In high-proportion new energy energy system, energy storage is a key measure to meet the balance of supply and demand, and the safety and stability requirements. Firstly, this paper proposes that the main goal of configuring energy storage is to improve the new energy consumption and meet the load supply capacity. Based on this main goal, the basic principles of energy storage deployment are analyzed. Considering annual calculations, a demonstration and optimization model for the scale of energy storage deployment from the perspective of the whole society is proposed. Then, the paper introduces the overall method and process of the model calculation, annual system startup curve calculation and energy storage charging and discharging strategy to maximize the consumption of new energy. Finally, the power grid parameters at the provincial scale are used as a case to verify the effectiveness of the scale demonstration method and process.

Energy storage can alleviate network congestion through "charge in low load period and discharge in high load period", and solve the contradiction between the difficulty of power grid construction and the requirement of reliable power supply. However, there are few researches on optimization of energy storage planning to alleviate network congestion and reasonable alternatives to traditional power grid investment.Therefore, this paper proposed an optimization method of energy storage planning for alleviating network congestion. Firstly, the load center network section is divided by using the principle of layering and partitioning. Secondly, the energy storage planning optimization model that comprehensively considers energy storage investment and maintenance costs, system congestion costs, and energy storage charging and discharging benefits is constructed, and the model solution method is proposed with particle swarm algorithm. Finally, a simulation is carried out with a load center in the Guangdong-Hong Kong-Macao Greater Bay Area to verify the feasibility and effectiveness of the model and provide a reference for power grid planning.

Energy storage system (ESS) can provide services such as peak load shaving and valley load filling, short-term power support for the distribution system with a high percentage of new energy penetration. However, there are few studies on the location and capacity optimization of energy storage considering system reliability. Therefore, this paper first uses analytical methods to model the reliability of traditional equipment and ESS. Then the reliability indicators and calculation methods are proposed based on the charging and discharging efficiency of ESS. Overall optimization considering reliability and cost is the objective function, and genetic algorithm is used to optimize the location and capacity of ESS in the distribution network. Finally, the power distribution system of an industrial park in the south is taken as an example, simulation calculations are performed on Matlab. The reasonable layout of the ESS can reduce the average outage time decrease from 0.32 h/per each outage to 0.24 h/per each outage, which significantly improves the system reliability and verifies the effectiveness, technical and economic efficiency of the proposed model.

The large-capacity, centralized grid-side lithium battery energy storage power station is of positive significance for improving the system’s flexible regulation ability and safety and stability after the access of large-scale high-proportion new energy and large-capacity DC. To further study the response of large-scale lithium battery energy storage power stations connected to the power grid, this paper proposes an equivalent simulation method of large-capacity lithium battery energy storage power stations. Firstly, the main ideas and methods in the simulation of energy storage power station are summarized from four aspects: lithium battery pack modeling, parameters design of power conversion system (PCS) and converter transformer, control strategies and equivalent modeling method. Then, an equivalent model of 100 MW lithium battery energy storage power station based on the actual design parameters of the energy storage power station is built on the PSCAD. The simulation test results show that the equivalent energy storage power station model can maintain the basic characteristics of a single energy storage unit. Its control accuracy, response time, regulation time and switching time of charge and discharge are all within the relevant national standards, which make it capable of analyzing and simulating the external characteristics of large capacity energy storage power station on the side of grid connection, and can provide a reference model for related simulation research.

In the new power system with renewable energy as the main body, the electric energy storage system will face the urgent demand of more frequent energy interaction and larger capacities. The structural design model of axial gap optimized superconducting magnetic energy storage is established, and the concept design scheme of large-scale superconducting energy storage is formed. Compared with the traditional solenoidal magnet, the energy storage of the optimized magnet is improved by 30%, and the investment cost of unit energy storage is effectively reduced. Considering that the new energy applications demand of 330 times of energy storage charge and discharge per day, the equivalent battery storage capacity of 10.8 GJ/3 MWh scalable superconducting energy storage system reaches 495 MWh, and the total cost of superconducting energy storage will be lower than that of battery energy storage after 10 years of full-load operation. Therefore, the proposed superconducting energy storage system is expected to achieve lower energy storage capacity in the renewable energy based power system with frequent energy interaction demands.

