EconPapers    
Economics at your fingertips  
 

Multiobjective Scheduling of Hybrid Renewable Energy System Using Equilibrium Optimization

Salil Madhav Dubey, Hari Mohan Dubey, Manjaree Pandit and Surender Reddy Salkuti
Additional contact information
Salil Madhav Dubey: Department of Electrical Engineering, Madhav Institute of Technology & Science, Gwalior 474005, India
Hari Mohan Dubey: Department of Electrical Engineering, Birsa Institute of Technology, Dhanbad 828123, India
Manjaree Pandit: Department of Electrical Engineering, Madhav Institute of Technology & Science, Gwalior 474005, India
Surender Reddy Salkuti: Department of Railroad and Electrical Engineering, Woosong University, Daejeon 34606, Korea

Energies, 2021, vol. 14, issue 19, 1-20

Abstract: Due to increasing concern over global warming, the penetration of renewable energy in power systems is increasing day by day. Gencos that traditionally focused only on maximizing their profit in the competitive market are now also focusing on operation with the minimum pollution level. The paper proposes a multiobjective model capable of finding a set of trade-off solutions for the joint optimization problem, considering the cost of reserve and curtailment of power from renewable sources. Managing a hybrid power system is a challenging task due to its stochastic nature mixed with the objective function and complex practical constraints associated with it. A novel metaheuristic Equilibrium Optimizer (EO) algorithm incepted in the year 2020 utilizes the concept of control volume and mass balance for finding equilibrium state is proposed here for computing the optimal schedule and impact of renewable energy integration on profit and emission for different optimization objectives. In this paper, EO has shown dominant performance over well-established metaheuristic algorithms such as particle swarm optimizer (PSO) and artificial bee colony (ABC). In addition, EO produces well-distributed Pareto-optimal solutions and the fuzzy min-ranking is used as a decision maker to acquire the best compromise solution.

Keywords: multi-objective; renewable energy; profit-based scheduling; Equilibrium Optimizer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/19/6376/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/19/6376/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:19:p:6376-:d:650384

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6376-:d:650384