A method for optimizing configuration of electricity-heat sharing energy storage for multi-cchp microgrid

Abstract

The invention is to solve the problems of increasing investment cost of energy storage and mismatch between supply and demand of multi-cogeneration microgrid, and proposes a double-layer optimization configuration method of electricity-heat sharing energy storage for multi-cogeneration microgrid. Firstly, a new business model of electricity-heat sharing energy storage station is proposed, and the service mode, operation strategy and profit mechanism of the electricity-heat sharing energy storage station are analyzed. Secondly, a multi-objective double-layer programming model is established, which aims to minimize the operation cost of the electricity-heat sharing energy storage station and optimize the economy of the multi-cogeneration microgrid. Thirdly, the model is transformed and solved by using Karush-Kuhn-Tucker method. Finally, the example verification shows that the proposed electricity-heat sharing energy storage operation mode has significant advantages in reducing cost and improving economy, and the effectiveness of the proposed method in practical application is verified. The results show that the method proposed in the invention improves the utilization efficiency of energy storage resources, reduces redundant investment, and especially in the case of inconsistent demand period of electricity and heat, realizes flexible conversion and efficient scheduling between different energy forms.

Description

Technical Field

[0001] This invention relates to the field of two-layer optimized configuration of shared energy storage, and particularly to a two-layer optimized configuration method for shared electric-thermal energy storage in multi-CCHP microgrids. Background Technology

[0002] With the increasing depletion of global fossil fuels and the worsening of environmental pollution, improving energy efficiency and reducing greenhouse gas emissions have received widespread attention. The Paris Agreement set global temperature control targets to reduce excessive carbon dioxide emissions. China also pledged at the global climate summit to achieve its "dual carbon" targets. Natural gas-based combined cooling, heating, and power microgrids (CCHPMs) offer a promising approach to improving energy efficiency and achieving carbon neutrality. Based on the principle of energy cascade utilization, CCHPMs can simultaneously provide users with cooling, heating, and electricity services, thereby improving energy efficiency and reducing carbon dioxide emissions.

[0003] However, the diversity and irregularity of user load demands, along with the uncertainties associated with renewable energy, pose significant challenges to the planning and operation of CCHPMs. To address these issues, energy storage systems (ESS) offer effective solutions and methods. Current research analyzes the performance of energy storage devices and CCHPMs from various perspectives, including energy storage selection, capacity optimization, and profitability strategies. However, ESS research primarily focuses on scenarios where each CCHPM is equipped with its own storage, which limits the full utilization of ESS energy. To reduce investment costs and improve energy efficiency, building shared energy storage (SES) stations is an effective approach. Multiple users can charge and release energy according to their respective load conditions, effectively resolving the aforementioned issues. Currently, electricity sharing is the primary focus, while thermal energy sharing is neglected. Furthermore, research on the performance of multiple CCHPMs shows that their interactive operation can leverage the spatiotemporal complementarity of loads to improve the performance of regional integrated energy systems. Therefore, in energy systems containing multiple CCHPMs, shared electricity storage and shared thermal energy storage need to be considered simultaneously.

[0004] In the research on the optimal configuration of CCHPM and hybrid electric-thermal energy storage systems, the key lies in improving the efficiency of multi-energy integration and conversion, accurately predicting load demand and designing effective demand response strategies, and selecting appropriate energy storage technologies and optimizing their charging and discharging management. The challenges lie in achieving multi-objective optimization, handling uncertainties such as energy prices and user demand, and ensuring the compatibility and collaborative operation of various technologies and equipment within the system. Summary of the Invention

[0005] To address the aforementioned issues, a two-tiered optimization configuration method for shared electricity-heat energy storage in multi-generational cogeneration microgrids is proposed. First, a novel business model for shared electricity-heat energy storage stations is introduced, and their service models, operational strategies, and profit mechanisms are analyzed. Second, a multi-objective two-tiered programming model is established to achieve both the lowest operating cost of shared electricity-heat energy storage stations and the optimal economic efficiency of multi-generational cogeneration microgrids. Third, the Karush-Kuhn-Tucker method is used to transform and solve the model. Finally, numerical examples demonstrate that the proposed shared electricity-heat energy storage operation model exhibits significant advantages in cost reduction and improved economic efficiency, validating the effectiveness of the proposed method in practical applications.

[0006] The results show that the method proposed in this invention improves the utilization efficiency of energy storage resources and reduces redundant investment. In particular, it enables flexible conversion and efficient scheduling between different energy forms when the demand for electricity and heat is inconsistent.

