Multi-objective-based robust unit commitment using hydro-thermal-wind: a hybrid technique

Abstract

Purpose The purpose of this paper is to solve economic emission dispatch problem in connection of wind with hydro-thermal units. Design/methodology/approach The proposed hybrid methodology is the joined execution of both the modified salp swarm optimization algorithm (MSSA) with artificial intelligence technique aided with particle swarm optimization (PSO) technique. Findings The proposed approach is introduced to figure out the optimal power generated power from the thermal, wind farms and hydro units by minimizing the emission level and cost of generation simultaneously. The best compromise solution of the generation power outputs and related gas emission are subject to the equality and inequality constraints of the system. Here, MSSA is used to generate the optimal combination of thermal generator with the objective of minimum fuel and emission objective function. The proposed method also considers wind speed probability factor via PSO-artificial neural network (ANN) technique and hydro power generation at peak load demand condition to ensure economic utilization. Originality/value To validate the advantage of the proposed approach, six- and ten-units thermal systems are studied with fuel and emission cost. For minimizing the fuel and emission cost of the thermal system with the predicted wind speed factor, the proposed approach is used. The proposed approach is actualized in MATLAB/Simulink, and the results are examined with considering generation units and compared with various solution techniques. The comparison reveals the closeness of the proposed approach and proclaims its capability for handling multi-objective optimization problems of power systems.

A Comprehensive Review on Evolutionary Optimization Techniques Applied for Unit Commitment Problem

“…A new multi-objective, hybrid combined technique of Modified Salp Swarm Algorithm (MSSA) and ANN, assisted with PSO, was proposed to solve EED problem, related to hydro, wind and thermal units [241]. The optimal combination of the thermal generator unit was created by MSSA, with the customary objective functions like minimum fuel and emission.…”

Stochastic Unit Commitment Problem, Incorporating Wind Power and an Energy Storage System

“…Thus, today's power system operators extended the classical models of several problems in order to consider the intermittency of WP [4]. The unit commitment problem (UCP) of wind energy has been one of the most studied problems over the last few years [5][6][7][8]. The UCP aims to determine which units have to be committed/uncommitted from an economic perspective [9].…”

A new operation strategy of PEV parking and hydro storage in smart grid environment

“…Robust unit commitment with considerations for conventional and DGs (wind power) is solved in Jain and Huddar (2019).…”

“…As a summary, according to literature (Yang et al , 2017; Tumuluru and Tsang, 2018; Howlader et al , 2018; Azari et al , 2018; Howlader et al , 2018; Goya et al , 2012; Kyoho et al , 2013; Goya et al , 2010; Imani et al , 2018; Shahinzadeh et al , 2017; Sadeghian and Wang, 2017; Saber and Venayagamoorthy, 2010; Saber and Venayagamoorthy, 2012; Zhang et al , 2015; Madzharov et al , 2014; Goleijani et al , 2013; Liu et al , 2012; Bahreyni et al , 2012; Yu et al , 2013; Khodayar et al , 2012; Abdollahi et al , 2012; Zhang et al , 2016; Kumar et al , 2017; Howlader et al , 2016; Hua et al , 2017; Peng et al , 2017; Deepak et al , 2019; Jain and Huddar, 2019), the impacts of PEV parking and hydro storage on smart grid scheduling are not studied (Table 1).…”