Integrated energy microgrid shared energy storage optimization configuration methods, devices, media and products

Abstract

This invention discloses a method, device, medium, and product for optimizing the configuration of shared energy storage in an integrated energy microgrid, relating to the field of energy storage optimization technology. The method includes: determining an integrated energy microgrid; the integrated energy microgrid comprising multiple microgrids and hybrid shared energy storage; establishing a mathematical model of the hybrid shared energy storage in the integrated energy microgrid; establishing a conditional value-at-risk (VAT) model considering the uncertainties of wind and solar power; based on the VAT model, establishing a mathematical model of the integrated energy microgrid's multiple microgrids; using the hybrid shared energy storage mathematical model as the upper-level model and the integrated energy multiple microgrid mathematical model as the lower-level model to obtain a two-layer model; solving the two-layer model to obtain the optimal configuration and charging / discharging strategy of the hybrid shared energy storage, as well as the optimal cost of the integrated energy microgrid. This invention improves energy utilization efficiency.

Description

Technical Field

[0001] This invention relates to the field of energy storage optimization technology, and in particular to a method, device, medium and product for optimizing the configuration of shared energy storage in an integrated energy microgrid. Background Technology

[0002] As building a clean and efficient energy structure becomes the direction of China's energy industry transformation, integrated energy microgrids can realize the cascade utilization of multiple energy sources, improving energy utilization efficiency and playing a significant role in achieving energy structure transformation. Rational configuration of energy storage devices can realize the time-based transfer of energy within integrated energy microgrids, smoothing net load fluctuations and more effectively absorbing new energy sources. However, self-built energy storage devices have high investment costs and low utilization rates, making it difficult to fully realize their value. Combining the sharing economy with energy storage technology can effectively reduce investment costs for energy storage users and improve the utilization rate of energy storage devices.

[0003] Existing technologies determine shared energy storage capacity configuration schemes by considering factors such as day-ahead dispatch and idle energy storage resources at renewable energy power plants. However, these schemes only consider the sharing of electrical energy and do not take into account hybrid energy storage configuration schemes involving the sharing of multiple energy sources within an integrated energy microgrid. Furthermore, they do not consider the impact of uncertain wind and solar power output on shared energy storage capacity configuration. Therefore, this invention proposes a hybrid shared energy storage optimization configuration method that considers the sharing of multiple energy sources and the uncertainty of renewable energy. It establishes a two-layer model that considers hybrid energy storage configuration and optimized operation of integrated energy multi-microgrids. This model maximizes the interests of two different stakeholders while achieving the sharing of multiple energy sources and quantifies the investment risks arising from the uncertainty of wind and solar power. Summary of the Invention

[0004] The purpose of this invention is to provide a method, device, medium, and product for optimizing the configuration of shared energy storage in an integrated energy microgrid, which takes into account the sharing of multiple energy sources and improves energy utilization.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] A method for optimizing the allocation of shared energy storage in an integrated energy microgrid includes:

[0007] Define an integrated energy microgrid; the integrated energy microgrid includes: multiple microgrids and hybrid shared energy storage, the microgrid includes: gas turbines, gas boilers, waste heat boilers, photovoltaic units, wind turbines, absorption chillers, heat exchangers, electric chillers and user-side loads, the user-side loads include: cooling loads, heating loads and electrical loads, the hybrid shared energy storage includes: shared energy storage power stations and shared energy storage heat stations;

[0008] A hybrid shared energy storage mathematical model is established for the integrated energy microgrid. The hybrid shared energy storage mathematical model includes: a first objective function and a first constraint condition. The first objective function is a function that aims to minimize the overall cost of hybrid shared energy storage, with the decision variables being the capacity configuration and maximum charging / discharging power of the energy storage power station and the capacity configuration and maximum charging / discharging heat of the energy storage thermal station. The first constraint condition includes: thermal storage constraint and state of charge and charging / discharging power constraint of the shared energy storage power station.

[0009] A conditional risk value model considering the uncertainties of wind and solar power is established; the conditional risk value model includes: a second objective function and a second constraint; the second objective function is a function with the goal of minimizing the operational risk cost of the integrated energy microgrid, and the decision variable is the VaR value;

[0010] Based on the conditional value-at-risk model, a mathematical model of the integrated energy microgrid is established. This integrated energy microgrid mathematical model includes a third objective function and third constraints. The third objective function aims to minimize the operating cost of the integrated energy microgrid, with decision variables including the output power of the gas turbine, the output power of the gas boiler, the power consumption of the electric chiller, the output power of the absorption chiller, the heat generation power of the heat exchanger, the power purchased from the grid, the energy parameters purchased by the integrated energy microgrid, and the energy parameters sold by the integrated energy microgrid. The energy purchase parameters of the integrated energy multi-microgrid include: the power, heat, power status, and heat status of the electricity purchased from the hybrid shared energy storage; the energy sales parameters of the integrated energy multi-microgrid include: the power, heat, power status, and heat status of the electricity sold to the hybrid shared energy storage; the third constraint includes: power balance constraint, heat power balance constraint, cold power balance constraint, waste heat boiler waste heat balance constraint, energy storage charge and discharge balance constraint, upper and lower limit constraints of microgrid equipment output, power purchase constraint from the grid, and purchase and sale constraints between the microgrid and the hybrid shared energy storage;

[0011] Using the hybrid shared energy storage mathematical model as the upper-level model and the integrated energy multi-microgrid mathematical model as the lower-level model, a two-layer model is obtained;

[0012] Solving the two-layer model yields the optimal configuration and charging / discharging strategy for the hybrid shared energy storage, as well as the optimal cost of the integrated energy microgrid.

