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Techno-economic modelling of hybrid energy system to overcome the load shedding problem: a case study of Pakistan

Bakht, Muhammad Paend and Salam, Zainal and Bhatti, Abdul Rauf and Sheikh, Usman Ullah and Khan, Nuzhat and Anjum, Waqas (2022) Techno-economic modelling of hybrid energy system to overcome the load shedding problem: a case study of Pakistan. PLoS ONE, 17 (4). pp. 1-29. ISSN 1932-6203

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Official URL: http://dx.doi.org/10.1371/journal.pone.0266660

Abstract

This paper demonstrates the application of hybrid energy system (HES) that comprises of photovoltaic (PV) array, battery storage system (BSS) and stand-by diesel generator (DGen) to mitigate the problem of load shedding. The main work involves techno-economic modelling to optimize the size of HES such that the levelized cost of electricity (LCOE) is minimized. The particle swarm optimization (PSO) algorithm is used to determine the optimum size of the components (PV, BSS). Simulations are performed in MATLAB using real dataset of irradiance, temperature and load shedding schedule of the small residential community situated in the city of Quetta, Pakistan. The LCOE for the HES system under study is 8.32 cents/kWh—which is lower than the conventional load shedding solution, namely the uninterruptable power supply (UPS) (13.06 cents/kWh) and diesel and generator system (29.19 cents/kWh). In fact, the LCOE of the HRES is lower than the grid electricity price of Pakistan (9.3 cents/kWh). Besides that, the HES alleviates the grid burden by 47.9% and 13.1% compared to the solution using the UPS and generator, respectively. The outcomes of the study suggests that HES is able to improve reliability and availability of electric power for regions that is affected by the load shedding issue.

Item Type:Article
Uncontrolled Keywords:reliability, simulation, algorithm, electricity
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Faculty of Engineering - School of Electrical
ID Code:103653
Deposited By: Yanti Mohd Shah
Deposited On:22 Nov 2023 00:21
Last Modified:22 Nov 2023 00:21

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