A site selection and capacity optimization method and terminal for joint planning of adjustable resources

Abstract

The present invention discloses a site selection and sizing optimization method and terminal for joint planning of adjustable resources, which takes into account the adjustment capabilities of flexible resources such as different types of energy storage and demand response, obtains comprehensive costs based on the investment and operation and maintenance costs of electrochemical energy storage, pumped storage and hydrogen energy storage, the operating costs of generator sets and the load shedding costs, constructs an adjustable resource joint planning model with the minimum comprehensive cost as the goal, and proposes a site selection and sizing optimization method for joint planning of multiple adjustable resources under high wind power penetration, obtains the optimal capacity configuration and site selection layout of different energy storage systems, can effectively alleviate the problem of insufficient flexibility of the power grid under high wind power penetration, and reduce the investment cost of the power grid while improving the utilization rate of wind power.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid planning, and in particular to a site selection and sizing optimization method and terminal for joint planning of adjustable resources. Background Art

[0002] With the continuous improvement of the cleanliness of the power grid, the access of a high proportion of clean energy to the power grid has become an inevitable trend. However, the volatility and uncertainty of new energy sources such as wind power and photovoltaics have also had a certain impact on the reliable operation of the power system. It is necessary to strengthen the construction of flexible adjustment capabilities to ensure the real-time balance of system power.

[0003] As an efficient and flexible resource, energy storage can optimize the output characteristics of renewable energy, reduce its uncontrollability and randomness, and compensate for the shortcomings of insufficient output regulation margin and ramp rate of conventional units through rapid response. It can meet the power shortage caused by sudden changes in load demand and renewable energy output, improve the flexibility of the power system and promote the absorption of renewable energy.

[0004] Currently, the mainstream forms of energy storage include electrochemical storage, pumped hydro storage, and hydrogen storage. Electrochemical storage technology is mature, highly efficient, fast, flexible, and requires minimal geographical requirements. Pumped hydro power stations are large and technologically mature, but site selection is difficult and construction is time-consuming. Hydrogen is considered the most promising energy carrier to replace traditional fossil fuels. It is an excellent energy storage medium with the advantages of zero pollution and high energy density. However, hydrogen storage technology is currently immature and the costs of various facilities are relatively high.

[0005] At present, the equipment costs of various types of energy storage are still relatively high and are also restricted by many factors such as construction conditions and geographical conditions. How to optimize the site selection and sizing of different types of energy storage according to local conditions and improve the flexibility of the power system in the context of a high proportion of clean energy grid connection is one of the key technical issues that need to be solved. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a site selection and sizing optimization method and terminal for joint planning of adjustable resources, which can realize site selection and sizing optimization of adjustable resources and improve system flexibility.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0008] A site selection and sizing optimization method for joint planning of adjustable resources includes the following steps:

[0009] Obtain the wind farm active output time series and load active power time series;

[0010] Taking the minimization of the comprehensive cost of the power grid as the objective function, the comprehensive cost includes the investment and operation and maintenance costs of energy storage, the operating costs of the generator sets, and the load shedding costs. The energy storage includes electrochemical energy storage, pumped storage, and hydrogen energy storage. A joint planning model for adjustable resources that includes multiple types of energy storage is established. The constraints of the joint planning model are obtained based on the active output time series of the wind farm and the active power time series of the load.

[0011] By solving the joint planning model, the site selection and layout plan as well as the configuration capacity of each type of energy storage are obtained.

[0012] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0013] A site selection and sizing optimization terminal for adjustable resource joint planning includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0014] Obtain the wind farm active output time series and load active power time series;

[0015] Taking the minimization of the comprehensive cost of the power grid as the objective function, the comprehensive cost includes the investment and operation and maintenance costs of energy storage, the operating costs of the generator sets, and the load shedding costs. The energy storage includes electrochemical energy storage, pumped storage, and hydrogen energy storage. A joint planning model for adjustable resources that includes multiple types of energy storage is established. The constraints of the joint planning model are obtained based on the active output time series of the wind farm and the active power time series of the load.

[0016] By solving the joint planning model, the site selection and layout plan as well as the configuration capacity of each type of energy storage are obtained.