[0013] Optionally, the first objective function includes:

[0014]

[0015]

[0016] C op,s =Cses,s -C ses,g -C shs,g +C shs,s -C serve ;

[0017] Among them, C B The construction and maintenance costs of hybrid shared energy storage; S represents the total number of scenarios; π s C represents the probability of scenario s; op,s The operating cost of the integrated energy microgrid in scenario s; C inv,e For the investment, construction, and maintenance costs of shared energy storage power stations; C inv,h The investment, construction, and maintenance costs of shared energy storage thermal stations; The power cost of the shared energy storage power station is expressed in yuan per kilowatt. This represents the maximum charging and discharging power of the shared energy storage power station. The capacity cost of the shared energy storage power station is expressed in yuan per kilowatt-hour. For the maximum capacity of the shared energy storage power station; T s Planned usage period for hybrid shared energy storage; M ses The average daily maintenance cost of shared energy storage power stations; The power cost of shared energy storage thermal stations; This represents the maximum charge and discharge heat capacity of the shared energy storage thermal station. The capacity cost of shared energy storage thermal stations; For the maximum capacity of the shared energy storage thermal station; M shs The average daily maintenance cost of shared energy storage thermal stations; C ses,s For shared energy storage power stations in scenario s, the cost of purchasing electricity from the microgrid; C ses,g C represents the revenue from electricity sales from a shared energy storage power station to a microgrid in scenario s. shs,g For the heat sales revenue from the shared energy storage heat station to the microgrid in scenario s; C shs,s For shared energy storage heat stations in scenario s, the cost of purchasing heat from the microgrid; C serve The service fee cost for microgrids to provide hybrid shared energy storage in scenario s.

[0018] Optionally, the thermal storage constraint includes:

[0019]

[0020] U H,abs (t)+U H,relea (t)≤1;

[0021] E shs (0)≤E shs (T);

[0022]

[0023] Among them, E shs (t) represents the heat stored by the shared energy storage station in time period t; E shs (t-1) represents the heat stored by the shared energy storage station during the (t-1)th time period; η abs,h For the charging efficiency of shared energy storage heat stations; Q shs,abs (t) represents the charging power of the shared energy storage thermal station in time period t; η relea,h For the heat release efficiency of shared energy storage heat stations; Q shs,relea (t) represents the heat release power of the shared energy storage thermal station in time period t; Δt represents the scheduling period; For the maximum capacity of the shared energy storage thermal station; U H,abs (t) represents the charging indicator of the shared energy storage thermal station in time period t; The maximum charge / discharge heat power U of the shared energy storage heat station H,relea (t) represents the heat release indicator of the shared energy storage thermal station in time period t; E shs (0) represents the initial stored heat capacity of the shared energy storage station; E shs (T) represents the heat stored at the end of the cycle by the shared energy storage station;

[0024] The state of charge and charge / discharge power constraints of the shared energy storage power station include:

[0025]

[0026] U abs (t)+U relea (t)≤1;

[0027] E ses (0)≤E ses (T);

[0028]

[0029] Among them, E ses (t) represents the stored energy of the shared energy storage power station in time period t; E ses (t-1) represents the amount of electricity stored by the shared energy storage power station in the (t-1)th time period; η abs For the charging efficiency of shared energy storage power stations; P ses,abs (t) represents the charging power of the shared energy storage power station in time period t; η relea For the discharge efficiency of shared energy storage power stations; P ses,relea (t) represents the discharge power of the shared energy storage power station in time period t; For the maximum capacity of the shared energy storage power station; U abs (t) represents the charging status of the shared energy storage station in time period t; The maximum charging and discharging power of the shared energy storage power station; Urelea (t) represents the discharge flag of the shared energy storage power station in time period t; E ses (0) represents the initial stored energy capacity of the shared energy storage power station; E ses (T) represents the amount of electricity stored by the shared energy storage power station at the end of the cycle.

[0030] Optionally, the second objective function is:

[0031]

[0032] Where CVaR is the integrated energy microgrid operation risk cost; ε is the VaR value; q is the confidence level; S is the total number of scenarios; π s Let be the probability of scenario s; Let be a non-negative auxiliary variable for scenario s.

[0033] Optionally, the second constraint includes:

[0034]

[0035] in, Let C be a non-negative auxiliary variable for scene s; S is the total number of scenes; C op,s ε represents the operating cost of the integrated energy microgrid under scenario s; ε is the VaR value.

[0036] Optionally, the third objective function includes:

[0037] minC wop,s =C grid,g,d +C fuel +C ses,g +C shs,g -C ses,s -C shs,s +C serve +fx·CVaR;

[0038] Among them, C wop,s C represents the total operating cost of the integrated energy microgrid in scenario s; grid,g,d The cost of purchasing electricity from the grid for integrated energy microgrids; C fuel For the fuel cost of integrated energy microgrids; C ses,g C represents the revenue from electricity sales from a shared energy storage power station to a microgrid in scenario s. shs,g For the heat sales revenue from the shared energy storage heat station to the microgrid in scenario s; C ses,s For shared energy storage power stations in scenario s, the cost of purchasing electricity from the microgrid; C shs,s For shared energy storage heat stations in scenario s, the cost of purchasing heat from the microgrid; C serve denoted as , where fx is the service fee cost of the microgrid to hybrid shared energy storage in scenario s; fx is the risk preference coefficient; and CVaR is the operational risk cost of the integrated energy microgrid.

