Analysis reveals optimal energy allocation in electrical networks using linear programming, suggesting enhanced sustainability.
Energy resource allocation in electrical grids is a major challenge in the energy sector, as providing energy sustainably and efficiently requires optimizing its distribution between various power plants and consumers. Electricity grids exhibit significant complexity in terms of the amount of energy generated and consumed, as well as multiple constraints such as power plant capacity and transmission and distribution requirements. Therefore, linear programming is one of the most important tools used to optimize energy allocation and distribution in these networks. Linear programming is a mathematical technique that aims to find optimal solutions to resource allocation problems under specific constraints. The mathematical problem is represented by a model that includes an objective function (such as minimizing costs) and constraints that define possible values for variables (such as power plant capacity and transmission line constraints). In electrical grids, linear programming helps determine the amount of energy that must be generated from each plant to ensure demand is met at all points in the grid, taking into account the costs associated with energy production and transmission. Using operations research techniques such as linear programming algorithms, energy allocation across the grid is optimized by identifying solutions that result in the lowest operational cost, addressing technical constraints such as power plant capacity, power plant production capacity, and time-varying demand. The Simplex algorithm, for example, is widely used to solve these problems to find optimal solutions for power distribution. An important application of these techniques is in renewable energy management, where solar and wind power are considered non-stationary energy sources. Linear programming helps allocate renewable energy efficiently across the grid, reducing reliance on conventional sources and enhancing grid sustainability. These methods also contribute to reducing transmission losses and balancing energy supply and demand across timescales. Additionally, linear programming helps achieve economic efficiency in the grid by reducing costs associated with operation and maintenance. By applying operations research and linear programming, environmental sustainability can be improved by reducing emissions from conventional power plants, making the grid more efficient and resilient to future challenges, such as increased energy demand and the use of renewable energy sources.
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Abdalsatar et al. (2025) studied this question.
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