A Two-Layer Cooperative Optimization Approach for Coordinated Photovoltaic-Energy Storage System Sizing and Factory Energy Dispatch Under Industrial Load Profiles

Sustainability, Journal Year: 2025, Volume and Issue: 17(6), P. 2713 - 2713

Published: March 19, 2025

Driven by policy incentives and economic pressures, energy-intensive industries are increasingly focusing on energy cost reductions amid the rapid adoption of renewable energy. However, existing studies often isolate photovoltaic-energy storage system (PV-ESS) configurations from detailed load scheduling, limiting industrial park management. To address this, we propose a two-layer cooperative optimization approach (TLCOA). The upper layer employs genetic algorithm (GA) to optimize PV capacity sizing through natural selection crossover operations, while lower utilizes mixed integer linear programming (MILP) derive cost-minimized scheduling strategies under time-of-use tariffs. Multi-process parallel computing accelerates fitness evaluations, resolving high-dimensional data challenges. is introduced accelerate effectively addressing challenges posed data. Validated with real power market data, TLCOA demonstrated adaptation fluctuations achieving 23.68% improvement in computational efficiency, 1.73% reduction investment costs, 7.55% decrease purchase 8.79% enhancement utilization compared traditional methods. This integrated framework enables cost-effective PV-ESS deployment adaptive management facilities, offering actionable insights for integration scalable optimization.

Language: Английский

A Review of Battery Energy Storage Optimization in the Built Environment

Batteries, Journal Year: 2025, Volume and Issue: 11(5), P. 179 - 179

Published: May 2, 2025

The increasing adoption of renewable energy sources necessitates efficient storage solutions, with buildings emerging as critical nodes in residential systems. This review synthesizes state-of-the-art research on the role batteries settings, emphasizing their diverse applications, such for photovoltaic systems, peak shaving, load shifting, demand response, and backup power. Distinct from prior studies, our work provides a structured framework categorizing battery spanning individual use, shared communities, examines modeling techniques like State Charge estimation degradation analysis. Highlighting integration infrastructures, we explore multi-objective optimization strategies hierarchical decomposition methods effective utilization. findings underscore that advanced management systems technological innovations are aimed at extending life enhancing efficiency. Finally, identify knowledge gaps propose directions future research, focus scaling applications to meet operational, economic, environmental objectives. By bridging theoretical insights practical this contributes advancing understanding within transition.

Language: Английский

Research on Optimal Scheduling Strategy of Differentiated Resource Microgrid with Carbon Trading Mechanism Considering Uncertainty of Wind Power and Photovoltaic

Energies, Journal Year: 2024, Volume and Issue: 17(18), P. 4633 - 4633

Published: Sept. 16, 2024

Accelerating the green transformation of power system is inevitable path energy revolution; increasing installed capacity new and penetration rate electricity, uncertainty regarding output, rising proportion distributed supply access have led to threat against safe stable operation current system. With on both sides demand, microgrid (MG) needed effectually aggregate, coordinate, optimize resources, such as adjustable supply, storage in a certain area demand side. Therefore, this paper, wind PV first dealt with by Latin hypercube sampling (LHS). Secondly, differentiated resources MG region can be divided into storage. Adjustable are classified according response characteristics. At same time, operating cost carbon trading mechanism (CTM) comprehensively considered. Finally, low-carbon economy optimal scheduling strategy lowest total optimization goal formed. Then, order verify effectiveness proposed algorithm, three different scenarios established for comparison. The algorithm reduced about 30%, amount 24 h reach nearly 600 kg, bringing economic social benefits MG.

Language: Английский