[0017] The beneficial effects of the present invention are: considering the flexible resource regulation capabilities of different types of energy storage and demand response, constructing an adjustable resource joint planning model with the goal of minimizing the comprehensive costs such as investment and operation and maintenance costs of electrochemical energy storage, pumped storage and hydrogen energy storage, operation costs of generator sets and load shedding costs, proposing a site selection and sizing optimization method for joint planning of multiple adjustable resources under high wind power penetration, obtaining the optimal capacity configuration and site selection layout of different energy storage systems, which can effectively alleviate the problem of insufficient flexibility of the power grid under high wind power penetration, and reduce the investment cost of the power grid while improving the utilization rate of wind power. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of a method for optimizing site selection and capacity for joint planning of adjustable resources according to an embodiment of the present invention;

[0019] Figure 2A schematic diagram of a site selection and capacity optimization terminal for adjustable resource joint planning according to an embodiment of the present invention;

[0020] Figure 3 A topological structure diagram of an embodiment of the present invention;

[0021] Figure 4 This is a time series diagram of active power output of a wind farm according to the second embodiment of the present invention;

[0022] Figure 5 This is a time series diagram of load active power according to the second embodiment of the present invention;

[0023] Description of labels:

[0024] 1. A site selection and sizing optimization terminal for joint planning of adjustable resources; 2. Memory; 3. Processor. DETAILED DESCRIPTION

[0025] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0026] Please refer to Figure 1 The embodiment of the present invention provides a method for optimizing site selection and capacity by joint planning of adjustable resources, comprising the steps of:

[0027] Obtain the wind farm active output time series and load active power time series;

[0028] Taking the minimization of the comprehensive cost of the power grid as the objective function, the comprehensive cost includes the investment and operation and maintenance costs of energy storage, the operating costs of the generator sets, and the load shedding costs. The energy storage includes electrochemical energy storage, pumped storage, and hydrogen energy storage. A joint planning model for adjustable resources that includes multiple types of energy storage is established. The constraints of the joint planning model are obtained based on the active output time series of the wind farm and the active power time series of the load.

[0029] By solving the joint planning model, the site selection and layout plan as well as the configuration capacity of each type of energy storage are obtained.

[0030] From the above description, it can be seen that the beneficial effects of the present invention are: considering the flexible resource adjustment capabilities of different types of energy storage and demand response, constructing an adjustable resource joint planning model with the goal of minimizing the comprehensive costs such as investment and operation and maintenance costs of electrochemical energy storage, pumped storage and hydrogen energy storage, operating costs of generator sets, and load shedding costs, and proposing a site selection and sizing optimization method for joint planning of multiple adjustable resources under high wind power penetration, obtaining the optimal capacity configuration and site selection layout of different energy storage systems, which can effectively alleviate the problem of insufficient flexibility of the power grid under high wind power penetration, and reduce the investment cost of the power grid while improving the utilization rate of wind power.

[0031] Furthermore, the objective function is to minimize the comprehensive cost of the power grid. The comprehensive cost includes the investment and operation and maintenance costs of energy storage, the operating costs of the generator sets, and the load shedding costs. The energy storage includes electrochemical energy storage, pumped storage, and hydrogen energy storage, specifically:

[0032]

[0033] Where, Represents the investment and operation and maintenance costs of electrochemical energy storage, pumped storage, and hydrogen energy storage, The operating cost of the power grid includes the power generation cost, start-up and shutdown costs of the generator sets, and the load shedding cost of the system.

[0034] From the above description, it can be seen that constructing an adjustable resource joint planning model with the goal of minimizing the comprehensive costs, including the investment and operation and maintenance costs of electrochemical energy storage, pumped storage and hydrogen energy storage, the operating costs of generator sets, and the load shedding costs, can effectively alleviate the problem of insufficient grid flexibility under high wind power penetration, thereby improving wind power utilization and reducing grid investment costs.

[0035] Furthermore, the investment and operation and maintenance costs of electrochemical energy storage, pumped storage, and hydrogen energy storage are calculated as follows:

[0036]

[0037]

[0038] Where, Represent the investment and operation and maintenance costs of electrochemical energy storage, pumped storage, and hydrogen energy storage respectively; R BES , R PSP , R HES They represent the operation and maintenance loss coefficients of electrochemical energy storage, pumped storage, and hydrogen energy storage respectively; η represents the discount rate; n BES , n PSP , n HES Respectively represent the operating years of electrochemical energy storage, pumped storage, and hydrogen energy storage; N Q Indicates the number of network nodes; N BES , N PSP , N HES Respectively represent the amount of electrochemical energy storage, pumped storage, and hydrogen energy storage; Represents the unit capacity cost of electrochemical energy storage; represents the rated capacity of the electrochemical energy storage b at node q; represents the unit power cost of pumped storage; represents the rated power of the pumped storage p at node q; They represent the unit power cost of the electrolyzer, the unit power cost of the fuel cell, and the unit capacity cost of the hydrogen storage tank in hydrogen energy storage respectively; They represent the rated power of the electrolyzer, the rated power of the fuel cell and the rated capacity of the hydrogen storage tank in the hydrogen energy storage h at node q respectively.

