Optimized Battery Capacity Allocation Method for Wind Farms with Dual Operating Conditions

Sustainability, Journal Year: 2024, Volume and Issue: 16(9), P. 3615 - 3615

Published: April 25, 2024

In order to solve the problems of wind power output volatility and participation in frequency regulation, a method for optimizing capacity allocation farm storage batteries based on dual grouping strategy considering simultaneous execution conditions energy fluctuation smoothing primary regulation is proposed. Firstly, two-layer model established optimize under operating conditions, i.e., planning layer takes into account lifetime, cost, benefit, operation considers turbine reserve backup control participate cooperative manner. Then, battery pack embedded with variational modal decomposition determine charging discharging after grid-optimized reference power. An improved particle swarm algorithm inverse learning pre-optimization combined crossover post-optimization GUROBI computation obtain optimal scheme. Finally, superiority proposed this paper terms improving utilization, service life, economic efficiency as well reducing load shedding verified by comparing it single working condition scenario traditional strategy.

Language: Английский

Large-Scale Optimization among Photovoltaic and Concentrated Solar Power Systems: A State-of-the-Art Review and Algorithm Analysis

Energies, Journal Year: 2024, Volume and Issue: 17(17), P. 4323 - 4323

Published: Aug. 29, 2024

Large-scale optimization (LSO) problems among photovoltaic (PV) and concentrated solar power (CSP) systems are attracting increasing attention as they help improve the energy dispatch efficiency of PV CSP to minimize costs. Therefore, it is necessary urgent systematically analyze summarize various LSO methods showcase their advantages disadvantages, ensuring efficient operation hybrid comprising different systems. This paper compares analyzes latest for based on meta-heuristic algorithms (i.e., Particle Swarm Optimization, Genetic Algorithm, Enhanced Gravitational Search Grey Wolf Optimization), numerical simulation stochastic Constraint Programming, Linear Dynamic Programming Optimization Derivative-Free machine learning-based AI (Double Grid Support Vector Machine, Long Short-Term Memory, Kalman Filter, Random Forest). An in-depth analysis A comparison essence applications these conducted explore characteristics suitability or The research results demonstrate specificities algorithms, providing valuable insights researchers with diverse interests guiding selection most appropriate method solution algorithm in also offers useful references suggestions extracting challenges proposing corresponding solutions guide future development.

Language: Английский

Research on the optimal capacity configuration of green storage microgrid based on the improved sparrow search algorithm

Frontiers in Energy Research, Journal Year: 2024, Volume and Issue: 12

Published: May 3, 2024

Green storage plays a key role in modern logistics and is committed to minimizing the environmental impact. To promote transformation of traditional green storage, research on capacity allocation wind-solar-storage microgrids for proposed. Firstly, this paper proposes microgrid configuration model, secondly takes shortest payback period as objective function, uses improved sparrow search algorithm (ISSA) optimization. Logistic-Tent compound chaotic mapping method added population initialization (SSA). Secondly, adaptive t-distribution mutation used improve discoverer, overall optimization ability improved. Finally, hybrid decreasing strategy adopted process vigilance position update. The ISSA can efficiency algorithm, avoid premature convergence enhance robustness which helpful better apply optimal storage. By analyzing results two typical days, system adapt dynamic requirements flexibility sustainability supply chain.

Language: Английский