[0007] It consists of the following steps:

[0008] S1 ET-SES station service model

[0009] The high investment cost and long payback period of on-load energy storage have limited its widespread use. Based on this, the ET-SES service model is proposed, such as... Figure 1 As shown. This service model involves ET-SES operators investing in and constructing large-scale energy storage stations at selected sites among users of combined cooling, heating, and power microgrids (CCHPM), providing users with more economical shared energy services. The operators are responsible for the operation and management of the energy storage stations and charge users a service fee. This service fee is defined (taking electricity sharing as an example): the fee paid by the user for each unit of power of electricity used for charging and discharging at the ET-SES station; the same applies to heat sharing.

[0010] The CCHPM (Centralized Heat and Power Plant) incorporates three types of loads: cooling load, heating load, and electrical load. Its main equipment includes: micro gas turbines (MT), gas boilers (GB), electric boilers (EB), electric chillers (EC), absorption chillers (AC), heat exchangers (HER), waste heat recovery boilers (WB), and a renewable energy power plant. The output of the micro gas turbines and the electricity purchased from the renewable energy power plant can meet the electrical load of most users. If a user's electrical load exceeds the supply, electricity can be purchased from the ET-SES (Electric Heat and Power Supply) station. If the user's electrical load is less than the supply, the electricity can be used to drive the electric boilers to provide part of the user's heating load, and the remaining electricity can be sold back to the ET-SES station. The electric boilers, gas boilers, and waste heat recovery boilers can meet the heating load of most users. The heat emitted by the micro gas turbines is recovered through the waste heat recovery boilers and can be used as a heat source for the absorption chillers. If a user's heating load exceeds the supply, heat energy can be purchased from the ET-SES station; if the user's heating load is less than the supply, the excess heat energy can be sold back to the ET-SES station.

[0011] S2 ET-SES Station Operation Strategy and Profit Model

[0012] The ET-SES station houses a dispatch center. Based on historical user data, such as cooling, heating, and electricity load curves and renewable energy output curves, it uses a reasonable optimization dispatch model to calculate the required energy storage capacity and maximum charging / discharging power for each CCHPM user. Figure 2 As shown in the figure. Based on the calculation results, each CCHPM user and operator sign a service agreement, which clearly stipulates the maximum charging and discharging power, energy storage capacity, charging and discharging power plan, etc., and charges users corresponding service fees.

[0013] According to the signed service agreement, the dispatch center will deliver energy (electricity and heat) to users served by the ET-SES station through shared energy storage. For the ET-SES station, during peak energy consumption periods of the Multi-combined Cooling Heating and Power Microgrid (Mu-CCHPM), the dispatch center will send energy from the ET-SES station to supplement users' energy needs; during off-peak energy consumption periods of the Mu-CCHPM, the dispatch center will send energy into the ET-SES station to store users' surplus energy.

[0014] S3 Dual-Layer Optimization Configuration Model

[0015] S3.1 Upper-level model

[0016] The upper-level objective function is:

[0017] In the formula: C1 is the total operating cost of the ET-SES station; C inv The average daily investment and maintenance cost of the ET-SES station; and Investment and operating costs for constructing heating pipelines from the ET-SES station to each CCHPM; C s The storage service fee charged by ET-SES to Mu-CCHPM; and C represents the cost of purchasing / selling electricity from the grid at the ET-SES station. cchp,g and C cchp,s The cost of purchasing / selling energy (electricity, heat) from Mu-CCHPM to the ET-SES station.

[0018] 1) The average daily investment and maintenance cost of the ET-SES station is:

[0019]

[0020]

[0021]

[0022] In the formula: and These are the average daily investment and maintenance costs for SEES and STES, respectively; μ s and β s For the charge / discharge power and installed capacity cost factor of SEES; μ t and β t Cost coefficients for STES charge / discharge power and installed capacity; and This refers to the maximum charge / discharge power and installed capacity of the SEES. and This refers to the maximum charge / discharge power and installed capacity of STES; T day Service days for ET-SES stations; M s and M t The maintenance costs are for SEES and STES, respectively.

