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

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 pl...

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Published in:	Sustainability 2022-03, Vol.14 (5), p.2998
Main Authors:	Almalaq, Abdulaziz, Alqunun, Khalid, Refaat, Mohamed M., Farah, Anouar, Benabdallah, Fares, Ali, Ziad M., Aleem, Shady H. E. Abdel
Format:	Article
Language:	English
Subjects:	Algorithms Alternative energy Carbon dioxide Electric power demand Electrical loads Emissions Energy sources Forecasting techniques Fuzzy logic Genetic algorithms Heuristic Heuristic methods Optimization Planning Stochasticity Sustainability Vectors
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cited_by	cdi_FETCH-LOGICAL-c295t-760aab32cfd7932ac78009c0ea633925573ed16be8079ac05727d7cfdd685aee3
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container_title	Sustainability
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creator	Almalaq, Abdulaziz Alqunun, Khalid Refaat, Mohamed M. Farah, Anouar Benabdallah, Fares Ali, Ziad M. Aleem, Shady H. E. Abdel
description	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.
doi_str_mv	10.3390/su14052998
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subjects	Algorithms Alternative energy Carbon dioxide Electric power demand Electrical loads Emissions Energy sources Forecasting techniques Fuzzy logic Genetic algorithms Heuristic Heuristic methods Optimization Planning Stochasticity Sustainability Vectors
title	Towards Increasing Hosting Capacity of Modern Power Systems through Generation and Transmission Expansion Planning
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