Optimization Strategy of Configuration and Scheduling for User-Side Energy Storage

Liu, Yushan; Liu, Qianqian; Guan, Huaimin; Li, Xiao; Bi, Dongxue; Guo, Yingjun; Sun, Hong

doi:10.3390/electronics11010120

Cited by 8 publications

(4 citation statements)

References 13 publications

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“…SOC min ≤ SOC(t) ≤ SOC max (7) where SOC min and SOC max are the minimum charge level and maximum residual charge level, respectively.…”

Section: Constraint Conditionmentioning

confidence: 99%

“…They also considered the energy storage investment cost, operation and maintenance, penalty costs for deviating from the planned output, and revenue from PV plants. Liu et al analyzed the influence of fluctuations of load power on the distribution network and proposed a model predictive control-based optimization strategy for energy storage allocation and scheduling with the goal of economic efficiency of user-side energy storage operation [7].…”

Section: Introductionmentioning

confidence: 99%

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Optimization Strategy of Hybrid Configuration for Volatility Energy Storage System in ADN

et al. 2022

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This study aims to address the issues of volatile energy access to the active distribution network (ADN), which are the difficulty of frequency regulation, the increased voltage deviation of the ADN, the decrease in operational security and stability, etc. In this study, a two-stage majorization configuration model is established to identify and understand how volatility energy affects a hybrid energy storage system (HESS). The ADN and HESS with lead-acid batteries and supercapacitors (SC) are examined using day forecast data for wind, solar, and load. In this planning stage, the integrated cost, network loss, and node voltage deviation are considered as optimal objectives in a multi-objective optimization model, while the revised multi-objective optimization particle swarm approach is used to solve the initial value of capacity configuration. In the operation stage, optimizing objectives like wind output power fluctuations, the frequency deviation of HESS is used to solve the modified value of the configuration capabilities of the SC, and the output of different types of units in ADN is further optimized by the quantum particle swarm with the addition of a chaotic mechanism. The simulation study is conducted to determine the best configuration result based on case 33 node examples, and the simulation results demonstrate the model’s viability.

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“…SOC min ≤ SOC(t) ≤ SOC max (7) where SOC min and SOC max are the minimum charge level and maximum residual charge level, respectively.…”

Section: Constraint Conditionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization Strategy of Hybrid Configuration for Volatility Energy Storage System in ADN

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Similarly, in [11,12], a weighted sum approach is utilized to unify objectives such as power loss, load fuctuation, and voltage fuctuation in optimal operation strategies for distribution networks with distributed renewable energy sources. In [13], a model predictive control-based scheduling method for user-side energy storage is proposed, optimizing control with the objective of economic efciency. In [14], a fuzzy control method is employed to dynamically adjust the weight coefcients of multiple objectives, forming an energy management strategy for hybrid oil-electric systems and achieving global optimal control.…”

Section: Introductionmentioning

confidence: 99%

The Multiobjective Control Based on Tolerance Optimization in a Multienergy System

Ma,

Li,

Jiang

et al. 2024

International Transactions on Electrical Energy Systems

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To address the issue of multiobjective control in multienergy systems with diverse operational objectives, a two-stage optimization framework based on expected point tolerance has been proposed in this paper. In the first stage, a single objective function is used for optimization control to obtain the expected point of the multiobjective optimization problem. Then, in the second stage, by defining the allowable deviation between each optimization objective and the expected point, the original multiobjective optimization problem is transformed into a single objective optimization problem solution with tolerance measurement. Finally, in the simulation scene of a multienergy system, it is demonstrated that compared with the optimal results under each single objective method, the proposed method increases power line loss, maximum voltage deviation, new energy consumption, and economy by 2.22, 2.30, 1.02, and 2.45 times, respectively. Compared with the suboptimal results, the proposed method reduces power line loss by 22.26, 1.74, 1.09, and 0.97 times, respectively. Combining the shape of the Pareto frontier, it is demonstrated that the proposed method can comprehensively consider the needs of multiple power optimization objectives for forming a more reasonable and effective system optimization scheduling and also provide a new approach for solving multiobjective optimization problems.

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“…Ref. [7] constructed a rolling optimization method for a user-side ESS operation allocation for the intraday and the month-ahead. Tatsuya et al constructed a model of a grid-connected photovoltaic (PV) renewable generation station (RGS) incorporating the HSS by [8], which analyses the intercoupling between different PV capacities, the system cost, and greenhouse effect gas emissions, showing that the HSS has the economic advantage of an ESS for long periods of time.…”

Section: Introductionmentioning

confidence: 99%

A Transaction Model and Profit Allocation Method of Multiple Energy Storage Oriented to Versatile Regulation Demand

Zhi,

Xue,

et al. 2023

Sustainability

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This study proposes a day-ahead transaction model that combines multiple energy storage systems (ESS), including a hydrogen storage system (HSS), battery energy storage system (BESS), and compressed air energy storage (CAES). It is catering to the trend of a diversified power market to respond to the constraints from the insufficient flexibility of a high-proportion renewable energy system (RES). The model is a double-layer game based on the Nash–Stackelberg–cooperative (N–S–C) game. Multiple users in the upper layer form the Nash game with the goal of maximizing their own benefits, while the multiple ESSs in the lower layer form a cooperative game with the goal of maximizing the overall benefits; the two layers form a Stackelberg game. Moreover, an allocation mechanism is proposed to balance the overall and individual rationality and promote the sustainable development of multiple ESSs, considering the operational characteristics. A numerical simulation is carried out using the rationality and effectiveness of the proposed model, which is based on data from the renewable energy gathering area in northwest China. The results show that this strategy shortens the energy storage payback period and improves the energy storage utilization. The simulation results indicate that small-scale energy storage with a rated power of less than 18 MWh does not have a price advantage, indicating the need to improve the configuration capacity of energy storage in the future from decentralized energy storage to independent/shared energy storage.

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Optimization Strategy of Configuration and Scheduling for User-Side Energy Storage

Cited by 8 publications

References 13 publications

Optimization Strategy of Hybrid Configuration for Volatility Energy Storage System in ADN

Optimization Strategy of Hybrid Configuration for Volatility Energy Storage System in ADN

The Multiobjective Control Based on Tolerance Optimization in a Multienergy System

A Transaction Model and Profit Allocation Method of Multiple Energy Storage Oriented to Versatile Regulation Demand

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