[0023] 2) The operating and investment costs of the heating pipeline are:

[0024]

[0025]

[0026] In the formula: C ben The construction cost per unit length (m) of the heating pipeline is taken as 1941 yuan / m; r is the benchmark discount rate; g is the operating cycle of the ET-SES station, taken as 10; N is the number of CCHPMs; m idenoted as , where is the construction length (m) of the heat pipeline from the ET-SES station to the i-th CCHPM; ER is the power consumption-to-heat transfer ratio of the heat pipeline; δ st,t This refers to the current electricity price sold by the power grid. and Let be the amount of heat purchased / sold by the i-th CCHPM to the ET-SES station during time period t.

[0027] 3) The storage service fee charged by ET-SES to Mu-CCHPM is:

[0028]

[0029]

[0030]

[0031] In the formula: and These are the shared electricity / heating service fees charged by ET-SES stations to Mu-CCHPM; N t The daily scheduling time period is 24 hours. and The unit price for electricity / heating services at ET-SES stations; and Let t represent the amount of electricity purchased / sold by the i-th CCHPM from the ET-SES station during time period t.

[0032] 4) The cost of energy exchange between the ET-SES station and the power grid is:

[0033]

[0034]

[0035] Where: δ ad,t The electricity price sold by the ET-SES station to the grid; and This refers to the amount of electricity purchased / sold by the ET-SES station from the power grid.

[0036] 5) The cost of energy (electricity and heat) purchased by the ET-SES station from Mu-CCHPM is:

[0037]

[0038]

[0039]

[0040] In the formula: and The costs of electricity / heat purchased from Mu-CCHPM for the ET-SES station are respectively; and These are the unit prices of electricity and heat at the time of purchase.

[0041] 6) The cost of energy (electricity and heat) sold by the ET-SES station to Mu-CCHPM is:

[0042]

[0043]

[0044]

[0045] In the formula: and The respective costs of electricity / heat sold from the ET-SES station to Mu-CCHPM; and These are the electricity / heat prices at the time of sale.

[0046] The upper-level model constraints are:

[0047] 1) The constraints for shared electrical energy storage (SEES) are:

[0048]

[0049] In the formula: Store energy for SEES at time t; and These are the charging and discharging efficiencies of the energy storage device; and These represent the energy stored at the start and end of SEES, respectively. and These are the charging and discharging power of SEES, respectively; and The SEES charge / discharge status bit is set to a value between 0 and 1.

[0050] 2) Constraints for shared thermal energy storage (STES):

[0051]

[0052] In the formula: Store energy for STES at time t; and These are the charging and discharging efficiencies of the energy storage device; and These represent the energy stored at the initial and final stages of STES, respectively. and These are the charging and discharging heat powers of STES, respectively. and Set the STES charge / discharge state bit, with a value of 0-1.

[0053] S3.2 Lower Layer Model

[0054] The lower-level objective function is:

[0055]

[0056] In the formula: C2 is the total operating cost of Mu-CCHPM; C xin The cost of electricity purchased by Mu-CCHPM from renewable energy power plants (WT, PV); C qi The cost of gas consumed for Mu-CCHPM; The equipment investment cost for Mu-CCHPM.

[0057] 1) The cost of Mu-CCHPM purchasing electricity from renewable energy power plants is:

[0058]

[0059] In the formula: α xin,t The electricity price of the new energy power station during time period t; Let represent the electricity purchased by the i-th CCHPM from its renewable energy power station during time period t.

[0060] 2) The heat energy recovered from the micro gas turbine to the waste heat boiler is:

[0061]

[0062]

[0063]

[0064] In the formula: Let be the electrical power output of the micro gas turbine of the i-th CCHPM during time period t; Let be the heat power output of the i-th CCHPM recovered from the micro gas turbine to the waste heat boiler during time period t; R represents the thermal power output of the gas-fired boiler at the i-th CCHPM during time period t; MT This indicates the output thermal power ratio of a micro gas turbine; and η represents the amount of gas consumed by the micro gas turbine and gas boiler in the i-th CCHPM during time period t; MT and η WB The efficiencies of the micro gas turbine and the gas boiler are respectively; Lqi It has the low calorific value of natural gas. η WB This refers to the efficiency of the waste heat boiler.

[0065] 3) The gas cost consumed by Mu-CCHPM is

[0066]

[0067] In the formula: p qi This refers to the price of natural gas.

[0068] 4) The equipment investment cost of Mu-CCHPM is:

[0069]

[0070] In the formula: The capacity of each device in Mu-CCHPM; where Let m represent the initial investment cost of each device; m be the benchmark discount rate; j be the number of devices; n represent the total lifespan; and assume that all devices in the Mu-CCHPM have the same annual interest rate and lifespan.