[0039] Optionally, the power balance constraint includes:

[0040] P GT,i (t)+P WT,i (t)+P PV,i (t)+P grid,i (t)+P ses,g,i (t)-P ses,s,i (t)-P EC,i (t)=P load,i (t);

[0041] Among them, P GT,i (t) represents the output power of the gas turbine in the i-th microgrid during time period t; P WT,i (t) represents the output power of the wind turbine in the i-th microgrid during time period t; P PV,i (t) represents the output power of the photovoltaic unit in the i-th microgrid during time period t; P grid,i (t) represents the power purchased by the i-th microgrid from the grid during time period t; P ses,g,i (t) represents the power purchased by the i-th microgrid from the shared energy storage power station in time period t; P ses,s,i (t) represents the power sold by the i-th microgrid to the shared energy storage station during time period t; P EC,i (t) represents the power consumption of the electric chiller in the i-th microgrid during time period t; P load,i (t) represents the electrical load of the i-th microgrid in time period t;

[0042] The thermal power balance constraint includes:

[0043] Q GB,i (t)+P HX,i (t)+Q shs,g,i (t)-Q shs,s,i (t)=P heat,i (t);

[0044] Among them, Q GB,i (t) represents the output power of the gas-fired boiler in the i-th microgrid during time period t; P HX,i (t) represents the output power of the heat exchange device of the i-th microgrid in time period t; Q shs,g,i (t) represents the heat power purchased by the i-th microgrid from the shared energy storage station during time period t; Q shs,s,i (t) represents the heat power sold by the i-th microgrid to the shared energy storage power station in time period t; P heat,i (t) represents the heat load of the i-th microgrid in time period t;

[0045] The cold power balance constraint includes:

[0046] PEC,i (t)η EC +Q AC,i (t)=P cold,i (t);

[0047] Among them, P EC,i (t) represents the output power of the electric chiller of the i-th microgrid in time period t; η EC For electrical cooling efficiency; Q AC,i (t) The output power of the absorption chiller of the i-th microgrid in time period t; P cold,i (t) represents the cooling load of the i-th microgrid in time period t;

[0048] The waste heat balance constraint of the waste heat boiler includes:

[0049]

[0050] Where, η HX For the efficiency of the heat exchanger; η AC For absorption refrigeration efficiency; γ GT η is the gas turbine heat-to-electric ratio; WHB For waste heat boiler efficiency;

[0051] The energy storage charge-discharge balance constraint includes:

[0052]

[0053] Where N is the total number of microgrids; P ses,relea (t) represents the discharge power of the shared energy storage power station in time period t; P ses,abs (t) represents the charging power of the shared energy storage station in time period t; Q shs,relea (t) represents the heat release power of the shared energy storage thermal station in time period t; Q shs,abs (t) represents the charging power of the shared energy storage thermal station in time period t;

[0054] The upper and lower limits of the output of the microgrid equipment include:

[0055]

[0056] in, This represents the minimum output power of the gas turbine. This represents the maximum output power of the gas turbine. This is the minimum output power of the gas-fired boiler; This is the maximum output power of the gas-fired boiler. This is the minimum output power of the heat exchanger; This represents the maximum output power of the heat exchanger. This is the minimum output power of the absorption chiller; This is the maximum output power of the absorption chiller; This is the minimum output power of the electric chiller; This is the maximum output power of the electric chiller;

[0057] The constraints on purchasing electricity from the grid include:

[0058]

[0059] in, This represents the maximum power that the microgrid can purchase from the grid.

[0060] The purchase and sale constraints between the microgrid and the hybrid shared energy storage include:

[0061]

[0062]

[0063] U eg,i (t)+U es,i (t)≤1;

[0064]

[0065] U hg,i (t)+U hs,i (t)≤1;

[0066] in, U represents the maximum interaction power between the microgrid and the shared energy storage power station. eg,i (t) represents the electricity purchase indicator between the i-th microgrid and the shared energy storage power station during time period t; U es,i (t) represents the electricity sales indicator between the i-th microgrid and the shared energy storage power station during time period t; U represents the maximum interaction power between the microgrid and the shared energy storage thermal station. hg,i (t) represents the heat purchase indicator between the i-th microgrid and the shared energy storage heat station during time period t; U hs,i (t) represents the heat sales indicator between the i-th microgrid and the shared energy storage heat station during time period t.

[0067] A computer device includes: 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 integrated energy microgrid shared energy storage optimization configuration method described in any of the preceding claims.

[0068] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the integrated energy microgrid shared energy storage optimization configuration method described in any of the preceding claims.

[0069] A computer program product includes a computer program that, when executed by a processor, implements the integrated energy microgrid shared energy storage optimization configuration method described in any of the preceding claims.

[0070] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0071] This invention discloses a method, device, medium, and product for optimizing the configuration of shared energy storage in a comprehensive energy microgrid. It not only considers the sharing of multiple energy sources and improves energy utilization, but also takes into account the impact of the uncertainty of wind and solar power output on system operating costs, providing a reference for investors to configure the capacity of hybrid shared energy storage under different risk aversion levels. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0073] Figure 1 This is a schematic diagram of the integrated energy microgrid shared energy storage optimization configuration method provided in Embodiment 1 of the present invention;

[0074] Figure 2 A schematic diagram of the process for optimizing the allocation of shared energy storage in a comprehensive energy microgrid that takes into account conditional risk value. Detailed Implementation

[0075] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0076] The purpose of this invention is to provide a method, device, medium, and product for optimizing the configuration of shared energy storage in an integrated energy microgrid, aiming to improve energy utilization.

[0077] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0078] Example 1

[0079] like Figure 1 and Figure 2 As shown, the integrated energy microgrid shared energy storage optimization configuration method in this embodiment includes:

[0080] Step 101: Determine the integrated energy microgrid.

[0081] The integrated energy microgrid includes multiple microgrids and hybrid shared energy storage. The microgrids include gas turbines, gas boilers, waste heat boilers, photovoltaic units, wind turbines, absorption chillers, heat exchangers, electric chillers, and user-side loads. User-side loads include cooling loads, heating loads, and electrical loads. Hybrid shared energy storage includes shared energy storage power stations and shared energy storage heat stations.

[0082] Step 102: Establish a mathematical model for hybrid shared energy storage in an integrated energy microgrid.

