Enhanced Renewable Energy Integration: A Comprehensive Framework for Grid Planning and Hybrid Power Plant Allocation

Renewable energy sources play a crucial role in the urgent global pursuit of decarbonizing electricity systems. However, persistent grid congestion and lengthy planning approval processes remain the main barriers to the accelerated deployment of new green energy source capacities. Capitalizing on the synergies afforded by co-locating hybrid power plants—particularly those that harness temporally anti-correlated renewable sources such as wind and solar—behind a unified connection point presents a compelling opportunity. To this end, this paper pioneers a comprehensive planning framework for hybrid configurations, integrating transmission grid and renewable energy assets planning to include energy storage systems, wind, and solar energy capacities within a long-term planning horizon. A mixed-integer linear programming model is developed that considers both the technical and economic aspects of combined grid planning and hybrid power plant allocation. Additionally, the proposed framework incorporates the N − 1 contingency criterion, ensuring system reliability in the face of potential transmission line outages, thereby adding a layer of versatility and resilience to the approach. The model minimizes the net present value of costs, encompassing both capital and operational expenditures as well as curtailment costs. The efficacy of the proposed model is demonstrated through its implementation on the benchmark IEEE 24-bus RTS system, with findings underscoring the pivotal role of hybrid power plants in enabling cost-effective and rapid sustainable energy integration.

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Publication Details

Journal
Energies
Published
2025-08-28
DOI
https://doi.org/10.3390/en18174561
Primary Topic
Hybrid Renewable Energy Systems
Type
article
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article

Enhanced Renewable Energy Integration: A Comprehensive Framework for Grid Planning and Hybrid Power Plant Allocation

Innocent Kamwa, Mahmoud Taheri, Abbas Rabiee
Energies
Hybrid Renewable Energy Systems
article

Enhanced Renewable Energy Integration: A Comprehensive Framework for Grid Planning and Hybrid Power Plant Allocation

Innocent Kamwa, Mahmoud Taheri, Abbas Rabiee
article en

Abstract

Renewable energy sources play a crucial role in the urgent global pursuit of decarbonizing electricity systems. However, persistent grid congestion and lengthy planning approval processes remain the main barriers to the accelerated deployment of new green energy source capacities. Capitalizing on the synergies afforded by co-locating hybrid power plants—particularly those that harness temporally anti-correlated renewable sources such as wind and solar—behind a unified connection point presents a compelling opportunity. To this end, this paper pioneers a comprehensive planning framework for hybrid configurations, integrating transmission grid and renewable energy assets planning to include energy storage systems, wind, and solar energy capacities within a long-term planning horizon. A mixed-integer linear programming model is developed that considers both the technical and economic aspects of combined grid planning and hybrid power plant allocation. Additionally, the proposed framework incorporates the N − 1 contingency criterion, ensuring system reliability in the face of potential transmission line outages, thereby adding a layer of versatility and resilience to the approach. The model minimizes the net present value of costs, encompassing both capital and operational expenditures as well as curtailment costs. The efficacy of the proposed model is demonstrated through its implementation on the benchmark IEEE 24-bus RTS system, with findings underscoring the pivotal role of hybrid power plants in enabling cost-effective and rapid sustainable energy integration.

EnergiesVol. 18(17)
Université Laval (CA)
Openalex Percentile: Top 76%
Hybrid Renewable Energy Systems
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Enhanced Renewable Energy Integration: A Comprehensive Framework for Grid Planning and Hybrid Power Plant Allocation — Innocent Kamwa, Mahmoud Taheri, et al. · Energies (2025) | TGRS Research Map | TGRS