Station Capacity Research Articles

Penjadwalan Kapasitas Produksi Roti menggunakan Metode Rough Cut Capacity Planning di UMKM Cita Rasa Gorontalo

MSME Cita Rasa is a manufacturing industry in Gorontalo City. Fulfillment of consumer demand for the quantity and time of orders is closely related to the availability of raw materials, labor, machines, working time and other resources that support bread-making production. Therefore, it is necessary to calculate the scheduling of capacity requirements for bread products to see available capacity and actual capacity. The aim of this research is to create a bread production plan and determine the feasibility of bread production capacity at MSME Cita Rasa using the Rough Cut Capacity Planning method. RCCP is a method used to measure work station capacity so that it can be seen whether a production schedule requires overtime work hours or subcontracts. Based on the results obtained, from the production capacity feasibility test using RCCP, it can be seen that all work stations in the MSME Cita Rasa have a positive value, which means the capacity is feasible

A robust dynamic hydrogenation network layout model considering station capacity expansion and flexible transportation modes

The development of the hydrogen-fueled vehicle industry needs a mature hydrogenation network to provide a guaranteed source of hydrogen in the future. We propose a dynamic hydrogen supply network optimization model under demand uncertainty. The model incorporates the dynamic characteristics of the network, takes into account the linkages of units within the network as well as the hydrogenation network between cycles. Hydrogenation networks can be planned over multiple cycles and allow for capacity expansion of hydrogen production and refueling stations, and shifts in the way hydrogen is transported between sites. Robust optimization is used to deal with demand uncertainty. In the results of the case study obtained, resources within the network were fully utilized, costs within the network show economies of scale; the average resource utilization rate at each site reached 85.6 %; and the rate of meeting user demand reached more than 98.5 %. A hydrogenation network with sustainable operations was formed.

Application of hybrid renewable energy systems for supplying electricity demand of a water pump station of agricultural plants: a case-based research

Abstract Employing clean energy production in agricultural purposes has attracted the attention of many researchers. One of the challenges is the flexible nature of irrigation of the plants that need to have a changeable power source of pump stations to supply the load demands. Renewable energies are among the best solutions to supply environmentally-friendly power, especially in remote areas where there is no access to the electricity. This study considers the needed water of five different plants, and according to the calculated hydromodule, the capacity of the pump station as well as its monthly and yearly load demands are determined. Based on the calculated load demand, different configurations of hybrid renewable energy systems (HRES) are considered, and the optimum sizes of equipment are determined. The needed load demand is 1463 kWh/day and peak load is 266.16 kW. Based on the suppositions and inputs of this study, results show that the best economic configuration would be PV/wind turbine/diesel generator/battery the way that cost of energy (COE) and net present cost (NPC are 0.28 ($/kWh) and $2.48 million. Also, the best environmentally friendly system (PV/wind turbine/battery) where CO2 emission is zero and RF is 100%, can be obtained with 647 kW PV panels and 106 wind turbines, the way that COE and NPC values are 0.5 ($/kWh) and 4.41 $ million. To reach the best technical system (PV/generator/battery), 514 kW PV, 100 kW diesel generator, and 1816 batteries would have the least unmeted load and excess electricity where COE and NPC values are 0.34 ($/kWh) and 2.98$ million.

Site selection and capacity determination of charging stations considering the uncertainty of users’ dynamic charging demands

Aiming at the problems of high investment and low efficiency in the planning and construction of electric vehicle (EV) charging stations in cities, an optimization model for site selection and capacity determination of charging stations considering the uncertainty of users’ dynamic charging demands is proposed. Firstly, based on the travel chain theory and the Origin-Destination (OD) matrix, the travel characteristics of EVs are studied, and the spatial and temporal distribution prediction model of EV charging load is established through the dynamic Dijkstra algorithm combined with the Monte Carlo method. Secondly, a site selection model for the charging station is established which takes the minimum annualized cost of the charging station operator and the annualized economic loss of the EV users as the goal. At the same time, the weighted Voronoi diagram and Adaptive Simulated Annealing Particle Swarm Optimization algorithm (ASPSO) are adopted to determine the optimal number/site selection and service scope of charging stations. Finally, an uncertain scenario set is introduced into the capacity determination model to describe the uncertainty of the users’ dynamic charging demands, and the robust optimization theory is utilized to solve the capacity of the charging station. A case study is carried out for the EV charging station planning problem in some urban areas of a northern city, and the validity of the model is verified.

