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CC BY V4.0, Open Access
Journal article
Intelligent Management of Integrated Energy Systems with a Stochastic Multi-Objective Approach with Emphasis on Demand Response, Energy Storage Devices, and Power-to-Gas
Sustainability, Vol.17(7), 3001
2025
Abstract
Optimal scheduling of integrated PV/wind energy systems (IESs) is a complex task that requires innovative approaches to address uncertainty and improve efficiency. This paper proposes a novel multi-objective optimization framework for IES operation, incorporating demand response (DR), a comprehensive set of components, and innovative techniques to reduce computational complexity. The proposed framework minimizes total losses, cost, and emissions while meeting energy demands, offering significant advantages in terms of sustainability and cost reduction. The optimization model is implemented using steady-state energy analysis and non-dominated sorting genetic algorithm-III (NSGA-III) heuristic optimization, while uncertainty analysis and scenario reduction techniques enhance computational efficiency. To further reduce the computational burden, the proposed framework incorporates a novel clustering strategy that effectively reduces the number of scenarios from 1000 to 30. This innovation significantly improves the computational efficiency of the proposed framework, making it more practical for real-world applications. The effectiveness of the proposed approach is validated against multi-objective seagull optimization algorithm (MOSOA)- and general algebraic modeling system (GAMS)-based methods, demonstrating its superior performance in various scenarios. The improved management system, enabled by the proposed algorithms, facilitates informed operational decisions, enhancing the system’s installed capacity and overall flexibility. This optimization framework paves the way for more efficient and sustainable operation of integrated PV/wind energy systems. Reducing gas and heat network losses, considering both electric and thermal load response, simultaneously utilizing electricity, gas, and heat storage devices, and introducing a new clustering strategy to reduce scenarios are the specific innovations that are mentioned in this paper.
Details
- Title
- Intelligent Management of Integrated Energy Systems with a Stochastic Multi-Objective Approach with Emphasis on Demand Response, Energy Storage Devices, and Power-to-Gas
- Authors/Creators
- Hossein Faramarzi - Imam Khomeini International UniversityNavid Ghaffarzadeh - Imam Khomeini International UniversityFarhad Shahnia - Murdoch University, Centre for Water, Energy and Waste
- Publication Details
- Sustainability, Vol.17(7), 3001
- Publisher
- MDPI AG
- Number of pages
- 27
- Identifiers
- 991005765131807891
- Copyright
- © 2025 by the authors.
- Murdoch Affiliation
- School of Engineering and Energy
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International collaboration
- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.18 Power Systems & Electric Vehicles
- 4.18.204 Smart Grid Optimization
- Web Of Science research areas
- Environmental Sciences
- Environmental Studies
- Green & Sustainable Science & Technology
- ESI research areas
- Environment/Ecology