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Developing a multi-objective multi-layer model for optimal design of residential complex energy systems

Davoudi, M ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1016/j.ijepes.2021.107889
  3. Publisher: Elsevier Ltd , 2022
  4. Abstract:
  5. Optimal planning of residential complex energy systems requires thorough mathematical modelling to address the interconnections between all the energy installations from the largest ones, shared by all the residents, to the smallest ones in each distinct unit. Besides, conflicting desires of investors and residents in various aspects such as reliability index make this problem more challenging. In response, this paper presents a thorough framework to obtain the optimum design and operation of a residential complex energy system from scratch. To address the appropriate interconnection between various components of such an energy system, a multi-layer energy hub structure is proposed. Besides, the proposed optimization problem consists of a multi-objective function to consider several criteria such as reliability, operational costs, and investment costs to address both investors’ and residents’ desires appropriately. A Multi-objective Particle Swarm Optimization (MOPSO) algorithm is implemented to obtain the optimum solutions for the developed optimization problem, and a set of Pareto optimal solutions are introduced. By doing so, investors can accurately analyse the interrelation among different objectives such as reliability, investment costs, and operational costs of the residential complex and choose an optimum solution based on their priorities. To demonstrate the effectiveness of the proposed method, it is applied to a case study consisting of a residential energy system with 300 units. The numerical results indicate that such a framework not only reduces total operation and investments costs by 24% but also increases reliability, continuity of energy supply, significantly in comparison to other common methods such as single-layer EH and single-objective EH planning frameworks. © 2021 Elsevier Ltd
  6. Keywords:
  7. Energy Hub ; MOPSO algorithm ; Multi-layer ; Residential complex ; Housing ; Investments ; Multiobjective optimization ; Numerical methods ; Optimal systems ; Pareto principle ; Particle swarm optimization (PSO) ; Complex energy systems ; Energy hub planning ; Energy hubs ; Integrated energy systems ; Investment costs ; Multi-layers ; Multi-objective particle swarm optimization algorithms ; Optimization problems ; Residential complexes ; Reliability
  8. Source: International Journal of Electrical Power and Energy Systems ; Volume 138 , 2022 ; 01420615 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0142061521011030