Demand Response-Integrated Economic Emission Dispatch Using Improved Remora Optimization Algorithm

Demand Response-Integrated Economic Emission Dispatch Using Improved Remora Optimization Algorithm

Karthik Nagarajan (Hindustan Institute of Technology and Science, India), Arul Rajagopalan (Vellore Institute of Technology, Chennai, India), P. Selvaraj (MGR Educational and Research Institute, India), Hemantha Kumar Ravi (Tata Elxsi Limited, India), and Inayathullah Abdul Kareem (Vellore Institute of Technology, Chennai, India)
Copyright: © 2024 |Pages: 21
DOI: 10.4018/979-8-3693-1586-6.ch007
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Abstract

Customers of electric utilities that participate in demand response are encouraged to use less energy than they typically do in order to better balance the supply and demand for energy. In this study, demand response is taken into account as a demand resource in the multi-objective optimal economic emission dispatch issue. The optimal schedule of conventional generators with the incorporation of demand response is determined using the improved remora optimization algorithm (IROA), a new technique for optimization inspired by nature. The two distinct objective functions of generation cost and emission are both optimized using the suggested optimization algorithm. The proposed optimization algorithm is investigated on IEEE 118-bus system. The application results are then compared with those obtained using the IROA and other optimization algorithms. The results of the optimization prove that, while adhering to the given limitations, the suggested optimization approach can drastically reduce both the operation cost and emission of the test systems under consideration.
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Introduction

The modern energy landscape is undergoing a transformative shift towards sustainability and efficiency. As a result, optimizing the operation of power systems has become an essential task for ensuring reliable electricity supply while minimizing the environmental footprint. Economic emission dispatch (EED) is a critical facet of this endeavour, and it seeks to strike a balance between cost-effectiveness and environmental responsibility in electricity generation (Karthik et al., 2019). The challenge of Economic Emission Dispatch (EED) stands as a pivotal issue in power system optimization. Its aim revolves around establishing the most efficient generation timetable for power plants, balancing the need to satisfy electricity demands while concurrently minimizing both generation expenses and emissions. (Arul et al., 2019). Traditionally, EED focuses on minimizing the cost of generating electricity while adhering to generation capacity constraints (Karthik et al., 2022). However, the rising importance of reducing greenhouse gas emissions and the integration of renewable energy sources has prompted the need for more sophisticated EED solutions. This has led to the incorporation of demand response (DR) resources into the optimization process, enabling a more flexible and sustainable approach to power system management (Abo‐Elyousr et al., 2022). Demand response is a strategy that empowers electricity consumers to actively participate in the electricity market by adjusting their energy consumption patterns in response to price signals or grid conditions (McPherson and Stoll, 2020). It enables consumers to lessen or adjust their electricity consumption during times of high demand or when renewable energy generation is limited. This action helps ease pressure on the grid and diminishes reliance on fossil fuel-powered generation. The integration of demand response into EED poses several challenges and objectives (Karthik et al., 2023). Firstly, it requires modelling the behaviour of demand response resources accurately, accounting for factors like price elasticity of demand, response times, and load flexibility. Secondly, it necessitates the development of optimization algorithms that can simultaneously consider generator dispatch decisions and demand response participation to minimize both cost and emissions. The integration of demand response resources into economic emission dispatch yields several benefits. Integrating demand response (DR) resources into Economic Emission Dispatch (EED) can amplify the efficiency and sustainability of power systems. This integration empowers consumers to adjust their electricity consumption patterns based on price signals or grid conditions, enhancing overall system adaptability (Silva et al., 2020). Furthermore, it enhances grid reliability by reducing peak demand and grid congestion, thereby reducing the risk of blackouts. Furthermore, it advances environmental sustainability by facilitating the decrease of greenhouse gas emissions via the coordinated utilization of cleaner energy sources and demand-side management strategies. Additionally, it has the potential to generate cost savings for consumers through dynamic pricing models and incentive programs. Economic emission dispatch with the integration of demand response resources represents a forward-looking approach to power system optimization (Mansy et al., 2020). By harnessing cutting-edge optimization algorithms and encouraging active consumer involvement in the electricity market, this approach not only guarantees efficient electricity generation at lower costs but also contributes significantly to forging a more sustainable and robust energy future (Jordehi, 2019). As the energy landscape undergoes constant evolution, the integration of demand response within Economic Emission Dispatch (EED) will serve as a crucial element in attaining a harmonious equilibrium between economic objectives and environmental aspirations within the power sector.

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