Rural Photovoltaic Storage and Charging Integrated Charging Station Capacity Allocation Strategy based on Tariff Compensation Mechanism

Background: In order to help the carbon peaking and carbon neutrality goals, the current new energy vehicle to the countryside policy for the local use of renewable energy and demand-side carbon reduction provides a good opportunity but also requires rural townships and villages of electric vehicle charging infrastructure planning ahead. However, due to the current low rural electric vehicle ownership, the charging price compensation mechanism is not yet perfect, resulting in the planning period of electric vehicle growth and the willingness to respond to the tariff compensation policy is difficult to accurately assess. Methods: This paper proposes a rural photovoltaic storage and charging integrated charging station capacity allocation strategy based on the tariff compensation mechanism. Firstly, we construct a spatial-temporal dynamic distribution model of rural EV charging load coupled with distribution network-transportation network, and on this basis, we consider the rural EV charging time-sharing tariff and tariff compensation policy incentive, and amend the EV charging load transfer model; and then we construct an optimization planning model of charging station with the goal of minimizing the cost of construction, operation and maintenance, and maximizing the charging benefit of the integrated charging station in the rural area, and obtain the optimal synergistic planning scheme under the tariff compensation mechanism in the planning period. Results: The optimal collaborative planning scheme under the electricity price compensation mechanism is obtained, and the correctness and validity of the proposed optimal planning method of the rural optical storage charging station under the electricity price compensation mechanism is verified by the example, which is of positive significance in the promotion of the charging facilities to go to the countryside in an appropriate manner, and in the stimulation of the willingness of the rural consumers in the townships to purchase vehicles. Conclusion: (1) The spatial and temporal distribution and transfer model of rural EV charging loads with price incentives is constructed by taking into account the preferential charging price policies such as rural time-sharing tariff and tariff compensation mechanism. By comparing the operating revenues of optical storage-charging integrated charging stations with and without timesharing tariffs and tariff compensation policies, we verified the incentive effect of multiple types of price incentives for the over-planning of rural electric vehicle charging facilities. (2) The proposed optimal configuration method of rural photovoltaic, storage and charging integration charging station can realize the in-situ utilization of rural renewable energy, tap the price competitiveness of photovoltaic, storage and charging integration, and weaken the cost of electricity consumption. By comparing the optimized configuration scheme with and without joint planning, it is verified that the moderate configuration of in-situ photovoltaic and energy storage equipment on the basis of the planning of charging piles brings benefits far exceeding the investment cost, and has a great role in increasing the operational efficiency of rural charging facilities.

Germany's public EV charging points: Analysing the 2023 state of expansion

AbstractThe European Climate Law sets a legally binding target of net zero greenhouse gas emissions by 2050. In this regard, in 2023 the EU Environmental Council decided that from 2035 onwards only CO2‐neutral new cars will be licensed in the European Union. Simultaneously, since the energy crisis caused by the Russian invasion of Ukraine, fuel prices increased in Germany. This has made more and more households think about purchasing an e‐car. However, not every household has the opportunity to install their own wallbox, and when travelling long distances, e‐car users are dependent on the availability of ample public charging stations. Against this background, with a special focus on rural areas, this paper considers the questions whether and where spatial inequalities in the accessibility of public charging stations might currently exist. To approach these questions, based on an empirical analysis of the 2023 official location data of public charging points in Germany, we examine the nationwide distribution, accessibility and available capacity of public charging stations in Germany at small‐scale from the point of view of the ‘household’ as well as those who travel by e‐car within Germany. In order to evaluate the location data of public charging stations we mainly use raster‐based accessibility analysis methods as well as isotropic kernel intensity estimates. We found that, in contrast to the common belief, the network of public charging stations is quite dense. However, taking a closer look reveals that the charging infrastructure in Germany has so far been tailored to the needs of intra‐regional travelers (commuting, shopping, leisure) rather than to those of the residential population with no access to their own wallbox (daily recharging in close proximity to one‘s home) or the mid‐ to long‐distance travelers.

