In this study, the combination of crossover algorithm and particle swarm optimization—crossover algorithm-particle swarm optimization (CS-PSO) algorithm—to optimize photovoltaic hybrid energy storage scheduling, improving global search and convergence speed, is discussed.
This paper proposes a multi-time scale optimization scheduling method for an IES with hybrid energy storage under wind and solar uncertainties. Firstly, the proposed system framework of an IES including electric-thermal-hydrogen hybrid energy storage is established.
Provided by the Springer Nature SharedIt content-sharing initiative This paper proposes a deep reinforcement learning-based framework for optimizing photovoltaic (PV) and energy storage system scheduling. By modeling the co
Overall, in view of the photovoltaic energy storage system, the scheduling results indirectly benefit each unit. Table IV shows that maintenance costs remain stable, fuel costs decrease, and electricity sales increase. Therefore, in terms of the total lifecycle cost, this method has higher economic benefits than moth flame optimization. TABLE IV.
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Addressing the issues of volatility and uncertainty in the output of new energy sources such as PV power, a multi-timescale optimized scheduling strategy for a combined …
This paper proposed an IES integrated with electricity, heat, and fuel multi-energy storage, and the capacities of components were optimized by considering their energy …
In this study, the combination of crossover algorithm and particle swarm optimization—crossover algorithm-particle swarm …
In this study, the combination of crossover algorithm and particle swarm optimization—crossover algorithm-particle swarm optimization (CS-PSO) algorithm—to …
The rapid growth of renewable energy integration has fundamentally transformed modern power systems, driving an increasing demand for diverse energy storage solutions. While this …
This paper proposes a deep reinforcement learning-based framework for optimizing photovoltaic (PV) and energy storage system scheduling. By modeling the control …
This paper focuses on power system scheduling problems, aiming to enhance energy utilization efficiency through multi-energy complementarity. To support the “dual-carbon” strategic goals, …
Multi-Time-Scale Optimal Scheduling of Integrated Energy System with Electric-Thermal-Hydrogen Hybrid Energy Storage Under Wind and Solar Uncertainties
However, a scalable and generalizable design framework for such systems remains lacking. Here, we propose a general and scenario-adaptive design framework for …
ABSTRACT Due to the volatility and uncertainty of renewable energy, a significant amount of wind and solar power is wasted. With the increasing maturity of battery manufacturing, the …
With the increasing penetration of renewable energy sources, the uncertainty in power generation systems has intensified, necessitating the comprehensive utilization of …
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