Integration of Renewable Energy Project: A Technical Proposal for Rural Electrification to Local Communities

Abstract

The increasing environmental awareness across the globe is leading towards a green and clean world. Currently, Pakistan is going through an acute energy crisis; it is an ongoing challenge for the government to provide uninterrupted power supply at economical rates to its citizens and potential industrial investors, now and in future. Thus, this energy scenario necessitates the incorporation of renewable energy technologies with power systems to enhance its generation capacity, and to overcome electricity outage of approximately 8-12 hours, in the country. In this paper, the authors encouraged the state policy for utilizing the wind energy for power generation, which is freely available across 1600 km long coastal belt of Pakistan. For this purpose, wind potential is explicitly evaluated across Sindh and Baluchistan provinces in Pakistan. The energy generated by various wind turbine prototypes is employed to suggest the most optimum location through optimal probability function. Moreover, this study provides an evocative progression based on realtime wind data to integrate wind power for rural electrification across the coastal zones of Pakistan. This study is expected to play an imperative role in incorporating wind farms on proposed sites to facilitate investors interested in investing in Pakista's energy sector. INDEX TERMS Environmental challenges, wind power integration, Weibull/Rayleigh distribution technique, wind zone, rural electrification, renewable energy.

Power Supply to Local Communities Through Wind Energy Integration: An Opportunity Through China-Pakistan Economic Corridor (CPEC)

“…Among alternative and renewable resources, wind power has been recognized as a significant potential source of renewable energy in Pakistan. The country has a total estimated gross wind power potential installable capacity of 346,000 MW [2]. In [3], authors have forecasted the realization of about 40-70% of Pakistan wind power potential by the year 2030.…”

“…According to the NREL report of June 2007 named Wind Resource Assessment and Mapping for Afghanistan and Pakistan, by Dennis Elliott, Pakistan has a total land area of about 877525 km 2 in which installed capacity is MW per km 2 . Out of the entire land area, only 26362 km 2 land area is considered with percent windy area which equals 3.0% and the total capacity installed of 131800 MW [20].…”

Multicriteria Decision Analysis for Renewable Energy Integration Design: For an Institutional Energy System Network

“…A new methodology is developed to identify the different configuration problems and maximize the techno-economic benefits of distribution systems for all envisaged cases and scenarios [12]. As well, other studies have identified the most convenient HRES option for the Public Library building, the hotel building, and other locations by evaluating the potential for energy sources in the proposed area using HOMER and a similar assessment tool [13][14][15][16][17][18]. When hybridizing energy sources, over one energy source in the system makes performance evaluation and decision-making complex and requires thorough technical, economic, and environmental analysis.…”

Analysis of multi‐objective optimization: a technical proposal for energy and comfort management in buildings

“…Numerous studies have been conducted by Wang and Yang by considering the comfort factors of thermal, visual, and air quality employing multi‐objective particle swarm optimization technique. Moreover, a graphical user interface (GUI) has been proposed in their extended work 9,10 . The three comfort parameters including thermal, visual, and air quality have been considered 11 for energy conservation and comfort management that employed multi‐islanded genetic algorithm (MIGA) and simple genetic algorithm (GA).…”

“…Moreover, a graphical user interface (GUI) has been proposed in their extended work. 9,10 The three comfort parameters including thermal, visual, and air quality have been considered 11 for energy conservation and comfort management that employed multi-islanded genetic algorithm (MIGA) and simple genetic algorithm (GA). The studies considered use fuzzy inference system for the local controller agents.…”