[0083] The hybrid shared energy storage mathematical model includes: a first objective function and a first constraint condition; the first objective function is a function of the capacity configuration and maximum charging and discharging power of the energy storage power station and the capacity configuration and maximum charging and discharging heat of the energy storage thermal station, with the goal of minimizing the overall cost of hybrid shared energy storage; the first constraint condition includes: thermal storage constraint and state of charge and charging and discharging power constraint of the shared energy storage power station.

[0084] As an optional implementation, the first objective function includes:

[0085]

[0086] C op,s =C ses,s -C ses,g -C shs,g +C shs,s -C serve

[0087] Among them, C B The construction and maintenance costs of hybrid shared energy storage; S represents the total number of scenarios; π s C represents the probability of scenario s; op,s The operating cost of the integrated energy microgrid in scenario s; C inv,e For the investment, construction, and maintenance costs of shared energy storage power stations; C inv,h The investment, construction, and maintenance costs of shared energy storage thermal stations; The power cost of the shared energy storage power station is expressed in yuan per kilowatt. This represents the maximum charging and discharging power of the shared energy storage power station. The capacity cost of the shared energy storage power station is expressed in yuan per kilowatt-hour. For the maximum capacity of the shared energy storage power station; T s Planned usage period for hybrid shared energy storage; M ses The average daily maintenance cost of shared energy storage power stations; The power cost of shared energy storage thermal stations; This represents the maximum charge and discharge heat capacity of the shared energy storage thermal station. The capacity cost of shared energy storage thermal stations; For the maximum capacity of the shared energy storage thermal station; M shs The average daily maintenance cost of shared energy storage thermal stations; C ses,s For shared energy storage power stations in scenario s, the cost of purchasing electricity from the microgrid; C ses,g C represents the revenue from electricity sales from a shared energy storage power station to a microgrid in scenario s. shs,g For the heat sales revenue from the shared energy storage heat station to the microgrid in scenario s; C shs,s For shared energy storage heat stations in scenario s, the cost of purchasing heat from the microgrid; C serve The service fee cost for microgrids to provide hybrid shared energy storage in scenario s.

[0088] Specifically, the formulas for calculating various costs are as follows:

[0089]

[0090] Where N is the total number of microgrids; T is the end of the cycle; μ ses (t) represents the electricity price sold by the microgrid to the shared energy storage power station during time period t; P ses,s,i (t) represents the electricity sold by the i-th microgrid to the shared energy storage station in time period t; λ ses (t) represents the electricity purchase price of the microgrid from the shared energy storage power station in time period t; P ses,g,i (t) represents the power purchased by the i-th microgrid from the shared energy storage station during time period t; λ shs (t) represents the heat purchase price of the microgrid from the shared energy storage station during time period t; Q shs,g,i (t) represents the heat power purchased by the i-th microgrid from the shared energy storage station during time period t; μ shs (t) represents the heat price paid by the microgrid to the shared energy storage heat station during time period t; Q shs,s,i (t) represents the heat power sold by the i-th microgrid to the shared energy storage power station in time period t; c ses c is the unit price of the service fee paid by the microgrid to the shared energy storage power station; shs This refers to the unit price of the service fee paid by the microgrid to the shared energy storage thermal station.

[0091] As an optional implementation, thermal storage confinement includes:

[0092]

[0093] U H,abs (t)+U H,relea (t)≤1

[0094] E shs (0)≤E shs(T)

[0095]

[0096] Among them, E shs (t) represents the heat stored by the shared energy storage station in time period t; E shs (t-1) represents the heat stored by the shared energy storage station during the (t-1)th time period; η abs,h For the charging efficiency of shared energy storage heat stations; Q shs,abs (t) represents the charging power of the shared energy storage thermal station in time period t; η relea,h For the heat release efficiency of shared energy storage heat stations; Q shs,relea (t) represents the heat release power of the shared energy storage thermal station in time period t; Δt represents the scheduling period; For the maximum capacity of the shared energy storage thermal station; U H,abs (t) represents the charging indicator of the shared energy storage thermal station in time period t; The maximum charge / discharge heat power U of the shared energy storage heat station H,relea (t) represents the heat release indicator of the shared energy storage thermal station in time period t; E shs (0) represents the initial stored heat capacity of the shared energy storage station; E shs (T) represents the stored heat at the end of the cycle of the shared energy storage station.

[0097] State of charge and charge / discharge power constraints for shared energy storage power stations include:

[0098]

[0099] U abs (t)+U relea (t)≤1

[0100] E ses (0)≤E ses (T)

[0101]

[0102] Among them, E ses (t) represents the stored energy of the shared energy storage power station in time period t; E ses (t-1) represents the amount of electricity stored by the shared energy storage power station in the (t-1)th time period; η abs For the charging efficiency of shared energy storage power stations; P ses,abs (t) represents the charging power of the shared energy storage power station in time period t; η relea For the discharge efficiency of shared energy storage power stations; P ses,relea (t) represents the discharge power of the shared energy storage power station in time period t; For the maximum capacity of the shared energy storage power station; U abs(t) represents the charging status of the shared energy storage station in time period t; The maximum charging and discharging power of the shared energy storage power station; U relea (t) represents the discharge flag of the shared energy storage power station in time period t; E ses (0) represents the initial stored energy capacity of the shared energy storage power station; E ses (T) represents the amount of electricity stored by the shared energy storage power station at the end of the cycle.

[0103] Step 103: Establish a conditional value-at-risk model that takes into account the uncertainties of wind and solar power.

[0104] The conditional value at risk model includes a second objective function and a second constraint. The second objective function is a function that aims to minimize the risk cost of integrated energy microgrid operation, with VaR values ​​as the decision variable.

