Multi-criteria PSO-based optimal design of grid-connected hybrid renewable energy systems. Issue 11 (1st September 2020)

• Record Type: Journal Article
• Authors: Mansouri Kouhestani, Fariborz; Byrne, James; Johnson, Daniel; Spencer, Locke; Brown, Bryson; Hazendonk, Paul; Scott, Jeremy
• Is Part Of: International journal of green energy. Volume 17:Issue 11(2020)
• Page Start: 617
• Page End: 631
• Publication Date: 2020-09-01
• Subjects: Solar photovoltaic (PV) -- wind turbine -- battery storage -- grid-connected hybrid renewable energy system -- particle swarm optimization; Power resources -- Research -- Periodicals; Energy industries -- Periodicals; Energy development -- Periodicals; 333.79
• DOI: 10.1080/15435075.2020.1779072
• Languages: English
• ISSNs: 1543-5075

Abstract

ABSTRACT: Human-induced climate change through the over liberation of greenhouse gases, resulting in devastating consequences to the environment, is a concern of considerable global significance which has fuelled the diversification to alternative renewable energy sources. The unpredictable nature of renewable resources is an impediment to developing renewable projects. More reliable, effective, and economically feasible renewable energy systems can be established by consolidating various renewable energy sources such as wind and solar into a hybrid system using batteries or back-up units like conventional energy generators or grids. The precise design of these systems is a critical step toward their effective deployment. An optimal sizing strategy was developed based on a heuristic particle swarm optimization (PSO) technique to determine the optimum number and configuration of PV panels, wind turbines, and battery units by minimizing the total system life-cycle cost while maximizing the reliability of the hybrid renewable energy system (HRES) in matching the electricity supply and demand. In addition, by constraining the amount of conventional electricity purchased from the grid, environmental concerns were also considered in the presented method. Various systems with different reliabilities and potential of reducing consumer's CO2 emissions were designed and the behavior of the proposed method was comprehensively investigated. An HRES may reduce the annualized cost of energy and carbon footprint significantly.