Towards Increasing Hosting Capacity of Modern Power Systems through Generation and Transmission Expansion Planning

Abdulaziz Almalaq, Khalid Alqunun, Mohamed M. Refaat, Anouar Farah, Fares Benabdallah, Ziad M. Ali and Shady H. E. Abdel Aleem
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Abdulaziz Almalaq: Department of Electrical Engineering, College of Engineering, University of Hail, Hail 55473, Saudi Arabia
Khalid Alqunun: Department of Electrical Engineering, College of Engineering, University of Hail, Hail 55473, Saudi Arabia
Mohamed M. Refaat: Photovoltaic Cells Department, Electronics Research Institute, Cairo 11843, Egypt
Anouar Farah: Department of Electrical Engineering, College of Engineering, University of Hail, Hail 55473, Saudi Arabia
Fares Benabdallah: Department of Electrical Engineering, College of Engineering, University of Hail, Hail 55473, Saudi Arabia
Ziad M. Ali: Electrical Engineering Department, College of Engineering, Prince Sattam Bin Abdulaziz University, Wadi Addawaser 11991, Saudi Arabia
Shady H. E. Abdel Aleem: Department of Electrical Engineering, Valley High Institute of Engineering and Technology, Science Valley Academy, Qalyubia 44971, Egypt

Sustainability, 2022, vol. 14, issue 5, 1-26

Abstract: The use of renewable and sustainable energy sources (RSESs) has become urgent to counter the growing electricity demand and reduce carbon dioxide emissions. However, the current studies are still lacking to introduce a planning model that measures to what extent the networks can host RSESs in the planning phase. In this paper, a stochastic power system planning model is proposed to increase the hosting capacity (HC) of networks and satisfy future load demands. In this regard, the model is formulated to consider a larger number and size of generation and transmission expansion projects installed than the investment costs, without violating operating and reliability constraints. A load forecasting technique, built on an adaptive neural fuzzy system, was employed and incorporated with the planning model to predict the annual load growth. The problem was revealed as a non-linear large-scale optimization problem, and a hybrid of two meta-heuristic algorithms, namely, the weighted mean of vectors optimization technique and sine cosine algorithm, was investigated to solve it. A benchmark system and a realistic network were used to verify the proposed strategy. The results demonstrated the effectiveness of the proposed model to enhance the HC. Besides this, the results proved the efficiency of the hybrid optimizer for solving the problem.

Keywords: renewable and sustainable energy; hosting capacity; power system planning; load forecasting; meta-heuristic algorithms (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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