[0039] Furthermore, the operating cost of the generator set is calculated as follows:

[0040]

[0041] Where N GEN Indicates the number of generator sets; N T , N D Respectively, they represent the number of planning hours and days; represents the unit power generation cost of generator set n; It represents the active power output of the generator set n at the node q at time t; and They represent the startup cost and shutdown cost of generator set n at the node q at time t; c CUR represents the unit load shedding cost; Represents the load shedding amount of node q at time t.

[0042] From the above description, we can see that the annual operating cost is obtained by converting the cost of typical operating conditions under a limited planning time scale to one year, which can reduce the computational overhead caused by point-by-point calculations throughout the year.

[0043] Furthermore, the constraints of the joint planning model include: maximum installable capacity constraints for energy storage, energy storage site selection and layout constraints, wind power output constraints, system node power balance constraints, power supply margin constraints, line flow constraints, generator set operation constraints, electrochemical energy storage operation constraints, pumped storage operation constraints, and hydrogen energy storage operation constraints.

[0044] From the above description, it can be seen that analyzing the operating condition constraints of different energy storage resources facilitates the construction of an optimization model for the joint planning of multiple different adjustable resources such as energy storage, hydrogen storage, and pumped storage.

[0045] Please refer to Figure 2 Another embodiment of the present invention provides a site selection and capacity optimization terminal for adjustable resource joint planning, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:

[0046] Obtain the wind farm active output time series and load active power time series;

[0047] Taking the minimization of the comprehensive cost of the power grid as the objective function, the comprehensive cost includes the investment and operation and maintenance costs of energy storage, the operating costs of the generator sets, and the load shedding costs. The energy storage includes electrochemical energy storage, pumped storage, and hydrogen energy storage. A joint planning model for adjustable resources that includes multiple types of energy storage is established. The constraints of the joint planning model are obtained based on the active output time series of the wind farm and the active power time series of the load.

[0048] By solving the joint planning model, the site selection and layout plan as well as the configuration capacity of each type of energy storage are obtained.

[0049] From the above description, it can be seen that the beneficial effects of the present invention are: considering the flexible resource adjustment capabilities of different types of energy storage and demand response, constructing an adjustable resource joint planning model with the goal of minimizing the comprehensive costs such as investment and operation and maintenance costs of electrochemical energy storage, pumped storage and hydrogen energy storage, operating costs of generator sets, and load shedding costs, and proposing a site selection and sizing optimization method for joint planning of multiple adjustable resources under high wind power penetration, obtaining the optimal capacity configuration and site selection layout of different energy storage systems, which can effectively alleviate the problem of insufficient flexibility of the power grid under high wind power penetration, and reduce the investment cost of the power grid while improving the utilization rate of wind power.

[0050] Furthermore, the objective function is to minimize the comprehensive cost of the power grid. The comprehensive cost includes the investment and operation and maintenance costs of energy storage, the operating costs of the generator sets, and the load shedding costs. The energy storage includes electrochemical energy storage, pumped storage, and hydrogen energy storage, specifically:

[0051]

[0052] Where, Represents the investment and operation and maintenance costs of electrochemical energy storage, pumped storage, and hydrogen energy storage, The operating cost of the power grid includes the power generation cost, start-up and shutdown costs of the generator sets, and the load shedding cost of the system.

[0053] From the above description, it can be seen that constructing an adjustable resource joint planning model with the goal of minimizing the comprehensive costs, including the investment and operation and maintenance costs of electrochemical energy storage, pumped storage and hydrogen energy storage, the operating costs of generator sets, and the load shedding costs, can effectively alleviate the problem of insufficient grid flexibility under high wind power penetration, thereby improving wind power utilization and reducing grid investment costs.

[0054] Furthermore, the investment and operation and maintenance costs of electrochemical energy storage, pumped storage, and hydrogen energy storage are calculated as follows:

[0055]

[0056]

[0057] Where, Represent the investment and operation and maintenance costs of electrochemical energy storage, pumped storage, and hydrogen energy storage respectively; R BES , R PSP , R HES They represent the operation and maintenance loss coefficients of electrochemical energy storage, pumped storage, and hydrogen energy storage respectively; η represents the discount rate; n BES , n PSP , n HES Respectively represent the operating years of electrochemical energy storage, pumped storage, and hydrogen energy storage; N Q Indicates the number of network nodes; N BES , N PSP , N HES Respectively represent the amount of electrochemical energy storage, pumped storage, and hydrogen energy storage; Represents the unit capacity cost of electrochemical energy storage; represents the rated capacity of the electrochemical energy storage b at node q; represents the unit power cost of pumped storage; represents the rated power of the pumped storage p at node q; They represent the unit power cost of the electrolyzer, the unit power cost of the fuel cell, and the unit capacity cost of the hydrogen storage tank in hydrogen energy storage respectively; They represent the rated power of the electrolyzer, the rated power of the fuel cell and the rated capacity of the hydrogen storage tank in the hydrogen energy storage h at node q respectively.