[0105] Specifically, the output of renewable energy in the actual operation of microgrids will fluctuate significantly. In the model that considers hybrid shared energy storage, the error caused by this fluctuation will affect the electricity and heat transaction volume between the microgrid and the hybrid shared energy storage, thus making the operating cost of the system uncertain. In order to quantify the uncertainty that may be caused by the prediction error of renewable energy, this method introduces Conditional Value at Risk (CVaR) to quantitatively assess the uncertainty.

[0106] Latin hypercube sampling was used to process wind and forecast data, generating 1000 data sets. These were then reduced to five representative scenarios using k-means clustering, and the probability of each scenario was calculated. With a confidence level of q, the value corresponding to the quantile of the operating cost probability distribution at 1-q was used as the VaR value of the system operating cost, ensuring that the probability of the system operating cost exceeding VaR is less than 1-q. The objective function for optimizing the system operating cost CvaR is then the second objective function.

[0107] As an optional implementation, the second objective function is:

[0108]

[0109] Wherein, CVaR is the risk cost of operating a comprehensive energy microgrid; ε is the VaR value, representing the VaR value at which the expected operating cost of the comprehensive energy microgrid is optimal; q is the confidence level; S is the total number of scenarios; π s Let be the probability of scenario s; is a non-negative auxiliary variable for scenario s, representing the amount by which the total operating cost of the integrated energy microgrid exceeds the VaR value under scenario s.

[0110] As an optional implementation, the second constraint includes:

[0111]

[0112] in, Let C be a non-negative auxiliary variable for scene s; S is the total number of scenes; C op,s ε represents the operating cost of the integrated energy microgrid under scenario s; ε is the VaR value.

[0113] Step 104: Based on the conditional value at risk model, establish a mathematical model of integrated energy microgrids for multi-microgrid integrated energy microgrids.

[0114] The integrated energy microgrid mathematical model includes a third objective function and third constraints. The third objective function aims to minimize the operating cost of the integrated energy microgrid, with decision variables including the output power of the gas turbine, the output power of the gas boiler, the power consumption of the electric chiller, the output power of the absorption chiller, the heat generation power of the heat exchanger, the power purchased from the grid, the energy parameters purchased by the integrated energy microgrid, and the energy parameters sold by the integrated energy microgrid. The energy parameters purchased by the integrated energy microgrid include the power purchased from the hybrid shared energy storage, the heat purchased, the power purchase status, and the heat purchase status. The energy parameters sold by the integrated energy microgrid include the power sold to the hybrid shared energy storage, the heat sold, the power sold status, and the heat sold status. The third constraints include: power balance constraints, thermal power balance constraints, cold power balance constraints, waste heat boiler waste heat balance constraints, energy storage charge and discharge balance constraints, upper and lower limits of microgrid equipment output constraints, grid power purchase constraints, and purchase and sale constraints between the microgrid and the hybrid shared energy storage.

[0115] As an optional implementation, the third objective function includes:

[0116] minC wop,s =C grid,g,d +C fuel +C ses,g +C shs,g -C ses,s -C shs,s +C serve +fx·CVaR

[0117] Among them, C wop,s C represents the total operating cost of the integrated energy microgrid in scenario s; grid,g,d The cost of purchasing electricity from the grid for integrated energy microgrids; C fuel For the fuel cost of integrated energy microgrids; C ses,g C represents the revenue from electricity sales from a shared energy storage power station to a microgrid in scenario s. shs,g For the heat sales revenue from the shared energy storage heat station to the microgrid in scenario s; C ses,s For shared energy storage power stations in scenario s, the cost of purchasing electricity from the microgrid; Cshs,s For shared energy storage heat stations in scenario s, the cost of purchasing heat from the microgrid; C serve denoted as , where is the service fee cost of the microgrid to hybrid shared energy storage under scenario s; fx is the risk preference coefficient, representing the investor's attitude towards risk. When fx ≥ 0, a smaller fx indicates that the investor is more aggressive, prefers risk, and hopes to exchange greater risk for higher returns; when fx is larger, a larger fx indicates that the investor is more conservative, averse to risk, and hopes to adopt a more conservative strategy; when fx = 0, the investor has a neutral attitude towards risk and does not consider risk control; CVaR is the integrated energy microgrid operation risk cost.

[0118] Specifically, the formulas for calculating each cost include:

[0119]

[0120] Where δ(t) is the grid electricity price in time period t; P grid,i (t) represents the power purchased by the i-th microgrid from the grid during time period t; c gas P represents the price per unit volume of natural gas. GT,i (t) represents the output power of the gas turbine in the i-th microgrid during time period t; η GT For gas turbine power generation efficiency; L NG The calorific value of the gas is taken as 9.7 kWh / m³. 3 Q GB,i (t) represents the output power of the gas-fired boiler in the i-th microgrid during time period t; η GB For the efficiency of gas-fired boilers.

[0121] As an optional implementation method, power balance constraints include:

[0122] P GT,i (t)+P WT,i (t)+P PV,i (t)+P grid,i (t)+P ses,g,i (t)-P ses,s,i (t)-P EC,i (t)=P load,i (t)

[0123] Among them, P GT,i (t) represents the output power of the gas turbine in the i-th microgrid during time period t; P WT,i (t) represents the output power of the wind turbine in the i-th microgrid during time period t; P PV,i (t) represents the output power of the photovoltaic unit in the i-th microgrid during time period t; P grid,i (t) represents the power purchased by the i-th microgrid from the grid during time period t; P ses,g,i(t) represents the power purchased by the i-th microgrid from the shared energy storage power station in time period t; P ses,s,i (t) represents the power sold by the i-th microgrid to the shared energy storage station during time period t; P EC,i (t) represents the power consumption of the electric chiller in the i-th microgrid during time period t. load,i (t) represents the electrical load of the i-th microgrid in time period t.