Research on the impact of emergency evacuation of subway under emergencies based on Pathfinder: A case study of a university station

To guarantee the safe operation of the subway and improve the efficiency of personnel evacuation after emergencies, based on the sizes and passenger capacity of the actual subway station, the modeling on a special subway station in Harbin was carried out using the Pathfinder software. Combined with the passenger flow characteristics in the station at different periods, the unfavorable conditions that might exit the station were analyzed, and various conditions were simulated.

Method for calculating the supply of transport and logistics services depending on the demand for freight transportation

The article examines the problems that arise in railway freight transportation when determining the optimal size of rolling stock fleet under seasonal fluctuations in the volume of transportation and ensuring a certain reserve of vehicles. In order to optimize the number of vehicles in the fleet, it is necessary to find a balance between undesirable expenses for maintaining wagons in periods of falling demand for them (surplus supply of transport and logistics services) and unearned income from their lack (deficit) in periods of maximum growth of transportation volumes. The methodology and example of calculating the fleet of freight wagons, the efficiency of their use and determining the optimal number of rolling stock and the need for a certain reserve of vehicles are presented. It is noted that the railway transport of Ukraine was and continues to be one of the main types of transport in the transportation of goods and passengers. However, considering the long operating time of the rolling stock, more than 70% of semi-wagons and more than 80% of grain wagons require replacement or extension of their service life due to capital repairs. The role of railways is especially critical in the current period of russia's war against Ukraine, due to the lack of air transport, river and sea transport and the insufficient capacity of highways and border railway stations. Determining the required number and optimizing the number of vehicles in the fleet can be carried out according to the calculation methodology, which is based on the analytical determination of the minimum of the objective function of the total operating costs associated with both the deficit and the surplus of vehicles compared to the demand for transport and logistics services. It has been established that the application of this calculation method allows to optimize the inventory and working fleet of wagons taking into account the different cost per day of shortage and surplus of the fleet of wagons (supply of transport services compared to their demand). Compared to traditional methods of calculation, the proposed method saves operational costs for maintaining the fleet of wagons in the amount of 2-5%.

Digital design trends of train and shunting operations at railway stations

This article explores in detail the problems associated with the digitization of train and shunting work at railway stations. Based on the analysis of the indicators of the use of the “Ch” station under the JSC “Uzbekistan Railways”, the factors that negatively affect the development of the digitization stages have been studied. A daily executed work-plan graph of the sorting station was also studied in real-time conditions. It found that the finished contents would remain standing at the station departure park for an average of 4 hours or more. One of the main reasons for this was the insufficient capacity of the adjacent station to handle trains. The station staff were therefore shown to be making possible the formation of “abandoned trains”. Recommendations were made to introduce a digitized complex system to improve train and shunting operations at railway stations. The functional capabilities of the proposed system were analyzed. Key words: railway station, loading of station, “abandoned train”, station daily executed work-plan graph, sorting hump capacity, digitized system, functional capacity, software.

A multistage simulation-optimization-integrated methodology framework for user-oriented electric vehicle carsharing reallocation under dynamic price subsidy

Electric vehicle (EV) carsharing operation is facing major challenge to balance the increasing user demand with insufficient vehicle availability and station capacity. Previous researchers mainly focus on reallocating EVs in limited stations and discrete periods through operator-oriented strategies, while containing scant study of dynamic pricing scheme that can benefit supply-demand balance and service profitability in continuous operation periods. Therefore, this paper proposes a multistage simulation-optimization-integrated methodology framework for adaptively incentivizing users based on dynamic price subsidy (DPS). In stage I, Simulation of Urban Mobility (SUMO) is used to determine the real-time supply-demand distributions from user historical data. In stage II, a novel user-oriented reallocation optimization model is established to maximize the operation profit based on the obtained SUMO results. To obtian feasibile solutions, an improved immune genetic algorithm is developed to effectively solve the model. The real-world case study in Shanghai shows that, compared with other benchmark methods, the proposed methodology can significantly increase the daily profit from 78981 RMB to 89506 RMB and improve the system balance from 78.1 % to 94.5 %. Sensitivity analysis and cost-benefit analysis show that the user-oriented DPS can reduce operation cost and order waiting time, while promoting EV utilization within different user populations.