[0058] Furthermore, the operating cost of the generator set is calculated as follows:

[0059]

[0060] Where N GEN Indicates the number of generator sets; N T , N D Respectively, they represent the number of planning hours and days; represents the unit power generation cost of generator set n; It represents the active power output of the generator set n at the node q at time t; and They represent the startup cost and shutdown cost of generator set n at the node q at time t; c CUR represents the unit load shedding cost; Represents the load shedding amount of node q at time t.

[0061] From the above description, we can see that the annual operating cost is calculated by converting the cost of typical operating conditions under a limited planning time scale to one year, which can reduce the computational overhead caused by point-by-point calculations throughout the year.

[0062] Furthermore, the constraints of the joint planning model include: maximum installable capacity constraints for energy storage, energy storage site selection and layout constraints, wind power output constraints, system node power balance constraints, power supply margin constraints, line flow constraints, generator set operation constraints, electrochemical energy storage operation constraints, pumped storage operation constraints, and hydrogen energy storage operation constraints.

[0063] From the above description, it can be seen that analyzing the operating condition constraints of different energy storage resources facilitates the construction of an optimization model for the joint planning of multiple different adjustable resources such as energy storage, hydrogen storage, and pumped storage.

[0064] The above-mentioned method and terminal for optimizing site selection and capacity for joint planning of adjustable resources of the present invention are described below through specific implementation methods:

[0065] Example 1

[0066] Please refer to Figure 1 A site selection and sizing optimization method for joint planning of adjustable resources includes the following steps:

[0067] S1, please refer to Figure 3 , obtain the wind farm active output time series and load active power time series.

[0068] S2. Taking the minimization of the comprehensive cost of the power grid as the objective function, the comprehensive cost includes the investment and operation and maintenance costs of energy storage, the operating costs of the generator sets, and the load shedding costs. The energy storage includes electrochemical energy storage, pumped storage, and hydrogen energy storage. A joint planning model for adjustable resources containing multiple types of energy storage is established. The constraints of the joint planning model are obtained based on the active output time series of the wind farm and the active power time series of the load.

[0069] In this example, the investment and operation and maintenance costs of electrochemical energy storage, pumped storage, and hydrogen energy storage, the operating costs of generator sets, and the system's load shedding costs are comprehensively considered. A joint planning model for different adjustable resources, including energy storage, hydrogen storage, pumped storage, and demand response, is established. An optimization method for site selection and sizing that considers multiple adjustable resources is constructed, with the objective function being to minimize the overall cost. This can be expressed as a mathematical function as follows:

[0070]

[0071] Where, The construction costs of various energy storage systems, including investment and operation and maintenance costs for electrochemical energy storage, pumped hydro storage, and hydrogen energy storage; The operating cost of the system includes the power generation cost, start-up and shutdown cost of the unit, and the load shedding cost of the system.

[0072] in,

[0073]

[0074] Where, Respectively represent the input and operation and maintenance losses of electrochemical energy storage, pumped storage, and hydrogen energy storage; R BES , R PSP , R HES They represent the operation and maintenance loss coefficients of electrochemical energy storage, pumped storage, and hydrogen energy storage respectively; η represents the discount rate; n BES , n PSP , n HES Respectively represent the operating years of electrochemical energy storage, pumped storage, and hydrogen energy storage; N Q Indicates the number of network nodes; N BES , N PSP , N HES Respectively represent the amount of electrochemical energy storage, pumped storage, and hydrogen energy storage; Represents the unit capacity cost of electrochemical energy storage; represents the rated capacity of the electrochemical energy storage b at node q; represents the unit power cost of pumped storage; represents the rated power of the pumped storage p at node q; They represent the unit power cost of the electrolyzer, the unit power cost of the fuel cell, and the unit capacity cost of the hydrogen storage tank in hydrogen energy storage respectively; They represent the rated power of the electrolyzer, the rated power of the fuel cell and the rated capacity of the hydrogen storage tank in the hydrogen energy storage h at node q respectively.

[0075]

[0076] Where N GEN Indicates the number of generator sets; N T , N D Respectively, they represent the number of planning hours and days; represents the unit power generation cost of generator set n; It represents the active power output of the generator set n at the node q at time t; and They represent the startup cost and shutdown cost of generator set n at the node q at time t; c CUR represents the unit load shedding cost; Represents the load shedding amount of node q at time t.

