Comparison of optimization frameworks for the design of a multi-energy microgrid
| Autor: | Sean Ooi Chea Wae, Remy Rigo-Mariani, Alessandro Romagnoli, Stefano Mazzoni |
|---|---|
| Přispěvatelé: | Laboratoire de Génie Electrique de Grenoble (G2ELab ), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), G2Elab-SYstèmes et Réseaux ELectriques (G2Elab-SYREL), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Nanyang Technological University, Energy Research Institute at NTU (ERIAN), Nanyang Technological University [Singapour], School of Mechanical and Aerospace Engineering, Energy Research Institute @ NTU (ERI@N), Rigo-Mariani, Rémy |
| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
Mathematical problem Optimization problem Computer science 020209 energy Evolutionary algorithm 02 engineering and technology Management Monitoring Policy and Law 7. Clean energy Net present value Reduction (complexity) Cogeneration 020401 chemical engineering 0202 electrical engineering electronic engineering information engineering Quadratic programming 0204 chemical engineering ComputingMilieux_MISCELLANEOUS Mechanical Engineering [SPI.NRJ]Engineering Sciences [physics]/Electric power Building and Construction General Energy Mixed Integer Linear Programming Mechanical engineering [Engineering] Evolutionary Algorithms Microgrid [SPI.NRJ] Engineering Sciences [physics]/Electric power |
| Zdroj: | Applied Energy Applied Energy, Elsevier, 2020, 257, pp.113982 HAL |
| ISSN: | 0306-2619 |
| DOI: | 10.1016/j.apenergy.2019.113982 |
| Popis: | The scope of the paper is to investigate different strategies for the design of a multi-energy system considered as a systemic optimization problem. The objective is to determine the best sizes of the energy assets such as electrochemical and thermal storages, cogeneration units, solar generators and chillers. In these cases, the techno-economic optimization is a tradeoff between the operating costs and the capital expenditures in the form of integrated management and design of the system. The paper addresses the challenges of these optimization problems in two steps. The former implements generic piecewise linearization techniques based on non-linear models. That approach allows a significant reduction of the computational time for the management loop of the assets (i.e. optimal power dispatch). The latter takes into consideration the integration of that management loop in different architectures for optimal system planning. The main contribution of the paper toward filling the gap in the literature is to investigate a wide range of optimization frameworks - with bi-level optimizations (using both deterministic and evolutionary methods), Monte-Carlo simulations as well as a performant ‘all-in-one’ approach in which both sizes and controls are variables of a single mathematical problem formulation. Finally, a thorough results analysis highlights that the best solution tends to be the same whether the objective to optimize is the traditional net present value at the end of the system lifespan or the total yearly cost of ownership. National Research Foundation (NRF) NRF Award No.: NRF-ENIC-SERTD-SMES-NTUJTCI3C-2016 |
| Databáze: | OpenAIRE |
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