ОСОБЛИВОСТІ ВЛАШТУВАННЯ ВЕНТИЛЯЦІЇ В ЗАХИСНИХ СПОРУДАХ ЦИВІЛЬНОГО ЗАХИСТУ

Given the urgency of armed aggression, ensuring the safety of the civilian population is of utmost importance. Various types of structures are used for this purpose, including simple shelters, anti-radiation shelters, storage facilities, and dual-purpose structures. The construction of these facilities must be equipped with diverse internal engineering systems to ensure the livelihood of people. With the introduction of the updated State Building Code of Ukraine (DBN) B 2.2.-5:2023 [1], the requirements for the engineering support of these structures have significantly increased. This article aims to analyze the features of arranging engineering systems in these facilities, particularly ventilation systems, and provide recommendations for specific cases of ventilation and conditioning system installation.
 The article examines regulatory requirements for the installation of ventilation systems in the most common civil defense structures at present - anti-radiation shelters and dual-purpose structures with NBC (nuclear, biological, chemical) properties. Using the solution to a differential equation, the concentrations of carbon dioxide in rooms with people present are calculated depending on the ventilation mode: normal, reserve, and emergency. It is determined that in all cases, the concentration will not exceed the critical value. Recommendations are given for the design of ventilation systems for these buildings, and the specifics of ventilating and cooling rooms in diesel power stations for backup power supply are discussed.
 It is revealed that, at significant capacities of diesel power stations, the arrangement of ventilation for cooling becomes structurally complex. Solutions to this problem are proposed. It is recommended for large NBC structures and dual-purpose structures to have two ventilation chambers with separate air intakes. This will help reduce the risks of contaminating the inflow air and prevent an increase in carbon dioxide concentration during fires near civil defense structures.

Conceptual Design of Public Charging Stations for Freight Road Transport

We present a comprehensive methodology for a two-step approach to address the task at hand. The first step involves the optimal placement of charging stations, while the second step focuses on determining the necessary capacity of the charging stations based on traffic factors. This methodology is applicable to countries, states, or specific areas where the placement and optimization of charging stations for truck road transport are being considered. We identify the key inputs required for solving such a task. In the results section, we demonstrate the outcomes using a model example for the Czech Republic.

EXPRESS ANALYSIS OF PROBABILISTIC CHARACTERISTICS OF WIND POWER TATIONS AS A SOURCE OF ENERGY FOR SEAWATER DESALINATION IN THE AZOV-BLACK SEA REGION OF UKRAINE

Ukraine takes part in the implementation of the European program «2´40 GW Green Hydrogen Initiative». It is planned to build 10 GW of electrolyser capacity on the territory of Ukraine for the production of «green» hydrogen using the energy of wind power stations in the Azov-Black Sea region. Territorial sea waters of Ukraine are characterized by a significant potential of offshore wind energy, which is currently developing rapidly in the world. One of the alternative options for supplying fresh water for the operation of electrolysers when powered by offshore wind power stations involves using desalinated seawater. The operation of 10 GW of electrolyser capacity will ensure the production of «green» hydrogen in the amount of 1.65 million tons per year and will require the consumption of prepared fresh water of about 24 million m3/year. Seawater desalination is an established technology that is widely used worldwide to reduce freshwater scarcity. The use of energy from wind power stations for seawater desalination is an alternative option within the scope of this Program. However, the mismatch between the random nature of wind power generation and the constant energy demand for desalination makes the integration between the two technologies all the more important. The goal of this paper is to estimate the probabilistic annual ensuring of given levels of power and volume of electricity production by wind power stations in the coastal and offshore territories of the Azov-Black Sea region of Ukraine. The probabilistic annual distributions of wind speed and energy indicators of wind power stations for a height of 100 meters were studied, the average annual wind speed of about 7.5 m/s was substantiated. An achievable value of the utilization rate of the installed capacity of wind power stations was obtained at the level of 35 %, provided that the generated energy is fully integrated into the technological schemes of water desalination. The duration of production of full and half volumes of electricity production and power generation is determined. Algorithms for calculating the probability of exceeding various required power levels and volumes of electricity production by wind power stations have been developed. Bibl. 48, Fig. 6, Tab. 4.