[0071] 5) The output power of the electric boiler, electric chiller, absorption chiller, and heat exchanger is:

[0072]

[0073]

[0074]

[0075]

[0076] The formula is: and These refer to the output thermal power of the electric boiler and the heat exchange device, respectively. The electrical power consumed by the electric boiler; For the heat power input to the heat exchange device; η EB and η HE The efficiencies of the electric boiler and the heat exchanger are respectively. and These refer to the cooling power produced by the electric chiller and the absorption chiller, respectively. The electrical power consumed by the electric chiller; The heat power consumed by the absorption chiller; η EC and CO AC These are the performance coefficients for electric chillers and absorption chillers, respectively.

[0077] The lower-level model constraints are:

[0078] 1) The power balance constraint is:

[0079]

[0080] In the formula: and The power generation capacity of wind power and photovoltaic power in new energy power plants respectively; Let be the electrical load power of the i-th CCHPM within time period t.

[0081] 2) The thermal power balance constraint is:

[0082]

[0083] In the formula: Let be the heat load power of the i-th CCHPM within time period t.

[0084] 3) The waste heat power balance constraint is:

[0085]

[0086] 4) The cold power balance constraint is:

[0087]

[0088] In the formula: Let be the cooling load power of the i-th CCHPM during time period t.

[0089] 5) The charging and discharging power balance of the ET-SES station is as follows:

[0090]

[0091]

[0092] In the formula: (37) and (38) are the charge / discharge / thermal power balance of SEES and STES, respectively.

[0093] 6) The upper and lower limits of output for each piece of equipment are constrained as follows:

[0094]

[0095] In the formula: and These represent the minimum and maximum output electrical power of the micro gas turbine; and These are the minimum and maximum output thermal power of the gas-fired boiler; and These are the minimum and maximum output thermal power of the electric boiler; and These are the minimum and maximum output cooling power of the absorption chiller; and These are the minimum and maximum output cooling power of the electric chiller; and These represent the minimum and maximum thermal power of the heat exchange device.

[0096] 7) Energy interaction balance between ET-SES station and Mu-CCHPM:

[0097]

[0098]

[0099] In the formula: (40) and (41) are the electric / thermal constraint balance equations for the energy interaction between the ET-SES station and the Mu-CCHPM, respectively; This represents the maximum electrical power of the interaction between SEES and Mu-CCHPM. This represents the maximum thermal power of the STES and Mu-CCHPM interaction. and As an auxiliary bit, it takes the value 0-1.

[0100] S4 Solution Method

[0101] like Figure 3 As shown. For lower-level optimization problems with convex objective functions and non-empty feasible solution sets, the lower-level model can be transformed into constraints of the upper-level model by constructing the Lagrangian function of the lower-level model and based on the KKT complementary relaxation conditions of the lower-level model, resulting in an equilibrium-constrained mathematical programming problem (MPEC). The Big-M method is then used to linearize the nonlinear terms in the transformed single-level nonlinear model, thus obtaining a single-level mixed-integer linear programming problem (MILP). For example... Figure 4 As shown. Internationally, GUROBI is the fastest and most accurate solver for single-level mixed integer linear programming problems. This paper uses MATLAB 2020b to call the YALMIP toolbox and the commercial solver GUROBI 10.0.3 for solving.

[0102] S5 Case Analysis

[0103] S5.1 Example Introduction

[0104] This example selects three typical CCHPMs in western my country to analyze their optimal configuration and performance when using ET-SES. CCHPM1 is a multi-power type with both wind and solar power output, CCHPM2 is a multi-power type with both solar power output, and CCHPM3 is a power-poor type with both wind and solar power output. It is assumed that there is an ET-SES station connecting the three CCHPMs in the same region, and that each CCHPM is independent, while the ET-SES station is interconnected with each CCHPM. This study considers the seasonal characteristics of Northwest China and selects typical daily load data for the three CCHPMs during winter, as shown below. Figure 5 As shown in Table 1. Time-of-use energy prices are listed below.

