

[0086]

[0087] In the formula, β CEot is the total amount of carbon quota, is the emission quota per unit output, λ is the carbon quota coefficient, and M is the total production of the system.

[0088] Furthermore, a carbon quota mechanism that conforms to the operating characteristics of the isolated power grid is proposed, and the carbon trading cost in each period is expressed as:

[0089]

[0090] In the formula, is the carbon trading cost in period t. is the reward amount per unit carbon quota, is the penalty amount. CEct is the carbon capture amount, β CErtFor carbon emissions.

[0091] When carbon emissions are greater than carbon quotas, the system (i.e., grid-type island power grid) needs to purchase carbon emission rights, and the larger the carbon emissions, the higher the carbon trading price required. Therefore, in order to further control carbon emissions, this application adopts a step-by-step carbon trading mechanism, that is, a segmented compensation price is used to determine the demand response load reduction compensation. For example, three time period compensation prices are used for optimized scheduling calculations. Among them, the model using a step-by-step carbon trading mechanism is expressed as:

[0092]

[0093] In the formula, δ is the carbon trading price, μ is the length of the carbon emission interval, and k is the growth rate of the carbon trading price. It is the tiered carbon trading cost.

[0094] Based on the above description, in actual application, the implementation process of the grid-type isolated power grid source-grid-load-storage collaborative optimization scheduling method provided by the present application can be described as follows:

[0095] Obtain the forecast data of new energy output and load data of the isolated power grid 24 hours (hours) before the day, and the state of charge of the energy storage system. Comprehensively consider the carbon trading and demand response mechanism, take the operation and maintenance of the isolated power grid, the penalty for wind and solar curtailment, the life loss of energy storage, the compensation for load reduction and the minimum carbon trading cost as the goal, and take the system power balance, equipment operation limit, energy storage charging and discharging times and user satisfaction as constraints to construct a grid-type isolated power grid source-grid-load-storage collaborative optimization scheduling model. The linear programming method is used to solve the grid-type isolated power grid source-grid-load-storage collaborative optimization scheduling model, obtain the isolated power grid scheduling plan 24 hours before the day, and give the output plan of the power supply equipment of the isolated power grid 24 hours before the day. According to the measured data of the load of the isolated power grid, combined with the 4-hour new energy forecast data within the day, according to the established optimization scheduling model, the day-ahead optimization scheduling plan is corrected in real time. Through the grid-type technology and the two-stage scheduling method of day-ahead and day-intraday, the economic, low-carbon and reliable operation of the isolated power grid can be achieved.

[0096] Furthermore, when the method provided in the present application is used to construct a dispatching configuration plan for an island power grid, the safe and reliable operation of the island power grid is taken as a prerequisite, the sum of the maintenance cost of the island power grid operating equipment, the cost of wind and solar power abandonment, the cost of load reduction compensation, and the carbon emission cost is minimized as the goal, the power balance of the island power grid and the operating limit of the equipment are constrained, and the ladder-type carbon trading mechanism and user satisfaction are considered at the same time to construct a grid-type island power grid source-grid-load-storage collaborative optimization dispatching model. The carbon emission cost should comprehensively consider the carbon emissions and the carbon quota, where the carbon emission cost coefficient is calculated using the model of the ladder-type carbon trading mechanism. Power balance includes the active power and reactive power balance of the power system. The operating limits include the output limits of the energy supply equipment and the operating limits of the network and the nodes. According to the established optimization dispatching model, the linear programming method is used to solve and obtain the output dispatching plan for the energy supply equipment of the island power grid.

[0097] It can be seen that this application aims to solve the problem of difficult dispatching of isolated power grids with a high proportion of new energy terminals by using grid-building technology to improve the dispatching level of isolated power grids, ensure the safe and reliable operation of power grids through grid-building wind power, photovoltaic and energy storage systems, and build a grid-building isolated power grid source-grid-load-storage collaborative optimization dispatching model with the goal of minimizing the total operating cost of the isolated power grid, thereby obtaining a real-time optimization dispatching plan for the isolated power grid.

[0098] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the coordinated optimization scheduling data of the source, network, load and storage of the grid-type isolated power grid. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for coordinated optimization scheduling of the source, network, load and storage of the grid-type isolated power grid is implemented.

[0099] Those skilled in the art will understand that Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0100] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0101] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0102] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0103] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0104] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0105] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0106] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for coordinated optimization scheduling of source, grid, load and storage of grid-connected isolated power grid, characterized in that: The grid-type isolated island power grid source-grid-load-storage collaborative optimization scheduling method comprises: The topological structure, grid parameters and load forecast data of the grid-forming island power grid are obtained, and the power flow distribution of the grid-forming island power grid is obtained according to the operation mode of the grid-forming island power grid; Based on the power flow distribution of the grid-type isolated island power grid, the forecast data with a resolution of a set time length within the new energy day-ahead dispatch period is obtained, and the carbon trading and demand response mechanisms are comprehensively considered. The operation and maintenance of the grid-type isolated island power grid, the penalty for wind and solar abandonment, the loss of energy storage life, the compensation for load reduction in demand response, and the minimum carbon trading cost are taken as the goals. The power balance of the grid-type isolated island power grid, the equipment operation limit, the number of energy storage charge and discharge times, and the user satisfaction are taken as constraints to construct a source-grid-load-storage collaborative optimization dispatching model for the grid-type isolated island power grid. Taking the set time as the step length, a linear programming method is used to solve the grid-type isolated island power grid source-grid-load-storage collaborative optimization scheduling model to obtain an optimal configuration plan for each power generation equipment in the grid-type isolated island power grid; Based on the optimized configuration scheme of each power generation equipment in the grid-type isolated island power grid, the coordinated optimized scheduling of the source, grid, load and storage of the grid-type isolated island power grid is realized.