Green hydrogen levelized cost assessment from wind energy in Argentina with dispatch constraints

This study assesses the optimal levelized cost of hydrogen (LCOH) production from wind farms. The study investigates 84 locations in the south of Argentina with nodes spaced 100 km apart, as well as one location each in Chile, the USA, Spain, Japan, and Australia. A model is presented to optimize the design of the wind farm, electrolyzer plant, compressor station, and storage capacity (gaseous 160 bar), with different hydrogen demands (hydrogen dispatch constraints) and minimizing the LCOH. Hourly data for wind resources from NASA is used to define a characteristic year. The model involves energy and mass balances in hourly basis for the whole year. Sequential solution procedures with heuristic rules are implemented. The optimal costs and their relation to the main variables, as well as production and storage, are analyzed. By imposing dispatch constraints, increase in levelized cost ranges from 25 % to 40 %, and decrease in annual hydrogen production ranges from 5 % to 30 %. Best levelized cost without considering electric transport between wind farm and electrolyzer plant is 2700 USD/t.

Distribution network restoration supply method considers 5G base station energy storage participation

This paper proposes a distribution network fault emergency power supply recovery strategy based on 5G base station energy storage. This strategy introduces Theil's entropy and modified Gini coefficient to quantify the impact of power supply reliability in different regions on base station backup time, thereby establishing a more accurate base station's backup energy storage capacity model that can fully utilize the base station's energy storage resources to participate in the emergency power supply of distribution network faults. First, the optimal Copula function in each cycle is determined through the Akaike information criterion and squared Euclidean distance to establish a wind power-photovoltaic output scenario. Secondly, the traditional Gini coefficient is modified using the weighted average node degree and influence rate indicators. A comprehensive vulnerability model is established through the modified Gini coefficient and Theil's entropy indicators. Based on the comprehensive vulnerability model, a backup energy storage time model and a modified backup energy storage capacity model of the base station affected by power supply reliability are established. Thus, the callable energy storage capacity of base stations in different areas is obtained. Finally, a two-stage robust optimization model is introduced to minimize system operating costs to solve the volatility of 5G base station communications and wind-solar output, thereby establishing an emergency power supply recovery model for base station energy storage and wind-solar output. Simulated with the improved IEEE-33 node model, the results show that the proposed base station's energy storage model improves the utilization of the base station energy storage resources and, at the same time, effectively reduces the loss of load during the fault phase of the distribution network and improves the absorption of the PV output.

A multi-objective evolutionary approach for the electric vehicle charging stations problem

This paper presents a framework that integrates a mobility and traffic simulator with evolutionary algorithms to solve the location problem of electric vehicle charging infrastructure. The framework presented in this research is configured with a real-life scenario that considers a maximum number of charging stations and a specific number of electric vehicles that are driven according to a movement distribution model for the urban city under consideration. The concerning scenario is formulated as a multi-objective optimization problem and is approximated by two multi-objective evolutionary algorithms based on two evolutionary approaches for multi-objective optimization, namely, NSGA-II and MOEA/D-gen. In this way, the adopted algorithms search for optimal station locations and capacities in terms of travel time and the number of charging stations. The analysis of the results obtained by the multi-objective approaches used in the proposed framework is two-fold. On the one hand, solutions confirm that both objectives considered in this study are in conflict. That is, the better the solution for one objective is, the more deteriorated it is for the other. On the other hand, it was found that NSGA-II obtained a better approximation to the optimal solutions according to two multi-objective performance indicators. These results give an idea of the type of algorithms that could best solve the formulated problem in terms of efficiency and effectiveness and understand the behavior of evolutionary algorithms in the multi-objective electric vehicle charging stations problem. Therefore, this research traces the route to study different scenarios and analyze the characteristics of the problem. Furthermore, it opens the door to exploring other meta-heuristics and their components to deal with this problem adequately.

Doubly Selective with Expectation Maximization based Massive-Mimo-Non-Orthogonal Multiple Access systems

The Long-Term Evaluation (LTE) based Fourth Generation (4G) and Fifth Generation (5G) communications require higher data rates to satisfy the requirements of user equipment. However, it is a difficult task for conventional Multiple Input Multiple Output (MIMO) systems to deliver the highest throughput and data rates to end users. Additionally, an increase in data rates led to increased power consumption, which decreased spectrum efficiency and energy efficiency. Therefore, this paper focuses on the implementation of the Doubly Selective with Expectation Maximization (DSEM) channel estimation method for Massive-MIMO based Non-Orthogonal Multiple Access (NOMA) systems. Here, the DSEM scheme divides the channel into expectation and maximization vectors based on antenna diversity. Further, time sample and frequency band base dual channel analysis are performed to maintain the synchronization in the receiver. The simulations conducted using MatlabR2018a show that base station (BS) capacity, user equipment capacity, uplink (UL)-Spectrum Efficiency (SE), and downlink (DL)-SE performance measures are improved in Massive-MIMO-NOMA systems using DSEM channel estimation and shows the superior performance than state of art approaches.