[0077] The constraints of the model include: maximum installed capacity of energy storage, energy storage site selection and layout constraints, wind power output constraints, system node power balance constraints, power supply margin constraints, line flow constraints, generator set operation constraints, electrochemical energy storage operation constraints, pumped storage operation constraints, and hydrogen energy storage operation constraints:

[0078] 1. The maximum installed capacity of energy storage can be constrained. The upper limit of the rated power of any energy storage at each node is determined by its location flag and the maximum capacity that can be built:

[0079]

[0080] in, is the rated power of the electrochemical energy storage b at node q; are the location flags of electrochemical energy storage b, pumped storage p, and hydrogen energy storage h on node q, respectively. They are 0-1 variables, where 0 indicates that the node has no energy storage connected, and 1 indicates that the node has energy storage connected. are the maximum capacity limits that can be planned for electrochemical energy storage b and pumped storage p respectively; The maximum capacity that can be planned for electrolyzers and fuel cells in hydrogen energy storage h.

[0081] 2. Energy storage site selection and layout constraints: any energy storage can only be connected to one of the candidate nodes:

[0082]

[0083] in, They are the candidate flags for electrochemical energy storage b, pumped storage p, and hydrogen energy storage h on node q, respectively. They are 0-1 constants, where 0 indicates that the energy storage at the node is not accessible, and 1 indicates that the energy storage at the node is accessible.

[0084] 3. Wind power output constraint, expressed as a mathematical function as follows:

[0085]

[0086] Where, It represents the output active power at the node q where the wind farm m is located at time t; It represents the maximum active power output of wind farm m at time t.

[0087] 4. The system node power balance constraint is expressed as follows using mathematical functions:

[0088]

[0089]

[0090] Where, γ gen , γ wind , γ ess are the generator set, wind farm, and energy storage station set at node q respectively; Γ ls and Γ le are the sets of lines that flow out and in the power from node q respectively; represents the active power flow of line l at time t; represents the charging and discharging power of the energy storage e at node q at time t; are the charge and discharge power of electrochemical energy storage b, pumped storage p, and hydrogen energy storage h at node q at time t; D q,t represents the power load of node q at time t.

[0091] 5. The power supply adequacy constraint is expressed as follows using a mathematical function:

[0092]

[0093] The above formula indicates that the total amount of load shedding in the system cannot exceed a certain proportion of the load demand.

[0094]

[0095] The above formula indicates that the load shedding power of a node cannot be greater than the power load of the node.

[0096] Among them, α cur is the power supply redundancy factor.

[0097] 6. Line power flow constraints are expressed as follows using mathematical functions:

[0098]

[0099] Where, Indicates the upper limit of the transmission capacity of line l; B l is the susceptance of line l; and are the phase angles of the first and last nodes of line l, respectively, and are continuous variables.

[0100] 7. The operating constraints of the generator set are expressed as follows using mathematical functions:

[0101]

[0102]

[0103] The above formula represents the output constraint of the generator set;

[0104]

[0105] The above formula represents the climbing constraint of the generator set;

[0106]

[0107] The above formula describes the relationship between the running / non-running status of the unit and the startup / shutdown decision;

[0108]

[0109]

[0110] The above formula represents the constraints of the minimum startup and minimum shutdown time of the generator set;

[0111]

[0112]

[0113] The above formula represents the start-up and shutdown cost constraint of the generator set;

[0114]

[0115] The above formula is the system spinning reserve constraint.

[0116] in, represents the rated capacity of the generator set n at the node q; q,n,t It represents the capacity of the generator set n at the node q where the generator set n is located at the time t when it starts running. It is a non-negative continuous variable. is the minimum technical output coefficient of generator set n; and are the upper and lower climbing coefficients of generator set n respectively; is the startup capacity of the node q where the generator set n is located at time t (the capacity started from the non-operating state to the operating state), is the shutdown capacity (the capacity to be shut down from the operating state to the non-operating state) at the node q where the generator set n is located at time t, both of which are non-negative continuous variables; and are the minimum start-up and shutdown time of generator set n respectively; and are the unit startup and shutdown capacity costs of generator set n respectively; ρ is the spinning reserve capacity coefficient.

[0117] 8. The operating constraints of electrochemical energy storage are expressed as follows using mathematical functions:

[0118]

[0119]

[0120]

[0121] The above formula indicates that the charge and discharge power of electrochemical energy storage cannot exceed the rated power;

[0122]

[0123] The above formula represents the mutually exclusive states of charging and discharging of electrochemical energy storage;

[0124]

[0125]

[0126] The above formula represents the SOC constraint of electrochemical energy storage state of charge;

[0127]

[0128] The above formula represents the relationship constraint between the rated power and rated capacity of electrochemical energy storage;

[0129]

[0130] The above formula indicates that the initial and final moments of electrochemical energy storage should be equal to the initial set values;

[0131]

[0132] The above formula represents the charge and discharge capacity constraint of the electrochemical energy storage, indicating that the sum of the charge and discharge capacity of the electrochemical energy storage should meet certain restrictions within the planning period, thereby extending its service life.

