Wind and Solar Based Multi-Objective Hydro-Thermal Scheduling Using Chaotic-Oppositional Whale Optimization Algorithm

In multi-objective hydro-thermal scheduling (HTS), the hydro and thermal units are arranged to reduce the cost of generation and emission simultaneously. The wind and solar are incorporated with hydro-thermal to get reliable electricity generation at the lowest price with low emission. Whale optimiz...

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Vydáno v:	Electric power components and systems Ročník 51; číslo 6; s. 568 - 592
Hlavní autoři:	Paul, Chandan, Roy, Provas Kumar, Mukherjee, V.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Philadelphia Taylor & Francis 03.04.2023 Taylor & Francis Ltd
Témata:	Algorithms Basic converters chaotic-oppositional whale optimization algorithm (COWOA) Convergence Cost function Emissions control hydro-thermal scheduling (HTS) hydro-thermal-wind-solar scheduling (HTWSS) Minimum cost Multiple objective analysis Optimization Optimization algorithms Optimization techniques overestimation Scheduling Solar power generation Solar radiation Test systems underestimation Wind speed
ISSN:	1532-5008, 1532-5016
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Abstract	In multi-objective hydro-thermal scheduling (HTS), the hydro and thermal units are arranged to reduce the cost of generation and emission simultaneously. The wind and solar are incorporated with hydro-thermal to get reliable electricity generation at the lowest price with low emission. Whale optimization algorithm (WOA) has been developed as an optimization technique which works on whales' hunting behavior. However, WOA has slow convergence rate and experiences premature convergence, just like other optimization methods. Thus, chaotic-oppositional learning is combined with WOA in the suggested chaotic oppositional WOA (COWOA) technique for boosting the performance and convergence speed of the basic WOA. The first test system consists of four hydro and three thermal units, whereas for the second test system, one wind unit, and one solar unit are incorporated with four hydro and one thermal generating units. In the cost model, the improbability of wind and solar power generation is considered. It includes power imbalance terms like overestimation and underestimation cost. The suggested COWOA method is applied to handle the nonlinearity of the cost function due to valve-point loading and improbability aspect as both solar radiation and wind speed are unpredictable. The simulation results demonstrate that COWOA provides superior results in terms of minimum cost of fuel, least emission, and least convergence time. Moreover, it is observed that after incorporating wind and solar units with hydro-thermal, the total cost and emission get reduced significantly as compared to conventional HTS.
AbstractList	In multi-objective hydro-thermal scheduling (HTS), the hydro and thermal units are arranged to reduce the cost of generation and emission simultaneously. The wind and solar are incorporated with hydro-thermal to get reliable electricity generation at the lowest price with low emission. Whale optimization algorithm (WOA) has been developed as an optimization technique which works on whales’ hunting behavior. However, WOA has slow convergence rate and experiences premature convergence, just like other optimization methods. Thus, chaotic-oppositional learning is combined with WOA in the suggested chaotic oppositional WOA (COWOA) technique for boosting the performance and convergence speed of the basic WOA. The first test system consists of four hydro and three thermal units, whereas for the second test system, one wind unit, and one solar unit are incorporated with four hydro and one thermal generating units. In the cost model, the improbability of wind and solar power generation is considered. It includes power imbalance terms like overestimation and underestimation cost. The suggested COWOA method is applied to handle the nonlinearity of the cost function due to valve-point loading and improbability aspect as both solar radiation and wind speed are unpredictable. The simulation results demonstrate that COWOA provides superior results in terms of minimum cost of fuel, least emission, and least convergence time. Moreover, it is observed that after incorporating wind and solar units with hydro-thermal, the total cost and emission get reduced significantly as compared to conventional HTS.
Author	Paul, Chandan Mukherjee, V. Roy, Provas Kumar
Author_xml	– sequence: 1 givenname: Chandan orcidid: 0000-0002-2202-2900 surname: Paul fullname: Paul, Chandan organization: Electrical Engineering Department, Dr. B C Roy Engineering College – sequence: 2 givenname: Provas Kumar orcidid: 0000-0002-3433-5808 surname: Roy fullname: Roy, Provas Kumar organization: Electrical Engineering Department, Kalyani Government Engineering College – sequence: 3 givenname: V. orcidid: 0000-0002-9275-8761 surname: Mukherjee fullname: Mukherjee, V. organization: Electrical Engineering Department, IIT (ISM) Dhanbad
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SubjectTerms	Algorithms Basic converters chaotic-oppositional whale optimization algorithm (COWOA) Convergence Cost function Emissions control hydro-thermal scheduling (HTS) hydro-thermal-wind-solar scheduling (HTWSS) Minimum cost Multiple objective analysis Optimization Optimization algorithms Optimization techniques overestimation Scheduling Solar power generation Solar radiation Test systems underestimation Wind speed
Title	Wind and Solar Based Multi-Objective Hydro-Thermal Scheduling Using Chaotic-Oppositional Whale Optimization Algorithm
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