Solution of short term integrated hydrothermal-solar-wind scheduling using sine cosine algorithm. (March 2022)

• Record Type: Journal Article
• Authors: Dasgupta, Koustav; Roy, Provas Kumar; Mukherjee, Vivekananda
• Is Part Of: Energy strategy reviews. Volume 40(2022)
• Publication Date: 2022-03
• Subjects: Hydrothermal scheduling -- Sine cosine algorithm -- Solar energy -- Wind energy; BSA Backtracking search algorithm -- QOLTLBO Quasi-oppositional learning based TLBO -- CEES Combined economic emission scheduling -- QEA Quantum-inspired evolutionary algorithm -- DE Differential evolution -- RES Renewable energy sources -- ELS Economic load scheduling -- RCCRO Real coded chemical reaction optimization -- EES Economic emission scheduling -- RCGA Real coded GA -- HTS Hydrothermal scheduling -- SCA Sine cosine algorithm -- HTSWS Hydrothermal-solar-wind scheduling -- SPSO Small population-based PSO -- IMM Improved Mühlenbein mutation -- TLBO Teaching-learning based optimization -- MDE Modified DE -- WA Whale algorithm -- PSO Particle swarm optimization; Energy policy -- Periodicals; 333.7905
• DOI: 10.1016/j.esr.2022.100824
• Languages: English
• ISSNs: 2211-467X

Abstract

Abstract: The combined scheduling of hydro, thermal and hybrid energy ( i.e., wind and solar) is attracting more and more attention nowadays. This paper explores the contribution of renewable energy sources in the traditional hydrothermal scheduling problem in order to overcome the prevailing issues like high generation cost and more emissive particles of fuel. This paper presents a new wind-solar based generation scheduling model that reduces the aforementioned issues. The proposed hydrothermal-solar-wind scheduling (HTSWS) model is very effective. It can reduce the price rate of generation and different emissive particles of fuel of the traditional scheduling model. A solution approach i.e., robust sine cosine algorithm (SCA) is employed to determine the minimum generation cost and fuel emission based best generating schedule for traditional scheduling problem. The same approach has been carried out in the context of the suggested HTSWS problems. The different control parameters of the SCA have been properly utilized to balance the exploration and the exploitation phases. These parameters lead to determination of the near-optimal global solution. The results show that the combined application of renewable sources and hydrothermal units benefit both economic and emission goals of the utility houses with operating costs and pollutant emissions falling by 10% and 64%, respectively. Here, another two powerful algorithms ( i.e., backtracking search algorithm and whale algorithm) have also been applied to determine the minimum values of generation cost, emission, and combined generation cost-emission. Effectiveness and robustness of the proposed algorithm have been presented by comparing the SCA based results with other established latest algorithms for the considered problems. Highlights: A new wind and solar integrated hydrothermal scheduling (HTS) model has been presented. Utility of hybrid energy ( i.e. wind and solar energy) has been proposed. Different complexity of constraints have been properly handled in hydrothermal-solar-wind scheduling (HTSWS) problem. A novel SCA technique has been considered to solve HTS and HTSWS problems. Effectiveness of proposed HTSWS model and methodology have been presented.