[0133] in, and are the discharge power and charging power of the electrochemical energy storage b on node q at time t, respectively; and are the discharge and charge flags of the electrochemical energy storage b at node q at time t, which are 0-1 variables; is the state of charge capacity of the electrochemical energy storage b at node q at time t; η BES,c and η BES,d are the charging efficiency and discharging efficiency of electrochemical energy storage, respectively; Δt is the interval time; and They are the upper and lower limits of periodic operation of electrochemical energy storage capacity state; is the continuous discharge duration of electrochemical energy storage b; and are the initial capacity state and the final capacity state of the electrochemical energy storage b at node q; δ is the initial charge ratio of the energy storage; Q max It is the upper limit coefficient of the charge and discharge capacity of electrochemical energy storage within the planning time. Its value is determined based on factors such as the number of charge and discharge cycles of the electrochemical energy storage and the performance of the energy storage converter.

[0134] 9. Pumped storage operation constraints. The operation constraints of pumped storage are similar to those of electrochemical energy storage. The difference is that since pumped storage power stations cannot directly switch quickly between the discharge state and the pumping state, they need to be restricted to a period of shutdown as an intermediate state. For the sake of uniform expression, it is assumed that pumped storage pumping represents pumped storage charging, pumped storage discharge represents pumped storage discharge, and reservoir capacity represents the pumped storage charge state. It can be expressed as a mathematical function as follows:

[0135]

[0136]

[0137]

[0138]

[0139]

[0140]

[0141]

[0142]

[0143]

[0144] in, and are the discharge power and charging power of the pumped storage p at node q at time t, respectively; and are the discharge and charge flags of the pumped storage p on node q at time t; is the charge capacity state of the pumped storage p at node q at time t; is the rated capacity of the pumped storage p at node q; η PSP,c and η PSP,d are the charging efficiency and discharging efficiency of pumped storage, respectively; and They are the upper and lower limits of periodic operation of pumped storage capacity status; and are the initial capacity state and final capacity state of the pumped storage p at node q, respectively; is the continuous discharge duration of the pumped storage p.

[0145] 10. Hydrogen energy storage operation constraints. The operating constraints of hydrogen energy storage are similar to those of electrochemical energy storage. The difference is that the upper limit of hydrogen energy storage charging power is the rated hydrogen production power of the electrolyzer, and the upper limit of hydrogen energy storage discharge power is the rated power generation power of the fuel cell. For the sake of uniform expression, it is assumed that hydrogen production by water electrolysis represents hydrogen energy storage charging, fuel cell power generation represents hydrogen energy storage discharge, and the hydrogen content in the hydrogen storage tank represents the state of charge of hydrogen energy storage. It can be expressed as a mathematical function as follows:

[0146]

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154] Where, and are the discharge power and charging power of the hydrogen energy storage h on node q at time t respectively; and are the discharge and charge flags of the hydrogen energy storage h on node q at time t respectively; is the state of charge capacity of hydrogen energy storage h at node q at time t; η HES,c and η HES,d are the charging efficiency and discharging efficiency of hydrogen energy storage respectively; and They are the upper and lower limits of the periodic operation of the hydrogen energy storage capacity state; and are the initial capacity state and final capacity state of hydrogen energy storage h at node q, respectively; is the continuous discharge time of hydrogen energy storage h.

[0155] S3. Obtain the site selection and layout plan and configuration capacity of each energy storage by solving the joint planning model.

[0156] Specifically, the optimization results can be used to calculate its wind power penetration rate, wind curtailment rate and carbon emission index per kilowatt-hour, which can be expressed as follows using mathematical functions:

[0157]

[0158]

[0159]

[0160] Among them, W PER is the wind power penetration rate; N WIND is the number of wind farms; W CUR is the wind curtailment rate; is the carbon emission per kilowatt-hour; γ is the carbon emission coefficient.

