This chapter presents a supplementary controller, the tilt integral derivative (TID) controller, for load frequency control in a single-area thermal power system integrated with renewable energy sources. The tilt integral derivative controller's optimal parameter values are determined through state-of-the-art cohort intelligence optimization techniques, using performance indices such as ITAE as evaluation criteria. The suggested tilt integral derivative control method exhibits notable advantages, including ease of parameter adjustment and robust performance in the face of system parameter fluctuations. The effectiveness of the proposed method is showcased through a comparative analysis with recently published heuristic approaches, such as PID controllers optimized using differential evolution (DE), genetic algorithm (GA), and ant colony optimization (ACO). The simulations were conducted using MATLAB. A comparative examination with prior research reveals that the proposed tilt integral derivative controller outperforms the other methods.
Top1. Introduction
Electricity is a highly sought-after resource, and at present, over 70% of the world’s electricity needs are met by the combustion of fossil fuels like coal, crude oil, and natural gas. As economies expand and the global population grows, the need for electricity continues to surge, leading to a corresponding rise in the consumption of fossil fuels. Nevertheless, traditional fossil fuel stores are limited and dwindling at an alarming rate, necessitating urgent consideration and the implementation of sustainable strategies to avert a potential energy crisis down the road. Furthermore, fossil fuels are responsible for the release of detrimental emissions, notably greenhouse gases (GHGs), that play a significant role in exacerbating global warming. In the present context, various strategies are being employed to tackle these issues. One widely adopted approach involves raising public awareness about the importance of reducing energy consumption in both households and industries while also advocating for the adoption of energy-efficient technologies. Another strategy entails the promotion and advancement of renewable energy systems (RES) and related technologies, intending to make them dependable, cost-efficient, environmentally sustainable, and accessible to the general public for residential use. The latter approach has garnered increased attention within the research community, industries, and governments. Consequently, numerous countries and regions have initiated robust efforts to augment their renewable energy capacity (Kundur, n.d.; Annamraju & Nandiraju, 2020).
Effective LFC contributes to the quality of power supply. It helps in minimizing frequency fluctuations, which can affect the operation of sensitive equipment, industrial processes, and electronic devices. As renewable energy sources like wind and solar are integrated into power systems, LFC becomes even more critical. These sources can be variable, and LFC helps in managing their fluctuations and ensuring a stable power supply. Solar energy production is clean and produces no greenhouse gas emissions or air pollutants, which helps mitigate climate change and reduces air pollution Solar energy can contribute to greater energy independence, reducing reliance on fossil fuels and imported energy sources. This can enhance energy security for nations and regions.In addition, Once installed, solar panels have relatively low operating and maintenance costs. They require minimal upkeep and can last for decades. Wind power generation does not emit air pollutants such as sulphur dioxide (SO2), nitrogen oxides (Nox), or particulate matter, contributing to improved air quality and public health. Wind energy helps reduce carbon dioxide (CO2) emissions by displacing electricity generation from coal, natural gas, or other fossil fuels, thereby combating global warming and climate change. Wind farms can have an impact on local wildlife, particularly birds and bats. Proper site selection and mitigation measures are important to minimize these impacts. The integration of renewable with thermal power can lead to a reduction in air pollution and greenhouse gas emissions. Thermal power plants can operate at higher efficiency levels when used as backup sources rather than running continuously (Jagatheesan et al., 2016b; Murugesan et al.,2022).In recent years, researchers have delved into numerous techniques and optimization methods aimed at enhancing load frequency control in power systems. The literature reveals a wide array of controller structures employed for this purpose, including state space analysis (Jiang et al.,2011; Parmar et al.,2012), bode plot analysis (Anil Naik et al.,2011), sliding mode control (Farhad Farivar et al.,2022), conventional controllers, and Ziegler Nichols technique (Murugesan et al.,2023), Neural network model predictive control and fuzzy logic controllers (Kassem, 2010), PIDD controllers (Murugesan et al.,2021), cascaded PI-PD controllers (Padhy et al., 2017), adaptive neuro-fuzzy logic controllers (Khuntia & Panda, 2012), Crone controllers (Pritesh shah et al.,2022), PI controllers (Ali & Elazim, 2011), FOPID controllers (Murugesan et al., 2023), Nonlinear PID and Nonlinear FOPID controllers (Fayek, 2019), fractional order cascade controller (Sahoo et al., 2020), single PID and multiple PID controllers (Murugesan et al.,2023), Polar fuzzy controller (Chaturvedi et al., 2015), etc.