[0124] Thermal power balance constraints include:

[0125] Q GB,i (t)+P HX,i (t)+Q shs,g,i (t)-Q shs,s,i (t)=P heat,i (t)

[0126] Among them, Q GB,i (t) represents the output power of the gas-fired boiler in the i-th microgrid during time period t; P HX,i (t) represents the output power of the heat exchange device of the i-th microgrid in time period t; Q shs,g,i (t) represents the heat power purchased by the i-th microgrid from the shared energy storage station during time period t; Q shs,s,i (t) represents the heat power sold by the i-th microgrid to the shared energy storage power station in time period t; P heat,i (t) represents the heat load of the i-th microgrid during time period t.

[0127] Cold power balance constraints include:

[0128] P EC,i (t)η EC +Q AC,i (t)=P cold,i (t)

[0129] Among them, P EC,i (t) represents the output power of the electric chiller of the i-th microgrid in time period t; η EC For electrical cooling efficiency; Q AC,i (t) The output power of the absorption chiller of the i-th microgrid in time period t; P cold,i (t) represents the cold load of the i-th microgrid in time period t.

[0130] Waste heat balance constraints for waste heat boilers include:

[0131]

[0132] Where, η HX For the efficiency of the heat exchanger; η AC For absorption refrigeration efficiency; γ GT η is the gas turbine heat-to-electric ratio;WHB This refers to the efficiency of the waste heat boiler.

[0133] Energy storage charge-discharge balance constraints include:

[0134]

[0135] Where N is the total number of microgrids; P ses,relea (t) represents the discharge power of the shared energy storage power station in time period t; P ses,abs (t) represents the charging power of the shared energy storage station in time period t; Q shs,relea (t) represents the heat release power of the shared energy storage thermal station in time period t; Q shs,abs (t) represents the charging power of the shared energy storage thermal station during time period t.

[0136] Microgrid equipment output upper and lower limit constraints include:

[0137]

[0138] in, This represents the minimum output power of the gas turbine. This represents the maximum output power of the gas turbine. This is the minimum output power of the gas-fired boiler; This is the maximum output power of the gas-fired boiler. This is the minimum output power of the heat exchanger; This represents the maximum output power of the heat exchanger. This is the minimum output power of the absorption chiller; This is the maximum output power of the absorption chiller; This is the minimum output power of the electric chiller; This is the maximum output power of the electric chiller.

[0139] Constraints on purchasing electricity from the grid include:

[0140]

[0141] in, This represents the maximum power that the microgrid can purchase from the grid.

[0142] Purchase and sale constraints between microgrids and hybrid shared energy storage include:

[0143]

[0144] U eg,i (t)+U es,i (t)≤1

[0145]

[0146] Uhg,i (t)+U hs,i (t)≤1

[0147] in, U represents the maximum interaction power between the microgrid and the shared energy storage power station. eg,i (t) represents the electricity purchase indicator between the i-th microgrid and the shared energy storage power station during time period t; U es,i (t) represents the electricity sales indicator between the i-th microgrid and the shared energy storage power station during time period t; U represents the maximum interaction power between the microgrid and the shared energy storage thermal station. hg,i (t) represents the heat purchase indicator between the i-th microgrid and the shared energy storage heat station during time period t; U hs,i (t) represents the heat sales indicator between the i-th microgrid and the shared energy storage heat station during time period t.

[0148] Step 105: Using the hybrid shared energy storage mathematical model as the upper-level model and the integrated energy multi-microgrid mathematical model as the lower-level model, a two-layer model is obtained.

[0149] Step 106: Solve the two-layer model to obtain the optimal configuration and charging / discharging strategy of the hybrid shared energy storage, as well as the optimal cost of the integrated energy microgrid.

[0150] Specifically, the constraints of the integrated energy multi-microgrid mathematical model are transformed into a hybrid shared energy storage mathematical model using the KKT and Big-M methods. The two-layer model is then solved using the gurobi solver in the Yalmip toolbox of MATLAB software to obtain the optimal configuration and charging / discharging strategy of the hybrid shared energy storage, as well as the optimal cost of the integrated energy multi-microgrid mathematical model.

[0151] Example 2

[0152] A computer device includes: 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 integrated energy microgrid shared energy storage optimization configuration method in Embodiment 1.

[0153] Example 3

[0154] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the integrated energy microgrid shared energy storage optimization configuration method of Embodiment 1.

[0155] Example 4

[0156] A computer program product includes a computer program that, when executed by a processor, implements the integrated energy microgrid shared energy storage optimization configuration method in Embodiment 1.

[0157] Example 5

[0158] A computer device, which may be a database, includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The database stores pending transactions. The I / O interfaces facilitate information exchange between the processor and external devices. The communication interface enables communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the integrated energy microgrid shared energy storage optimization configuration method of Embodiment 1.