[0161] Example 2

[0162] Compared with the first embodiment, this embodiment provides a specific application example of a method for optimizing the joint planning, site selection, and sizing of multiple adjustable flexibility resources. Specifically:

[0163] Step S1, obtain the wind farm active output time series, load active power time series and related parameters; the wind farm active output and load active power time series are as follows: Figure 4 、 Figure 5 The specific parameters are as follows: the parameters of the generator set are shown in Table 1; the nodes to be selected for energy storage access are all nodes, and their parameters are shown in Table 2; the discount rate η = 8%; the power supply margin coefficient α cur =0.1%; Spinning reserve capacity factor ρ = 5%; Initial power ratio δ = 0.5; Planned hours N T = 672h; Typical planning days N D = 28d; carbon emission coefficient γ = 0.9970kg / (kWh); unit load shedding cost c CUR =10 yuan / (kWh).

[0164] Table 1 Generator set parameters

[0165]

[0166] Table 2 Energy storage parameters

[0167]

[0168] Step S2: Establish a joint planning, site selection and sizing optimization model containing multiple adjustable flexibility resources with the goal of minimizing comprehensive costs.

[0169] Step S3: The optimal capacity configuration and site selection layout of each energy storage are solved by calling the GUROBI method in the YALMIP environment through MATLAB. According to the parameters in step S1 of the embodiment, the calculation results using the model are shown in Table 3. In Table 3, Scheme 1 represents a configuration without flexible adjustable resources; Scheme 2 represents the configuration of electrochemical energy storage, pumped storage, hydrogen energy storage and the load shedding operation of demand-side response. The optimal capacity of each energy storage is obtained as follows: the capacity of electrochemical energy storage is 5.3MW, located at 1 node, the capacity of pumped storage is 22.9MW, located at 1 node, and the hydrogen energy storage capacity is 0. Compared with Scheme 1, the wind power penetration rate is increased by 2.5%, and the comprehensive cost is reduced by 11.56 million yuan.

[0170] Table 3 Optimization results of resource allocation with and without flexibility

[0171]

[0172] Among them, the wind power penetration rate refers to the ratio of the amount of wind power connected to the grid to the load demand. When no energy storage is added, due to the insufficient adjustment flexibility of the generator sets, the system generates a large amount of wind power abandonment, and the proportion of wind power connected to the grid is only 27.1%. When energy storage is added, the energy storage can store the abandoned wind power and transfer it to another time period for release, realizing energy transfer on a time scale, which can increase the amount of wind power connected to the grid and improve the wind power penetration rate of the system.

[0173] Compared to existing technologies, this embodiment has the following beneficial effects: The method of the present invention comprehensively considers the impact of electrochemical energy storage, pumped storage, hydrogen storage, and demand-side response on grid flexibility, analyzes the operating constraints of different energy storage resources, constructs an optimization model for the joint planning of multiple adjustable resources including energy storage, hydrogen storage, pumped storage, and demand response, and calculates and solves the optimal siting and sizing schemes for different energy storage systems. The implementation of this method effectively alleviates the problem of insufficient grid flexibility under high wind power penetration, improves wind power utilization, and reduces the overall investment cost of the grid.

[0174] Example 3

[0175] Please refer to Figure 2 A site selection and sizing optimization terminal 1 for joint planning of adjustable resources includes a memory 2, a processor 3, and a computer program stored on the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, each step of a site selection and sizing optimization method for joint planning of adjustable resources in embodiment one or embodiment two is implemented.

[0176] In summary, the present invention provides a site selection and sizing optimization method and terminal for joint planning of adjustable resources, which takes into account the flexible resource adjustment capabilities of different types of energy storage and demand response, and constructs an adjustable resource joint planning model with the goal of minimizing the comprehensive costs such as the investment and operation and maintenance costs of electrochemical energy storage, pumped storage and hydrogen energy storage, the operating costs of generator sets, and the load shedding costs. A site selection and sizing optimization method for joint planning of multiple adjustable resources under a high proportion of wind power penetration is proposed to obtain the optimal capacity configuration and site selection layout of different energy storage systems, which can effectively alleviate the problem of insufficient flexibility of the power grid under a high proportion of wind power penetration, and reduce the investment cost of the power grid while improving the utilization rate of wind power.