[0105] Table 1. Time-of-use energy prices

[0106]

[0107] S5.2 System Performance under Different Energy Storage Modes

[0108] This paper explores the optimization of energy storage capacity and charge / discharge power of Mu-CCHPM in independent energy storage mode and ET-SES mode, and analyzes the advantages of ET-SES mode in reducing energy storage demand. In independent energy storage mode, the optimization objective of CCHPM is to minimize the total system cost, including investment and operating costs. Table 2 shows the optimized energy storage capacity and maximum charge / discharge power of each CCHPM in independent energy storage mode and ET-SES mode. Under independent energy storage, the total electrical and thermal capacities of the three CCHPMs are 44440.93 kWh and 39750.85 kWh, respectively, while the electrical and thermal capacities under ET-SES are 20297.83 kWh and 11526.38 kWh, respectively. Compared to independent energy storage in each CCHPM, the electrical and thermal storage capacities are reduced by 54.33% and 71.00% under ET-SES, respectively. This significant capacity reduction can be attributed to the characteristics of shared energy storage.

[0109] Table 2 Results of CCHPM Independent Energy Storage and ET-SES Optimization

[0110]

[0111] Figure 6 This demonstrates the optimal operating power and energy storage level of the ET-SES station. It can be seen that the energy storage and thermal storage levels of the ET-SES station exhibit a pattern of initial storage followed by release and then re-storage. This pattern is influenced by the electricity price of the energy storage station, the characteristics of the energy storage equipment, and user load demand. For example... Figure 6 As shown in (a), the ET-SES station stores redundant power during off-peak hours (0:00-8:00 and 15:00-20:00) and releases this stored power back to the Mu-CCHPM during peak hours (9:00-15:00). Similarly, Figure 6 (b) shows that the ET-SES station stores thermal energy from 0:00 to 8:00 and from 14:00 to 16:00, and releases thermal energy during peak demand periods, thereby reducing energy waste and improving energy efficiency. Unlike the asynchronous charging and discharging operation in the independent energy storage mode, the charging and discharging of shared energy storage can be carried out synchronously.

[0112] Figure 7This demonstrates how the ET-SES station synchronously charges and discharges the Mu-CCHPM. Positive values ​​indicate that the Mu-CCHPM sells energy to the ET-SES station, while negative values ​​indicate that the Mu-CCHPM purchases energy from the ET-SES station. For Figure 7 As shown in (a), CCHPM1, being a wind-rich, high-load microgrid, purchases electricity from the ET-SES station during peak consumption periods and sells it back to the ET-SES station during periods of higher wind power. In contrast, CCHPM2, a solar-rich, high-load microgrid, has redundant power during midday (9:00-15:00) and can sell this power to the ET-SES station during these times. However, it purchases power from the ET-SES station at other times to maintain the normal operation of users' equipment. For CCHPM3, a low-power, high-load microgrid, it needs to purchase power from the ET-SES station for most of the day and sell to the SEES station only occasionally. This creates a complementary power structure among the CCHPMs, reducing energy waste and cost losses between units. Specifically, in... Figure 7 In (b), the thermal energy sharing in the ET-SES station also presents a similar situation. Since the load demands of different users differ in time and space, synchronous charging and discharging can be achieved between the Mu-CCHPM and the ET-SES station, thus greatly reducing the configuration capacity of the shared energy storage, as shown in Table 1.

[0113] S5.3 System performance under different energy storage modes

[0114] Having understood the advantages of the ET-SES mode in reducing energy storage capacity, this section compares the following three scenarios:

[0115] Scenario 1: Building a shared energy storage power station;

[0116] Scenario 2: Construction of shared energy storage thermal stations;

[0117] Scenario 3: Constructing an electric-thermal shared energy storage station.

[0118] Analyze the impact of establishing different types of SES stations on capacity and benefits.

[0119] Table 3 shows the optimization results of capacity and benefits for establishing different types of SES (Self-Storage Energy) stations. The data clearly shows that the optimal capacity of Scenario 1 is 39063.36 kWh, exceeding the optimal energy storage capacity of Scenario 3 (20297.83 kWh); and the optimal capacity of Scenario 2 is 23124.86 kWh, exceeding the optimal thermal storage capacity of Scenario 3 (11526.38 kWh). Regarding initial investment costs, although Scenario 3 has the highest initial investment cost (RMB 17.3077 million), followed by Scenario 1 (RMB 15.9741 million), Scenario 2 has the lowest investment cost (RMB 14.9881 million). However, in terms of returns, Scenario 3 generates the highest return (RMB 3.2142 million), followed by Scenario 1 (RMB 2.7179 million), and Scenario 2 generates the lowest return (RMB 1.7567 million). Furthermore, the investment payback periods for these three scenarios are 6.98 years, 8.53 years, and 5.38 years, respectively. Therefore, considering investment costs, returns, and investment return cycles, the ET-SES model demonstrates superior economic benefits compared to the SEES and STES models.