Underwater compressed air energy storage (UWCAES) is a large-scale energy storage technology that can take advantage of hydro-static pressure in the deep ocean. Integrating the UWCAES into offshore wind power generation can store fluctuate and intermittent wind energy, so that the output power can be smoothed to satisfy the user electricity demand. In this paper, the physical model of the wind power generation and UWCAES integrated system has been built. Based on this model, the optimal nominal working condition has been determined under an ideal charge-store-discharge operation mode with the air storage pressure constraint. Then, in order to expand the working condition range, the air and thermal oil flow rate of UWCAES have been optimized under the variable working condition. Finally, an integrated system of a 3 MW×2 wind power and a 3 MW/45 MWh UWCAES have been tested under the real wind power and the user electricity demand data. Results show that, under the ideal charge-store-discharge operation mode, the integrated system can work within the range of 10% to 120%, and the round-trip efficiency is 48.1%~58.4%. Besides, the operation simulation under the real wind power and user load data also shows that, the integrated system round-trip efficiency is 53.7%, and the wind curtailment rate is declined to 0.58% and the load satisfaction ratio is promoted to 99.57%.

Building a new power system with new energy as the main body is an inevitable choice to promote the clean and low-carbon development of power. Realizing the full consumption of clean energy and meeting the flexible access needs of user side has become an important direction of new power system technology research. Firstly, this paper analyzes the advantages of new energy storage module in improving the power supply reliability of urban power grid, and analyzes the application scenario, technical and economic advantages of the energy storage module AC/DC distribution network. A new AC/DC energy storage system technical scheme is proposed, which can support diversified development and provide flexible and diverse energy orderly access services. Based on the new AC/DC distribution network physical framework of energy storage module, it can realize the flexible access of distributed energy and electric vehicles, meet the needs of AC/DC users such as data center, and provide stable, high-quality and reliable energy supply, and realize the cascade utilization of energy, effectively improve the voltage quality of the park, ensure the full consumption of clean energy, and reduce line loss and power cost. Finally, through the actual case of a new AC/DC energy storage system demonstration project in an area, the advantages and feasibility of this scheme are shown from the aspects of economic and social benefits. It provides reference and experience for realizing the goals of carbon peak and carbon neutralization, ensuring the security of energy supply, promoting the diversified and large-scale development of energy Internet industry, and building a new power system with new energy as the main body.

In order to solve the problem of integrated power and heat storage allocation, a power and heat storage configuration method of regional integrated energy system with wind power integration is proposed. Firstly, the dynamic neural network model of wind power prediction is constructed to effectively predict the wind farm output in the regional integrated energy system. Then, the charging and discharging energy behavior of power and heat storage in regional integrated energy system is analyzed, and the relationship among power storage, heat storage and regional wind farm power is established. Considering the coupling relationship between power and heat energy, a joint optimal configuration model of power and heat energy storage is built. Finally, with the actual data of a certain place is selected and three scenarios are set up, the prediction results are substituted into the optimization model to calculate the power and heat storage configuration. The comparison shows that the wind power prediction under this method has better effects, which is conducive to the optimal configuration of energy storage resources and reduce costs.

In view of various application scenarios of energy storage technology in power systems and the relationship among different stakeholders, a business model of third-party invested energy storage based on the concept of shared energy storage is proposed, and economic analysis method and optimization algorithm of energy storage power station under the business model are established. By comparing profits with the contract energy management and the two-part electricity price business model, the proposed business model has a better economy when the income sharing is reasonable. The impact of energy storage battery type and configuration capacity on the economics of energy storage power stations is further analyzed. The economy and effectiveness of the proposed business model are verified through the calculation case of Hangzhou power grid, which can promote the commercial process of the energy storage industry.

In order to improve the power quality and electricity consumption reliability while reducing the cost of electricity, this paper proposes a coordinated optimization of source-storage-load model and an improved strength Pareto evolutionary algorithm. First of all, the users’ energy storage system model is established, and the loads are classified according to whether they participate in demand response or not and how they participate in. Secondly, under the mechanism of time-of-use price and demand response, a multi-objective source-storage-load coordinated optimization model is established with the objectives of reducing the cost of electricity, modifying voltage offset and shortening the outage time at fault. In the established model, the con-straints of power balance, the state of charge of energy storage system and the allowed range of flexible load are considered comprehensively. Then, an optimization solving strategy is proposed based on improved strength Pareto evolutionary algorithm and the multi-objective fuzzy comprehensive evaluation decision method. Finally, the effectiveness of the proposed model is verified by a low-voltage network simulation example.

