Techno-Economic and Environmental Impact Analysis of Large-Scale Wind Farms Integration in Weak Transmission Grid from Mid-Career Repowering Perspective

Abstract

Repowering a wind farm enhances its ability to generate electricity, allowing it to better utilize areas with high mean wind speeds. Pakistan’s present energy dilemma is a serious impediment to its economic development. The usage of a diesel generator as a dependable backup power source raises the cost of energy per kWh and increases environmental emissions. To minimize environmental emissions, grid-connected wind farms enhance the percentage of wind energy in the electricity system. These wind generators’ effects, on the other hand, are augmented by the absorption of greater quantities of reactive electricity from the grid. According to respective grid codes, integration of commercial onshore Large-Scale Wind Farms (LSWF) into a national grid is fraught with technical problems and inter-farm wake effects, which primarily ensure power quality while degrading overall system operation and limiting the optimal use of attainable wind resources. The goal of this study is to examine and estimate the techno-economic influence of large-scale wind farms linked to poor transmission systems in Pakistan, contemplating the inter-farm wake effect and reactive power diminution and compensating using a range of voltage-ampere reactive (VAR) devices. This study presents a partial repowering technique to address active power deficits produced by the wake effect by raising hub height by 20 m, which contributed to recovering the active power deficit to 48% and so reduced the effects of upstream wind farms. Simulations were conducted for several scenarios on an actual test system modeled in MATLAB for comparative study using capacitor banks and different flexible alternating current transmission system (FACTS) devices. Using the SAM (System Advisor Model) and RETscreen, a complete technical, economic, and environmental study was done based on energy fed into the grid, payback time, net present value (NPV), and greenhouse gases (GHG) emission reduction. The studies suggest that the unified power flow controller (UPFC) is the optimum compensating device via comparison analysis as it improved the power handling capabilities of the power system. Our best-case scenario includes UPFC with hub height augmentation, demonstrating that it is technically, fiscally, and environmentally viable. Over the course of its lifespan, the planned system has the potential to save 1,011,957 tCO2, resulting in a greener environment. When the energy generated annually by a current wake-affected system is compared to our best-recommended scenario, a recovered shortfall of 4.851% is seen, with improved system stability. This modest investment in repowering boosts energy production due to wake effects, resulting in increased NPV, revenue, and fewer CO2 footprints.

Publication DOI: https://doi.org/10.3390/su14052507
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Additional Information: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Funding: This research was funded by the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia, through project number IFP2021-081.
Uncontrolled Keywords: Renewable energy,System advisor model,Transmission grid,Wind generation,Geography, Planning and Development,Renewable Energy, Sustainability and the Environment,Environmental Science (miscellaneous),Energy Engineering and Power Technology,Management, Monitoring, Policy and Law
Publication ISSN: 2071-1050
Full Text Link:
Related URLs: https://www.mdp ... -1050/14/5/2507 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2022-02-22
Accepted Date: 2022-02-07
Authors: Butt, Rohan Zafar
Kazmi, Syed Ali Abbas
Alghassab, Mohammed
Khan, Zafar A.
Altamimi, Abdullah
Imran, Muhammad (ORCID Profile 0000-0002-3057-1301)
Alruwaili, Fahad F.

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