[0177] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A site selection and capacity optimization method for joint planning of adjustable resources, characterized in that: Including steps: Obtain the wind farm active output time series and load active power time series; The objective function is to minimize the comprehensive cost of the power grid. The comprehensive cost includes the investment and operation and maintenance costs of energy storage, the operating costs of the generator sets, and the load shedding costs. The energy storage includes electrochemical energy storage, pumped storage, and hydrogen energy storage: ； Where, Represents the investment and operation and maintenance costs of electrochemical energy storage, pumped storage, and hydrogen energy storage, The operating cost of the power grid includes the power generation cost, start-up and shutdown costs of the generator sets, and the load shedding cost of the system; ； ； Where, , , Represent the investment and operation and maintenance costs of electrochemical energy storage, pumped hydro storage, and hydrogen energy storage respectively; , , Respectively represent the operation and maintenance loss coefficients of electrochemical energy storage, pumped storage, and hydrogen energy storage; represents the discount rate; , , Respectively represent the operating years of electrochemical energy storage, pumped storage, and hydrogen energy storage; Indicates the number of network nodes; , , Respectively represent the amount of electrochemical energy storage, pumped storage, and hydrogen energy storage; Represents the unit capacity cost of electrochemical energy storage; represents the rated capacity of the electrochemical energy storage b at node q; represents the unit power cost of pumped storage; represents the rated power of the pumped storage p at node q; , , They represent the unit power cost of the electrolyzer, the unit power cost of the fuel cell, and the unit capacity cost of the hydrogen storage tank in hydrogen energy storage respectively; , , They represent the rated power of the electrolyzer, the rated power of the fuel cell, and the rated capacity of the hydrogen storage tank in the hydrogen energy storage h at node q respectively; ； Where, Indicates the number of generator sets; , Respectively, they represent the number of planning hours and days; represents the unit power generation cost of generator set n; It represents the active power output of the generator set n at the node q at time t; and They represent the startup cost and shutdown cost of the generator set n at the node q at time t; represents the unit load shedding cost; represents the load shedding amount of node q at time t; Establishing a joint planning model for adjustable resources including multiple types of energy storage, and obtaining constraints of the joint planning model based on the wind farm active output time series and the load active power time series; By solving the joint planning model, the site selection and layout plan as well as the configuration capacity of each type of energy storage are obtained.

2. The method for optimizing the site selection and sizing of adjustable resource joint planning according to claim 1, characterized in that: The constraints of the joint planning model include: maximum installable capacity constraints for energy storage, energy storage site selection and layout constraints, wind power output constraints, system node power balance constraints, power supply margin constraints, line flow constraints, generator set operation constraints, electrochemical energy storage operation constraints, pumped storage operation constraints, and hydrogen energy storage operation constraints.

3. A site selection and sizing optimization terminal for adjustable resource joint planning, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: Obtain the wind farm active output time series and load active power time series; The objective function is to minimize the comprehensive cost of the power grid. The comprehensive cost includes the investment and operation and maintenance costs of energy storage, the operating costs of the generator sets, and the load shedding costs. The energy storage includes electrochemical energy storage, pumped storage, and hydrogen energy storage: ； Where, Represents the investment and operation and maintenance costs of electrochemical energy storage, pumped storage, and hydrogen energy storage, The operating cost of the power grid includes the power generation cost, start-up and shutdown costs of the generator sets, and the load shedding cost of the system; ； ； Where, , , Represent the investment and operation and maintenance costs of electrochemical energy storage, pumped hydro storage, and hydrogen energy storage respectively; , , Respectively represent the operation and maintenance loss coefficients of electrochemical energy storage, pumped storage, and hydrogen energy storage; represents the discount rate; , , Respectively represent the operating years of electrochemical energy storage, pumped storage, and hydrogen energy storage; Indicates the number of network nodes; , , Respectively represent the amount of electrochemical energy storage, pumped storage, and hydrogen energy storage; Represents the unit capacity cost of electrochemical energy storage; represents the rated capacity of the electrochemical energy storage b at node q; represents the unit power cost of pumped storage; represents the rated power of the pumped storage p at node q; , , They represent the unit power cost of the electrolyzer, the unit power cost of the fuel cell, and the unit capacity cost of the hydrogen storage tank in hydrogen energy storage respectively; , , They represent the rated power of the electrolyzer, the rated power of the fuel cell, and the rated capacity of the hydrogen storage tank in the hydrogen energy storage h at node q respectively; ； Where, Indicates the number of generator sets; , Respectively, they represent the number of planning hours and days; represents the unit power generation cost of generator set n; It represents the active power output of the generator set n at the node q at time t; and They represent the startup cost and shutdown cost of the generator set n at the node q at time t; represents the unit load shedding cost; represents the load shedding amount of node q at time t; Establishing a joint planning model for adjustable resources including multiple types of energy storage, and obtaining constraints of the joint planning model based on the wind farm active output time series and the load active power time series; By solving the joint planning model, the site selection and layout plan as well as the configuration capacity of each type of energy storage are obtained.

4. The site selection and capacity optimization terminal for adjustable resource joint planning according to claim 3 is characterized in that: The constraints of the joint planning model include: maximum installable capacity constraints for energy storage, energy storage site selection and layout constraints, wind power output constraints, system node power balance constraints, power supply margin constraints, line flow constraints, generator set operation constraints, electrochemical energy storage operation constraints, pumped storage operation constraints, and hydrogen energy storage operation constraints.

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