[0159] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this invention are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0160] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided by this invention 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 can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided by this invention may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided by this invention may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0161] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0162] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for optimizing the allocation of shared energy storage in an integrated energy microgrid, characterized in that, The method includes: Define an integrated energy microgrid; the integrated energy microgrid includes: multiple microgrids and hybrid shared energy storage, the microgrid includes: gas turbines, gas boilers, waste heat boilers, photovoltaic units, wind turbines, absorption chillers, heat exchangers, electric chillers and user-side loads, the user-side loads include: cooling loads, heating loads and electrical loads, the hybrid shared energy storage includes: shared energy storage power stations and shared energy storage heat stations; A hybrid shared energy storage mathematical model is established for the integrated energy microgrid. The hybrid shared energy storage mathematical model includes: a first objective function and a first constraint condition. The first objective function is a function that aims to minimize the overall cost of hybrid shared energy storage, with the decision variables being the capacity configuration and maximum charging / discharging power of the energy storage power station and the capacity configuration and maximum charging / discharging heat of the energy storage thermal station. The first constraint condition includes: thermal storage constraint and state of charge and charging / discharging power constraint of the shared energy storage power station. A conditional risk value model considering the uncertainties of wind and solar power is established; the conditional risk value model includes: a second objective function and a second constraint; the second objective function is a function with the goal of minimizing the operational risk cost of the integrated energy microgrid, and the decision variable is the VaR value; Based on the conditional value-at-risk model, a mathematical model of the integrated energy microgrid is established. This integrated energy microgrid mathematical model includes a third objective function and third constraints. The third objective function aims to minimize the operating cost of the integrated energy microgrid, with decision variables including the output power of the gas turbine, the output power of the gas boiler, the power consumption of the electric chiller, the output power of the absorption chiller, the heat generation power of the heat exchanger, the power purchased from the grid, the energy parameters purchased by the integrated energy microgrid, and the energy parameters sold by the integrated energy microgrid. The energy purchase parameters of the integrated energy multi-microgrid include: the power, heat, power status, and heat status of the electricity purchased from the hybrid shared energy storage; the energy sales parameters of the integrated energy multi-microgrid include: the power, heat, power status, and heat status of the electricity sold to the hybrid shared energy storage; the third constraint includes: power balance constraint, heat power balance constraint, cold power balance constraint, waste heat boiler waste heat balance constraint, energy storage charge and discharge balance constraint, upper and lower limit constraints of microgrid equipment output, power purchase constraint from the grid, and purchase and sale constraints between the microgrid and the hybrid shared energy storage; Using the hybrid shared energy storage mathematical model as the upper-level model and the integrated energy multi-microgrid mathematical model as the lower-level model, a two-layer model is obtained; Solving the two-layer model yields the optimal configuration and charging / discharging strategy for the hybrid shared energy storage, as well as the optimal cost of the integrated energy microgrid. The second objective function is: Where CVaR is the integrated energy microgrid operation risk cost; ε is the VaR value; q is the confidence level; S is the total number of scenarios; π s Let be the probability of scenario s; Let be a non-negative auxiliary variable for scenario s; The second constraint includes: in, Let C be a non-negative auxiliary variable for scene s; S is the total number of scenes; C op,s ε represents the operating cost of the integrated energy microgrid under scenario s; ε is the VaR value.

2. The method for optimized configuration of shared energy storage in a comprehensive energy microgrid according to claim 1, characterized in that, The first objective function includes: C op,s =C ses,s -C ses,g -C shs,g +C shs,s -C serve ; Among them, C B The construction and maintenance costs of hybrid shared energy storage; S represents the total number of scenarios; π s C represents the probability of scenario s; op,s The operating cost of the integrated energy microgrid in scenario s; C inv,e For the investment, construction, and maintenance costs of shared energy storage power stations; C inv,h The investment, construction, and maintenance costs of shared energy storage thermal stations; The power cost of the shared energy storage power station is expressed in yuan per kilowatt. This represents the maximum charging and discharging power of the shared energy storage power station. The capacity cost of the shared energy storage power station is expressed in yuan per kilowatt-hour. The maximum capacity of the shared energy storage power station; T s Planned usage period for hybrid shared energy storage; M ses The average daily maintenance cost of shared energy storage power stations; The power cost of shared energy storage thermal stations; This represents the maximum charge and discharge heat capacity of the shared energy storage thermal station. The capacity cost of shared energy storage thermal stations; For the maximum capacity of the shared energy storage thermal station; M shs The average daily maintenance cost of shared energy storage thermal stations; C ses,s For shared energy storage power stations in scenario s, the cost of purchasing electricity from the microgrid; C ses,g C represents the revenue from electricity sales from a shared energy storage power station to a microgrid in scenario s. shs,g For the heat sales revenue from the shared energy storage heat station to the microgrid in scenario s; C shs,s For shared energy storage heat stations in scenario s, the cost of purchasing heat from the microgrid; C serve The service fee cost for microgrids to provide hybrid shared energy storage in scenario s.

3. The method for optimized configuration of shared energy storage in a comprehensive energy microgrid according to claim 1, characterized in that, The thermal storage constraint includes: U H,abs (t)+U H,relea (t)≤1; E shs (0)≤E shs (T); Among them, E shs (t) represents the heat stored by the shared energy storage station in time period t; E shs (t-1) represents the heat stored by the shared energy storage station during the (t-1)th time period; η abs,h For the charging efficiency of shared energy storage heat stations; Q shs,abs (t) represents the charging power of the shared energy storage thermal station in time period t; η relea,h For the heat release efficiency of shared energy storage heat stations; Q shs,relea (t) represents the heat release power of the shared energy storage thermal station in time period t; Δt represents the scheduling period; For the maximum capacity of the shared energy storage thermal station; U H,abs (t) represents the charging indicator of the shared energy storage thermal station in time period t; The maximum charge / discharge heat power U of the shared energy storage heat station H,relea (t) represents the heat release indicator of the shared energy storage thermal station in time period t; E shs (0) represents the initial stored heat capacity of the shared energy storage station; E shs (T) represents the heat stored at the end of the cycle by the shared energy storage station; The state of charge and charge / discharge power constraints of the shared energy storage power station include: U abs (t)+U relea (t)≤1; E ses (0)≤E ses (T); Among them, E ses (t) represents the stored energy of the shared energy storage power station in time period t; E ses (t-1) represents the amount of electricity stored by the shared energy storage power station in the (t-1)th time period; η abs For the charging efficiency of shared energy storage power stations; P ses,abs (t) represents the charging power of the shared energy storage power station in time period t; η relea For the discharge efficiency of shared energy storage power stations; P ses,relea (t) represents the discharge power of the shared energy storage power station in time period t; For the maximum capacity of the shared energy storage power station; U abs (t) represents the charging status of the shared energy storage station in time period t; The maximum charging and discharging power of the shared energy storage power station; U relea (t) represents the discharge flag of the shared energy storage power station in time period t; E ses (0) represents the initial stored energy capacity of the shared energy storage power station; E ses (T) represents the amount of electricity stored by the shared energy storage power station at the end of the cycle.

