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@article{172493,
        author = {Rahul Arya},
        title = {“Analysis of Economic Load Dispatch in Power Systems using Scaled Conjugate Gradient Approach in Machine Learning”},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {636-641},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172493},
        abstract = {The escalating size of power systems has heightened the need to minimize operational costs, pollution, and transmission losses. This study tackles the Economic Load Dispatch (ELD) problem, a crucial optimization challenge in power systems, aiming to allocate generations optimally among available units to achieve minimum generation costs. Three load demand scenarios – low, normal, and high – are considered, with incremental cost serving as a key system performance metric. Fuzzy Logic is employed to implement ELD constraints, formulating an optimization problem. Due to the complexity of solving ELD problems amidst numerous system constraints, Fuzzy Logic proves to be an efficient tool. This research utilizes the Fuzzy Logic toolbox, incorporating constraints such as generating limits, power balance, minimum uptime, minimum downtime, and spinning reserve to develop requisite rules and membership functions. A case study involving three generating units demonstrates the effectiveness of the proposed approach in solving unit commitment problems.},
        keywords = {Economic Load Dispatch, Fuzzy Logic, Optimization, Power System, Unit Commitment.},
        month = {February},
        }