[0120] Table 2. Capacity and efficiency optimization results under different scenarios

[0121]

[0122] S6 Conclusion

[0123] A two-level optimization model for Mu-CCHPM considering ET-SES was established to examine the combined performance of ET-SES stations and Mu-CCHPM. Based on this, the advantages of the shared energy storage operation mode in reducing capacity and saving costs were analyzed. Subsequently, the impact of energy storage capacity on the economic performance of the energy system was investigated. The main conclusions are as follows:

[0124] 1) ET-SES facilitates simultaneous charging and discharging of different CCHPMs. Compared to independently established energy storage operation modes, the electrical and thermal energy storage capacities in shared energy storage operation modes are reduced by 31.76% and 44.79%, respectively.

[0125] 2) Users of ET-SES stations do not need to build their own energy storage systems, thus saving investment costs and significantly reducing overall configuration capacity and power requirements, effectively reducing energy storage investment expenditures and improving the utilization efficiency of energy storage resources.

[0126] 3) Comparing the three scenarios of shared electric energy storage, shared thermal energy storage, and electric-thermal shared energy storage, ET-SES offers the highest returns under the same load conditions compared to the first two scenarios, and its investment payback period of 5.57 years is also the shortest among the three scenarios. Overall, the ET-SES operating mode demonstrates superior economic benefits. Attached Figure Description Figure 1 The CCHPM structure for participating in ET-SES station services; Figure 2 Schematic diagram of ET-SES station; Figure 3 This is a diagram showing the scheduling relationships between the two layers; Figure 4 Here is a flowchart of the KKT algorithm; Figure 5 For the renewable energy generation and load demand of each CCHPM; Figure 6 The operating power and corresponding energy storage level of the ET-SES station; Figure 7 The charge / discharge characteristics of each CCHPM and the net charge / discharge energy level of the ET-SES station.