4. The method for optimized configuration of shared energy storage in a comprehensive energy microgrid according to claim 1, characterized in that, The third objective function includes: minC wop,s =C grid,g,d +C fuel +C ses,g +C shs,g -C ses,s -C shs,s +C serve +fx·CVaR; Among them, C wop,s C represents the total operating cost of the integrated energy microgrid in scenario s; grid,g,d The cost of purchasing electricity from the grid for integrated energy microgrids; C fuel For the fuel cost of integrated energy microgrids; C ses,g C represents the revenue from electricity sales from a shared energy storage power station to a microgrid in scenario s. shs,g For the heat sales revenue from the shared energy storage heat station to the microgrid in scenario s; C ses,s For shared energy storage power stations in scenario s, the cost of purchasing electricity from the microgrid; C shs,s For shared energy storage heat stations in scenario s, the cost of purchasing heat from the microgrid; C serve denoted as , where fx is the service fee cost of the microgrid to hybrid shared energy storage in scenario s; fx is the risk preference coefficient; and CVaR is the operational risk cost of the integrated energy microgrid.

5. The method for optimized configuration of shared energy storage in a comprehensive energy microgrid according to claim 1, characterized in that, The power balance constraints include: P GT,i (t)+P WT,i (t)+P PV,i (t)+P grid,i (t)+P ses,g,i (t)-P ses,s,i (t)-P EC,i (t)=P load,i (t); Among them, P GT,i (t) represents the output power of the gas turbine in the i-th microgrid during time period t; P WT,i (t) represents the output power of the wind turbine in the i-th microgrid during time period t; P PV,i (t) represents the output power of the photovoltaic unit in the i-th microgrid during time period t; P grid,i (t) represents the power purchased by the i-th microgrid from the grid during time period t; P ses,g,i (t) represents the power purchased by the i-th microgrid from the shared energy storage power station in time period t; P ses,s,i (t) represents the power sold by the i-th microgrid to the shared energy storage station during time period t; P EC,i (t) represents the power consumption of the electric chiller in the i-th microgrid during time period t; P load,i (t) represents the electrical load of the i-th microgrid in time period t; The thermal power balance constraint includes: Q GB,i (t)+P HX,i (t)+Q shs,g,i (t)-Q shs,s,i (t)=P heat,i (t); Among them, Q GB,i (t) represents the output power of the gas-fired boiler in the i-th microgrid during time period t; P HX,i (t) represents the output power of the heat exchange device of the i-th microgrid in time period t; Q shs,g,i (t) represents the heat power purchased by the i-th microgrid from the shared energy storage station during time period t; Q shs,s,i (t) represents the heat power sold by the i-th microgrid to the shared energy storage power station in time period t; P heat,i (t) represents the heat load of the i-th microgrid in time period t; The cold power balance constraint includes: P EC,i (t)η EC +Q AC,i (t)=P cold,i (t); Among them, P EC,i (t) represents the output power of the electric chiller of the i-th microgrid in time period t; η EC For electrical cooling efficiency; Q AC,i (t) The output power of the absorption chiller of the i-th microgrid in time period t; P cold,i (t) represents the cooling load of the i-th microgrid in time period t; The waste heat balance constraint of the waste heat boiler includes: Where, η HX For the efficiency of the heat exchanger; η AC For absorption refrigeration efficiency; γ GT η is the gas turbine heat-to-electric ratio; WHB For waste heat boiler efficiency; The energy storage charge-discharge balance constraint includes: Where N is the total number of microgrids; P ses,relea (t) represents the discharge power of the shared energy storage power station in time period t; P ses,abs (t) represents the charging power of the shared energy storage station in time period t; Q shs,relea (t) represents the heat release power of the shared energy storage thermal station in time period t; Q shs,abs (t) represents the charging power of the shared energy storage thermal station in time period t; The upper and lower limits of the output of the microgrid equipment include: in, This represents the minimum output power of the gas turbine. This represents the maximum output power of the gas turbine. This is the minimum output power of the gas-fired boiler; This is the maximum output power of the gas-fired boiler. This represents the minimum output power of the heat exchanger. This is the maximum output power of the heat exchanger. This is the minimum output power of the absorption chiller; This is the maximum output power of the absorption chiller; This is the minimum output power of the electric chiller; This is the maximum output power of the electric chiller; The constraints on purchasing electricity from the grid include: in, This represents the maximum power that the microgrid can purchase from the grid. The purchase and sale constraints between the microgrid and the hybrid shared energy storage include: U eg,i (t)+U es,i (t)≤1; U hg,i (t)+U hs,i (t)≤1; in, U represents the maximum interaction power between the microgrid and the shared energy storage power station. eg,i (t) represents the electricity purchase indicator between the i-th microgrid and the shared energy storage power station during time period t; U es,i (t) represents the electricity sales indicator between the i-th microgrid and the shared energy storage power station during time period t; U represents the maximum interaction power between the microgrid and the shared energy storage thermal station. hg,i (t) represents the heat purchase indicator between the i-th microgrid and the shared energy storage heat station during time period t; U hs,i (t) represents the heat sales indicator between the i-th microgrid and the shared energy storage heat station during time period t.

6. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the integrated energy microgrid shared energy storage optimization configuration method according to any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the integrated energy microgrid shared energy storage optimization configuration method as described in any one of claims 1-5.

8. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the integrated energy microgrid shared energy storage optimization configuration method as described in any one of claims 1-5.

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