The integrated energy system can improve energy efficiency and promote the consumption of renewable energy. The further development of the integrated energy system requires the support of optimized operation technology, and reduces the overall operating cost by coordinating the energy consumption of various internal equipment in the electricity market. To fully tap the demand response potential of integrated energy system to participate in the interaction between market supply and demand, considering the change of energy efficiency ratio under different operation modes of ice-storage air-conditioning, an optimal operation method of integrated energy system with ice-storage air-conditioning is proposed. First, a general equipment operation model considering demand response is established, and refined modeling of ice-storage air-conditioners, gas turbines, batteries and other equipment are carried out. Then, an optimization method for the dispatch operation and demand response capacity of the integrated energy system under the market environment is proposed. And then, the proposed non-convex model is converted into a solvable mixed integer linear programming problem for solution. Finally, based on the actual operating data of the integrated energy system, the effectiveness of the proposed method is verified by simulation examples.

For typical parks with electricity/cooling/hydrogen demand, this paper proposes an optimal configuration model of hydrogen-ice energy storage microgrid considering solid oxide fuel cell (SOFC) waste heat recovery, which aims to optimize the capacity of main components such as wind/light/hydrogen/ice/storage in the microgrid, so as to improve the economy. Firstly, the AC/DC hybrid and source driving load directly of the dual energy storage mechanism of photovoltaic DC electrolytic water hydrogen storage and wind AC power ice storage is designed. In order to improve the utilization rate of hydrogen energy, it is proposed to use the waste heat recovery of SOFC for cogeneration of cold and electricity. Considering the nonlinearity of the model proposed in this paper, the changeable operation states of electrolyzer, ice storage and other equipment, and the problem that the optimization algorithm is easy to fall into local optimization and difficult to find global optimization, an ABC-QPSO algorithm with strong global search ability is proposed to solve the model. Finally, taking a park in Guangdong as an example, through the comparative analysis of four schemes, the superiority of the model proposed in this paper is verified.

A profit-based unit commitment model for a concentrated solar power (CSP) plant with a thermal energy storage system (TES) incorporating the component operating characteristics is proposed. The model considers three startup types and one shutdown type for the receiver and the power block and corresponding energy constraints. The model maximizes the operational profit of the plant by optimizing the commitment timing, thermal energy flows among the receivers, the thermal energy storage and the power block, and generation levels of the power block. Comparing with a traditional unit commitment model of system planning, the model includes more detailed operating constraints of thermal energy and power constraints in startup and shutdown processes and the solar irradiation conditions, in addition to arbitrage opportunity arisen from price variation. The model is tested in a one-week operating horizon at a time resolution of fifteen minutes. The results have shown that the optimized commitment decisions and operating levels are well matched with the resource availability and price patterns and imply that the model would be useful to the plant operator for operation planning.

In this paper, aiming at the inconsistency of decline law and short echelon service life of power batteries, an optimization method of residual value of retired batteries based on recession rate prediction is proposed. Firstly, based on the combination of grey prediction and least squares support vector machine, the historical usage data of batteries are mined to predict the decline rule of retired batteries, secondly, taking the highest utilization benefit of retired batteries as the objective function and considering the loss cost of retired batteries, the dynamic operation scheme of retired batteries in the whole life cycle is proposed. Finally, the rolling prediction is realized by using dynamic data. Taking a bus demonstration station in Yangtze River Delta as an example, the results show that the proposed method can effectively predict the decline law of batteries, and the revenue of retired batteries can be increased by 10%.

Aiming at the different attenuation degree and voltage of retired batteries in battery energy storage bank, a multi-paralleled retired battery-based energy storage bank and its control method under a new topology suitable for DC distribution network is proposed. Firstly, the droop characteristic of DC distribution network under multi-paralleled retired battery-based energy storage bank with droop control is analyzed. Then, a secondary voltage recovery control method based on discrete consensus algorithm is proposed to solve the bus voltage deviation caused by droop control and line resistance. Finally, the multiple retired battery-based energy storage banks are reorganized and distributed according to the global average state of health of retired batteries obtained by the discrete consensus algorithm. Single retired battery with good state of health (SOH) is selected to be put into the energy storage bank for priority output. In addition, based on the state of charge (SOC) distribution of the retired batteries, droop coefficient of DC/DC converter is adjusted. Therefore, the SoH optimization and SOC consistency between energy storage banks can be realized. The effectiveness of the proposed coordinated control method is verified by the simulation experiments of three retired battery-based energy storage banks in DC distribution network.