Research on short-term joint optimization scheduling strategy for hydro-wind-solar hybrid systems considering uncertainty in renewable energy generation

Due to its randomness, intermittence, and volatility, the high-proportional integration of wind and solar power poses challenges to the safe and stable operation of power systems. Cascade hydropower stations have a high response speed, high adjustability, and stable output. This study proposed a hydro-wind-solar hybrid system and investigated its short-term optimal coordinated operation based on deep learning and a double-layer nesting algorithm. A stochastic complementary scheduling model was constructed to maximize the cascade energy storage. The particle swarm optimization algorithm-dynamic programming (PSO-DP) coupled with the inner and outer nesting optimization algorithm reduces the problem-solving complexity. The hybrid system was applied to a national comprehensive development base of renewable energy with integrated wind, solar, and hydropower in China. Studies have shown the following: The hydro-wind-solar hybrid system has a certain degree of scalability. The utilization of deep learning methods can fully consider the uncertainty of wind and solar. The internal and external nested optimization algorithm, which realizes the reasonable and efficient distribution of water and electricity, and improves the future power generation capacity of cascade hydropower stations, was used to solve the problem. This study provided a valuable reference for the large-scale utilization of other renewable energy sources worldwide.

Battery-powered automated guided vehicles scheduling problem in automated container terminals for minimizing energy consumption

Battery-Powered Automated Guided Vehicles (B-AGVs) are important equipment used to transfer containers between the seaside and the landside in automated container terminals. Due to their limited battery capacity, the B-AGVs require battery recovery when their battery reaches the threshold. However, the processing capacity of electrical battery swapping stations is limited, it is crucial to avoid congestion in swapping station. Considering that the scheduling problem of B-AGV in the terminal is time intensive, this paper proposes a set partitioning method based on breadth-first and depth-first search to solve the established mixed integer programming model. Combined with the operational characteristics of the terminal, this paper adopts the flexible pooling strategy to effectively matches the inbound and outbound containers to form dual-cycle operation of B-AGVs, which can reduce the computational complexity and thus improving the solution efficiency. In addition, the record-to-record travel algorithm is applied to improve the quality of the solution. Finally, the effectiveness of the proposed model and solution method is evaluated through numerical experiments. Besides, the applicability of the flexible pooling strategy to different container terminals is studied, and the impact of the number of B-AGVs and the capacity of swapping stations on the energy consumption of B-AGVs is investigated, and some managerial insights are given accordingly.

Optimization of configurations and scheduling of shared hybrid electric‑hydrogen energy storages supporting to multi-microgrid system

As the energy structure undergoes transformation and the sharing economy advances, hydrogen energy and shared energy storage will become the new norm for addressing future energy demand and user-side storage applications, in order to better meet the flexibility and sustainability requirements of the energy system. This paper focuses on shared energy storage that links multiple microgrids and proposes a bi-layer optimization configuration method based on a shared hybrid electric‑hydrogen storage station for microgrids, combining cooling, heating, and power systems, to better achieve efficient energy utilization and promote sustainable development. The upper-layer model solves the energy storage station capacity configuration problem, while the lower-layer model solves the optimization operation problem of the multi-microgrid system. The lower-layer model is transformed into a constraint condition of the upper-layer model based on the Karush-Kuhn-Tucher condition of the lower-layer optimization model, and the Big-M method is used to linearize nonlinear problems. The rationality and effectiveness of the proposed bi-layer planning model are verified through analytical examples in three different scenarios. The results showed that compared to individual energy storage, shared power storage achieved an average daily net income of $430.00, reduced battery capacity by 75.94 %, and reduced daily operating costs of the microgrids by 11.53 %. Hybrid energy storage increased the daily net income of the energy storage side by 61.67 %, further reduced battery capacity by 67.13 %, and further reduced daily operating costs of the microgrid by 3.39 %. In addition, the optimal capacity allocation of energy storage systems and the operation optimization of multi microgrid systems have been achieved. The results demonstrate that the proposed hybrid energy storage services can effectively reduce user costs, save energy storage resources, and achieve mutual benefits for both users and energy storage operators.