Multi-energy systems (MES) play a key role in solving many significant problems related to economic efficiency, reliability, and impacts on the environment. The multiplicity of goals pursued in the creation of MES gives rise to the problem of multi-criteria choice. The long-life cycle of MES and different development scenarios cause uncertainty in the preferences of decision makers. Focusing on these problems, the article proposes a framework for MES sizing based on multi-criteria optimization and decision-making techniques. Multi-criteria optimization is carried out to find Pareto-optimal MES configurations using the metaheuristic non-dominated sorting genetic algorithm III (NSGA-III). Multi-criteria evaluation of Pareto front alternatives under uncertainty of preferences is performed with fuzzy technique for order of preferences by similarity to ideal solution (TOPSIS). To develop MES that is the most suitable for various scenarios, a new indicator is proposed within the multi-scenario approach, calculated as the geometric mean of fuzzy TOPSIS assessments. The effectiveness of the proposed framework is demonstrated for a remote settlement located on the coast of the Sea of Japan under three scenarios. The geometric mean indicator through the multi-scenario approach identified the MES configuration most suitable for all considered scenarios (levelized cost of energy 0.21 $/kW h (within the interval 0.178–0.275), investment costs 294 289 $(43 573–535 439), CO2 emission 43 008 kg/year (3069–118 542), and unmet load 3262 kW h/year (0–24 044). Furthermore, for the problem being solved, the modified Inverted Generational Distance indicator was used to compare NSGA-III and NSGA-II algorithms. The superiority of NSGA-III over NSGA-II was confirmed (intervals of the indicator estimates are 1874–4040 and 3445–21 521, respectively).
Skip Nav Destination
,
Article navigation
December 2024
Research Article|
December 02 2024
Multi-criteria design of multi-energy system for remote area using NSGA-III and fuzzy TOPSIS
Vladislav Shakirov
;
Vladislav Shakirov
(Conceptualization, Methodology, Writing – original draft, Writing – review & editing)
Department of Complex and Regional Problems in Energy, Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Science
, Irkutsk 664074, Russia
Search for other works by this author on:
Ilya Popov
Ilya Popov
a)
(Methodology, Software, Visualization, Writing – original draft, Writing – review & editing)
Department of Complex and Regional Problems in Energy, Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Science
, Irkutsk 664074, Russia
a)Author to whom correspondence should be addressed: [email protected]
Search for other works by this author on:
Vladislav Shakirov
Ilya Popov
a)
Department of Complex and Regional Problems in Energy, Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Science
, Irkutsk 664074, Russia
a)Author to whom correspondence should be addressed: [email protected]
J. Renewable Sustainable Energy 16, 066303 (2024)
Article history
Received:
April 24 2024
Accepted:
October 22 2024
Citation
Vladislav Shakirov, Ilya Popov; Multi-criteria design of multi-energy system for remote area using NSGA-III and fuzzy TOPSIS. J. Renewable Sustainable Energy 1 December 2024; 16 (6): 066303. https://doi.org/10.1063/5.0215524
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
57
Views
Citing articles via
Evaluation of wind resource uncertainty on energy production estimates for offshore wind farms
Kerry S. Klemmer, Emily P. Condon, et al.
Machine learning for modern power distribution systems: Progress and perspectives
Marija Marković, Matthew Bossart, et al.
Ultra-short-term prediction of solar irradiance with multiple exogenous variables by fusion of ground-based sky images
Xiaopeng Sun, Wenjie Zhang, et al.
Related Content
Multiple objective traveling salesman problem using NSGA-II: A case study of ice tube distribution
AIP Conf. Proc. (November 2024)
Multi-objective optimization of the Stirling heat engine through self-adaptive Jaya algorithm
J. Renewable Sustainable Energy (June 2017)
Multi-objective optimization of a natural aspirated three-cylinder spark ignition engine using modified non-dominated sorting genetic algorithm and multicriteria decision making
J. Renewable Sustainable Energy (April 2016)
Multicriteria optimization based comprehensive comparative analyses of single- and two-stage (series/parallel) thermoelectric generators including the influence of Thomson effect
J. Renewable Sustainable Energy (July 2018)
Path planning as multi-objective optimization using the NSGA-II algorithm
AIP Conf. Proc. (February 2025)