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Showing 1 results for Solar Energy
Dr Amir-Mohammad Golmohammadi, Naser Ghorbani, Dr Fateme Rashidian,
Volume 17, Issue 2 (9-2026)
Abstract
The optimal planning of hybrid renewable energy systems has become increasingly important due to rising energy demand, environmental concerns, and the need for reliable electricity supply in remote and isolated regions. This study presents a comprehensive mixed-integer linear programming (MILP) framework for the optimal design of a hybrid solar–wind–battery–fuel cell–diesel microgrid. The proposed model simultaneously determines the optimal type, size, and operation of system components over the project lifetime while minimizing the equivalent annual cost. Unlike many existing optimization approaches, the framework integrates economic, environmental, and reliability considerations into a unified objective function by incorporating carbon emission penalties, load curtailment penalties, and renewable energy incentive policies. Furthermore, replacement costs and component lifetime degradation are reformulated into linear constraints, enabling the problem to be solved efficiently using exact optimization techniques. Hourly meteorological and load data are employed to accurately capture seasonal and daily variations in renewable energy generation and electricity demand. The optimization model is implemented in GAMS and solved using the CPLEX solver. Different system configurations and regulatory scenarios are evaluated to investigate the influence of diesel generators, battery storage, hydrogen technologies, and government support policies on system performance. The results demonstrate that an appropriately designed hybrid microgrid can substantially improve renewable energy penetration while maintaining system reliability and reducing the overall lifecycle cost. Moreover, regulatory incentive mechanisms significantly increase the economic viability of renewable energy resources and decrease dependence on fossil-fuel-based generation. The proposed MILP framework provides an effective decision-support tool for policymakers, system planners, and investors involved in the development of sustainable hybrid microgrids.
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