2. The method for coordinated optimization and dispatching of source, grid, load and storage of grid-connected isolated power grid according to claim 1 is characterized in that: The grid-type island power grid source-grid-load-storage collaborative optimization dispatching model is expressed as: In the formula, T represents the dispatching period, X represents the number of power grid equipment, and X WF represents the number of wind turbines in the power grid, X PV represents the number of photovoltaic power generation systems, X bat represents the number of grid energy storage batteries, X L Indicates the number of grid loads; c i’,t is the operation and maintenance cost of the i'th production equipment in the power grid at time t, P i’,t is the output power of the i'th production equipment at time t; c i”WF,t is the penalty cost of wind power abandonment of the ith wind turbine generator at time t, P i”WF,t is the reported power of the ith wind turbine generator set at time t, P′ i”WF,t is the actual output power of the ith wind turbine generator set at time t; c i”’PV,t is the penalty cost of abandonment of the PV system of the ith group at time t, P i”’PV,t is the reported power of the PV system of the i-th group at time t, P′ i”’PV,t is the actual output power of the 'i'th photovoltaic system at time t; c i””bat,t is the initial investment cost of the i-th energy storage battery, L ibat,t is the life loss ratio of the energy storage battery; c i””’L,t is the compensation price for reducing load at the i-th load at time t, P i””’L,t is the load power of the ith load before the demand response at time t, P′ i””’L,t is the load power of the ith load after the demand response at time t; c CE,t is the carbon emission cost at time t, β CEO,t is the carbon emissions at time t, β CEc,t is the carbon capture amount at time t, β CEr,t is the carbon quota at time t, and F is the objective function.

3. The method for coordinated optimization and dispatching of source, grid, load and storage of grid-connected isolated power grid according to claim 1 is characterized in that: The new energy day-ahead scheduling period is 24 hours before the new energy day; the set duration is 15 minutes.

4. The method for coordinated optimization and dispatching of source, grid, load and storage of grid-connected isolated power grid according to claim 1 is characterized in that: The process of solving the source-grid-load-storage coordinated optimization dispatching model of the grid-forming isolated island power grid by using the set time as the step length and obtaining the optimal configuration scheme of each power generation equipment of the grid-forming isolated island power grid by using the linear programming method also includes: Real-time detection of the operating status of the grid-type isolated power grid, acquisition of power load data, and real-time acquisition of forecast data for new energy within m hours of the day; Compare the forecast data of new energy for m hours within a day with the forecast data of new energy with a resolution of a set duration within the day-ahead dispatch period to obtain the comparison deviation; Based on the comparison deviation, the grid-type island power grid source-grid-load-storage collaborative optimization scheduling model is adopted, and the set time length is used as the calculation step length to correct the optimal configuration plan of each power generation equipment of the grid-type island power grid in real time and rollingly, so as to obtain the optimal scheduling plan of the new energy within m hours of the day; According to the optimal dispatching plan of new energy within m hours of the day, the optimal configuration plan of each power generation equipment of the grid-forming island power grid is adjusted in real time to obtain the final optimal configuration plan of each power generation equipment of the grid-forming island power grid.

5. The method for coordinated optimization and dispatching of source, grid, load and storage of grid-connected isolated power grid according to claim 1, characterized in that: The power balance of the grid-type island power grid is expressed as: Where P i and Q i are the active power and reactive power injected into node i by the island power grid respectively; U i and U j are the voltage amplitudes at nodes i and j respectively; θ ij is the voltage phase difference between node i and node j; G ij and B ij are the real and imaginary values ​​of the elements in the i-th row and j-th column of the node admittance matrix respectively; n is the number of nodes.

6. The method for coordinated optimization and dispatching of source, grid, load and storage of grid-connected isolated power grid according to claim 1, characterized in that: Equipment operation limit constraints include: energy storage battery constraints, energy storage battery charge state constraints, thermal power unit output power constraints, gas turbine generator unit output power constraints, wind farm output power constraints, photovoltaic power station output power constraints, power system node voltage limit constraints and power system transmission line transmission power constraints.

7. The method for coordinated optimization and dispatching of source, grid, load and storage of grid-connected isolated power grid according to claim 1, characterized in that: The user satisfaction constraint is expressed as: Where P iLc,t is the amount of power load interrupted at time t; P i””’L,t is the load power of the ith load before the demand response at time t, S e For user satisfaction.

8. The method for coordinated optimization and dispatching of source, grid, load and storage of grid-connected isolated power grid according to claim 1, characterized in that: The demand response load reduction compensation is determined by adopting segmented compensation prices.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the source-grid-load-storage collaborative optimization scheduling method for a grid-type isolated power grid according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for coordinated optimization and scheduling of source, grid, load and storage of a grid-connected isolated power grid as described in any one of claims 1 to 8 is implemented.

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