Claims

1. Claim 1: This invention provides an optimized configuration method for electric-thermal shared energy storage in multi-CCHP microgrids, comprising the following steps: Step 1: Establish the service model of the Electric-thermal Shared Energy Storage (ET-SES) station. Step 2: Develop the operational strategy and profit model for ET-SES stations. Step 3: Based on Steps 1 and 2, establish a two-layer optimization configuration model. Step 4: Solve Step 3 using the KKT method. Step 5: Conduct case studies using new energy data and various types of loads. S1 ET-SES station service model The high investment costs and long payback periods of on-load energy storage have limited its widespread use. To address this, the ET-SES service model is proposed. This model involves ET-SES operators investing in and constructing large-scale energy storage stations at sites within combined cooling, heating, and power (CCHPM) microgrids, providing users with more economical shared energy services. The operator is responsible for the operation and management of the energy storage stations and charges users a service fee. This service fee is defined (taking electricity sharing as an example): the fee paid by the user for each unit of power of electricity used for charging and discharging at the ET-SES station; the same applies to heat sharing. The CCHPM (Centralized Heat and Power Plant) incorporates three types of loads: cooling load, heating load, and electrical load. Its main equipment includes: micro gas turbines (MT), gas boilers (GB), electric boilers (EB), electric chillers (EC), absorption chillers (AC), heat exchangers (HER), waste heat recovery boilers (WB), and a renewable energy power plant. The output of the micro gas turbines and the electricity purchased from the renewable energy power plant can meet the electrical load of most users. If a user's electrical load exceeds the supply, electricity can be purchased from the ET-SES (Electric Heat and Power Supply) station. If the user's electrical load is less than the supply, the electricity can be used to drive the electric boilers to provide part of the user's heating load, and the remaining electricity can be sold back to the ET-SES station. The electric boilers, gas boilers, and waste heat recovery boilers can meet the heating load of most users. The heat emitted by the micro gas turbines is recovered through the waste heat recovery boilers and can be used as a heat source for the absorption chillers. If a user's heating load exceeds the supply, heat energy can be purchased from the ET-SES station; if the user's heating load is less than the supply, the excess heat energy can be sold back to the ET-SES station. S2 ET-SES Station Operation Strategy and Profit Model The ET-SES station houses a dispatch center. Based on historical user data, such as cooling, heating, and electricity load curves and renewable energy output curves, it uses a rational optimization dispatch model to calculate the required energy storage capacity and maximum charging / discharging power for each CCHPM user. Based on the calculation results, each CCHPM user signs a service agreement with the operator, clearly specifying the maximum charging / discharging power, energy storage capacity, and charging / discharging power plan, and charges the user a corresponding service fee. According to the signed service agreement, the dispatch center will deliver energy (electricity and heat) to users served by the ET-SES station through shared energy storage. For the ET-SES station, during peak energy consumption periods of the Multi-combined Cooling Heating and Power Microgrid (Mu-CCHPM), the dispatch center will send energy from the ET-SES station to supplement users' energy needs; during off-peak energy consumption periods of the Mu-CCHPM, the dispatch center will send energy into the ET-SES station to store users' surplus energy. S3 Dual-Layer Optimization Configuration Model S3.1 Upper-level model The upper-level objective function is: In the formula: C1 is the total operating cost of the ET-SES station; C inv The average daily investment and maintenance cost of the ET-SES station; and Investment and operating costs for constructing heating pipelines from the ET-SES station to each CCHPM; C s The storage service fee charged by ET-SES to Mu-CCHPM; and C represents the cost of purchasing / selling electricity from the grid at the ET-SES station. cchp,g and C cchp,s The cost of purchasing / selling energy (electricity, heat) from Mu-CCHPM to the ET-SES station. 1) The average daily investment and maintenance cost of the ET-SES station is: In the formula: and These are the average daily investment and maintenance costs for SEES and STES, respectively; μ s and β s For the charge / discharge power and installed capacity cost factor of SEES; μ t and β t Cost coefficients for STES charge / discharge power and installed capacity; and This refers to the maximum charge / discharge power and installed capacity of the SEES. and This refers to the maximum charge / discharge power and installed capacity of STES; T day Service days for ET-SES stations; M s and M t The maintenance costs are for SEES and STES, respectively. 2) The operating and investment costs of the heating pipeline are: In the formula: C ben The construction cost per unit length (m) of the heating pipeline is taken as 1941 yuan / m; r is the benchmark discount rate; g is the operating cycle of the ET-SES station, taken as 10; N is the number of CCHPMs; m i denoted as , where is the construction length (m) of the heat pipeline from the ET-SES station to the i-th CCHPM; ER is the power consumption-to-heat transfer ratio of the heat pipeline; δ st,t This refers to the current electricity price sold by the power grid. and Let be the amount of heat purchased / sold by the i-th CCHPM to the ET-SES station during time period t. 3) The storage service fee charged by ET-SES to Mu-CCHPM is: In the formula: and These are the shared electricity / heating service fees charged by ET-SES stations to Mu-CCHPM; N t The daily scheduling time period is 24 hours. and The unit price for electricity / heating services at ET-SES stations; and Let t represent the amount of electricity purchased / sold by the i-th CCHPM from the ET-SES station during time period t. 4) The cost of energy exchange between the ET-SES station and the power grid is: Where: δ ad,t The electricity price sold by the ET-SES station to the grid; and This refers to the amount of electricity purchased / sold by the ET-SES station from the power grid. 5) The cost of energy (electricity and heat) purchased by the ET-SES station from Mu-CCHPM is: In the formula: and The costs of electricity / heat purchased from Mu-CCHPM for the ET-SES station are respectively; and These are the unit prices of electricity and heat at the time of purchase. 