Meta-Heuristic Algorithms for Optimal Sizing of HRES

Introduction

Conventional energy sources, mainly fossil fuels, have long served as the backbone of global energy production, powering homes, public transportation, and businesses over the years. The three basic types of fossil fuels are natural gas, oil, and coal. Since they are reliable, fossil fuels continue to rule the energy landscape even in the presence of alternate energy sources like wind and solar power. Despite their usage, the burning of fossil fuel contributes majorly to air pollution and climate change. The adoption of clean energy must be given the utmost importance in global government actions with the goal of reducing air pollution emissions that affect human health (Juciano Gasparotto, 2021).

Figure 1.

Global average surface temperature change (based on Horton, 2020)

The Intergovernmental Panel on Climate Change (IPCC) regularly evaluates the most recent literature on climate change and gives projections of global temperature change in its assessment reports. The most recent assessment report, the IPCC Sixth Assessment Report (AR6), provides updated projections based on different scenarios of greenhouse gas emissions. By the end of the 21st century, global temperatures are expected to climb drastically, according to the IPCC AR6. According to the report, global temperatures could rise by around 3.0°C to 5.7°C by 2100 compared to per-industrial levels under a scenario with high emissions (SSP5-8.5). The global scientific community estimated the change in mean sea level through scenarios called RCP (Representative Concentration Pathway). The Mean Sea level projection changed drastically over the years. In the RCP 2.6 projection from 1986 - 2005, It was 65 cm which changed to around 132 cm in the RCP 8.5. There was likely an increase in the mean sea levels projection, considering the change in environment. The global average surface temperature change is shown in Figure 1 (Horton, 2020). The objective of the Paris Agreement was to set global warming to a temperature of 1.5 degrees Celsius or below. Reducing the generation of fossil fuels minimizes emissions of greenhouse gases, which is essential for the Paris Agreement to be implemented. (Welsby, Dan, et al. 2021). From the insights of BP energy outlook in Figure 2, the forecast of energy usage will change in coming years. So, the necessity of renewable energy sources will keep rising and they will be an essential component of the energy mix in the future.

Figure 2.

Forecasting of global energy usage in percentage (BP Energy Outlook, 2023)

By 2050, consumption of fossil fuels is going to significantly decrease. To predict and evaluate the required amount of power sources for the future needs many methods have been proposed computationally. Due to enormous amount of data and criteria Meta heuristic analysis using machine learning training datasets. It can be used to improve data precision and reduce the computational time.

There are two strategies for reducing climate change’s effects, one is concentrating on lowering the emission and other is the absorption of these emission gases. This process is called negative emission process. Also, to meet the Paris Agreement, a strong transformation in technology framework in developing the alternative energy systems such as renewable energy is required. Hybrid Renewable Energy System can serve as an option for this technology framework which uses different renewable energies as well conventional energies to meet the energy demands and the systems were organized in different subsets to analyze and predict the requirement of energy. (Samer Fawzy, 2020).

Chapter Organization

The chapter encloses HRES system's overall description is provided. A mathematical model of the suggested system is created, and it consists of solar, wind, Battery, and Diesel Generator. Then the importance of HRES mathematical modelling using Meta heuristic evaluation method.This objective function is represented by the energy cost of HRES.