Volume 18, Issue 1 (March 2022)                   IJEEE 2022, 18(1): 2180-2180 | Back to browse issues page

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Paliwal P. Securing Reliability Constrained Technology Combination for Isolated Micro-Grid Using Multi-Agent Based Optimization. IJEEE 2022; 18 (1) :2180-2180
URL: http://ijeee.iust.ac.ir/article-1-2180-en.html
Abstract:   (2135 Views)
The determination of a suitable technology combination for an isolated micro-grid (IMG) based on hybrid renewable energy resources (HRES) is a challenging task. The intermittent behavior of RES leads to an adverse impact on system reliability and thus complicates the planning process. This paper proposes a two-fold approach to provide a suitably designed HRES-IMG. Firstly, a reliability-constrained formulation based on load index of reliability (LIR) is developed with an objective to achieve a minimum levelized cost of energy (LCOE). Multi-state modeling of HRES-IMG is carried out based on hardware availability of generating units and uncertainties due to meteorological conditions. Modeling of battery storage units is realized using a multi-state probabilistic battery storage model. Secondly, an efficient optimization technique using a decentralized multi-agent-based approach is applied for obtaining high-quality solutions. The butterfly-PSO is embodied in a multi-agent (MA) framework. The enhanced version, MA-BFPSO is used to determine optimum sizing and technology combinations. Three different technology combinations have been investigated. The combination complying with LIR criterion and least LCOE is chosen as the optimal technology mix. The optimization is carried out using classic PSO, BF-PSO, and, MA-BFPSO and obtained results are compared. Further, in order to add a dimension in system planning, the effect of uncertainty in load demand has also been analyzed. The study is conducted for an HRES-IMG situated in Jaisalmer, India. The technology combination comprising of solar, wind, and battery storage yields the least LCOE of 0.2051 $/kWh with a very low value of LIR (0.08%).  A reduction in generator size by 53.8% and LCOE by 16.5% is obtained with MABFPSO in comparison with classic PSO. The results evidently demonstrate that MA-BFPSO offers better solutions as compared to PSO and BF-PSO.
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  • Incorporation of multi-state output model of RES-based generators in system planning. The multi-state model integrates respective forced outage rates (FOR) of generators as well as climatological parameters.
  • Development of a reliability-constrained planning framework for determination of component sizes.
  • Consideration of different technology combinations and their assessment based on reliability and cost.
  • Consideration of battery storage system(BSS) as an integral component of system planning.
  • Implementation of a highly efficient optimization technique involving parallel processing, Multi-agent based Butterfly PSO (MA-BFPSO) algorithm. The MA-BFPSO not only reduces the computational time but also provides high-quality solutions. To establish the effectiveness of technique, a comparison has been carried out with standard PSO and Butterfly- PSO (BF-PSO).

Type of Study: Research Paper | Subject: Heuristics and Metaheuristics
Received: 2021/05/11 | Revised: 2021/07/20 | Accepted: 2021/08/02

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.