6) The cost of energy (electricity and heat) sold by the ET-SES station to Mu-CCHPM is: In the formula: and The respective costs of electricity / heat sold from the ET-SES station to Mu-CCHPM; and These are the electricity / heat prices at the time of sale. The upper-level model constraints are: 1) The constraints for shared electrical energy storage (SEES) are: In the formula: Store energy for SEES at time t; and These are the charging and discharging efficiencies of the energy storage device; and These represent the energy stored at the start and end of SEES, respectively. and These are the charging and discharging power of SEES, respectively; and The SEES charge / discharge status bit is set to a value between 0 and 1. 2) Constraints for shared thermal energy storage (STES): In the formula: Store energy for STES at time t; and These are the charging and discharging efficiencies of the energy storage device; and These represent the energy stored at the initial and final stages of STES, respectively. and These are the charging and discharging heat powers of STES, respectively. and Set the STES charge / discharge state bit, with a value of 0-1. S3.2 Lower Layer Model The lower-level objective function is: In the formula: C2 is the total operating cost of Mu-CCHPM; C xin The cost of electricity purchased by Mu-CCHPM from renewable energy power plants (WT, PV); C qi The cost of gas consumed for Mu-CCHPM; The equipment investment cost for Mu-CCHPM. 1) The cost of Mu-CCHPM purchasing electricity from renewable energy power plants is: In the formula: α xin,t The electricity price of the new energy power station during time period t; Let represent the electricity purchased by the i-th CCHPM from its renewable energy power station during time period t. 2) The heat energy recovered from the micro gas turbine to the waste heat boiler is: In the formula: Let be the electrical power output of the micro gas turbine of the i-th CCHPM during time period t; Let be the heat power output of the i-th CCHPM recovered from the micro gas turbine to the waste heat boiler during time period t; R represents the thermal power output of the gas-fired boiler at the i-th CCHPM during time period t; MT This indicates the output thermal power ratio of a micro gas turbine; and η represents the amount of gas consumed by the micro gas turbine and gas boiler in the i-th CCHPM during time period t; MT and η WB The efficiencies of the micro gas turbine and the gas boiler are respectively; L qi It has the low calorific value of natural gas. η WB This refers to the efficiency of the waste heat boiler. 3) The gas cost consumed by Mu-CCHPM is In the formula: p qi This refers to the price of natural gas. 4) The equipment investment cost of Mu-CCHPM is: In the formula: The capacity of each device in Mu-CCHPM; where Let m represent the initial investment cost of each device; m be the benchmark discount rate; j be the number of devices; n represent the total lifespan; and assume that all devices in the Mu-CCHPM have the same annual interest rate and lifespan. 5) The output power of the electric boiler, electric chiller, absorption chiller, and heat exchanger is: The formula is: and These refer to the output thermal power of the electric boiler and the heat exchange device, respectively. The electrical power consumed by the electric boiler; For the heat power input of the heat exchange device; η EB and η HE The efficiencies of the electric boiler and the heat exchanger are respectively. and These refer to the cooling power produced by the electric chiller and the absorption chiller, respectively. The electrical power consumed by the electric chiller; The heat power consumed by the absorption chiller; η EC and CO AC These are the performance coefficients for electric chillers and absorption chillers, respectively. The lower-level model constraints are: 1) The power balance constraint is: In the formula: and The power generation capacity of wind power and photovoltaic power in new energy power plants respectively; Let be the electrical load power of the i-th CCHPM within time period t. 2) The thermal power balance constraint is: In the formula: Let be the heat load power of the i-th CCHPM within time period t. 3) The waste heat power balance constraint is: 4) The cold power balance constraint is: In the formula: Let be the cooling load power of the i-th CCHPM during time period t. 5) The charging and discharging power balance of the ET-SES station is as follows: In the formula: (37) and (38) are the charge / discharge / thermal power balance of SEES and STES, respectively. 6) The upper and lower limits of output for each piece of equipment are constrained as follows: In the formula: and These represent the minimum and maximum output electrical power of the micro gas turbine; and These are the minimum and maximum output thermal power of the gas-fired boiler; and These are the minimum and maximum output thermal power of the electric boiler; and These are the minimum and maximum output cooling power of the absorption chiller; and These are the minimum and maximum output cooling power of the electric chiller; and These represent the minimum and maximum thermal power of the heat exchange device. 7) Energy interaction balance between ET-SES station and Mu-CCHPM: In the formula: (40) and (41) are the electric / thermal constraint balance equations for the energy interaction between the ET-SES station and the Mu-CCHPM, respectively; This represents the maximum electrical power of the interaction between SEES and Mu-CCHPM. This represents the maximum thermal power of the STES and Mu-CCHPM interaction. and As an auxiliary bit, it takes the value 0-1. S4 Solution Method For lower-level optimization problems with convex objective functions and non-empty feasible solution sets, the lower-level model can be transformed into constraints for the upper-level model by constructing the Lagrangian function of the lower-level model and applying the KKT complementary relaxation conditions, resulting in an equilibrium-constrained mathematical programming problem (MPEC). The Big-M method is then used to linearize the nonlinear terms in the transformed single-level nonlinear model, thus obtaining a single-level mixed-integer linear programming problem (MILP). Internationally, GUROBI is considered a fast and accurate solver for single-level mixed-integer linear programming problems. This paper utilizes MATLAB 2020b with the YALMIP toolbox and the commercial solver GUROBI 10.0.3 for solution.

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