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Decarbonizing the grid by optimal scheduling of solar PV-wind turbine-pumped hydro storage considering application on heuristic algorithms: A comprehensive review

期刊

INTERNATIONAL JOURNAL OF ENERGY RESEARCH
卷 45, 期 13, 页码 18473-18497

出版社

WILEY
DOI: 10.1002/er.7036

关键词

distribution generation; optimization techniques; pumped hydro storage; SPV system; wind turbine power

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Distributed generation has great potential, but requires optimization for optimal configuration; deploying in unfavorable locations can lead to problems; the paper covers various renewable energy generation technologies such as solar PV, wind power, and pumped hydro storage systems.
The potential for distributed generation (DG) to minimize power loss, increase productivity, lower investment costs, and, most significantly, the ability to leverage renewable energy resources such as wind, photovoltaic (PV), and microturbines, which generate power with low greenhouse-gas emissions, has piqued interest in the power sector. Deploying DG in an unfavorable location can result in a slew of problems, including increased system failures and costs, voltage spikes and swings, and stability and resilience issues. As a result, an optimization or perceptual technique-based paradigm is needed to identify the optimal configuration of distributed renewable energy generation for a given system that can provide fiscal, environmental, and technological benefits. Several researchers looked at the best possible location for distributed renewable generation based on their needs and goals. The formal theory for this issue, however, remains unsolved. Individual studies on solar PV systems, types of solar PV systems, wind power generation, and pumped hydro storage systems are all covered in detail in this paper. In addition, the study focuses on a variety of optimization techniques and algorithms for providing a better perspective on resolving issues related to the integration and functionality of many renewable resources in an islanded as well as grid-connected environment. The heuristic algorithms are explained with respective flow charts individually. Finally, a comparative analysis has been carried out in order to understand and validate the usefulness of individual optimization techniques with itself and others.

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