Generation Expansion Planning for a Real-world Power System: Aiming Towards Cost and Environmental Emission Minimization by Penetrating Huge Renewable Energy Sources

A power system planning must involve the Electricity demand forecasting (EDF) and Generation expansion planning (GEP) for better operation. The optimal plan should consider both qualitative and quantitative factors such as error, cost and reliability of the power system. In this study, EDF and GEP problem have been solved till the year 2030 for Tamil Nadu, an Indian state. The formulation of EDF problem has been modeled based on the input variables such as population, Gross State domestic product (GSDP) and per capita income, and has been solved using Genetic algorithm (GA), Artificial immune system (AIS) and Differential evolution (DE). While analyzing the results of EDF problem, DE provides optimal result with Minimum mean absolute percentage error (MAPE). Continually, short term (6-year) and long term (12-year) GEP problem have been solved using DE by considering minimization of cost and environmental effects as the main objectives. To achieve these objectives, Renewable Energy Sources (RES) have been integrated in different penetration levels such as 0–10%, 10–20%, 20–30%, 30–40%, and 40–50% on GEP problem and its impacts have been investigated. The results of DE have been validated with Dynamic Programing (DP). The outcomes of the study have assisted the power system planners while decision making in introducing Renewable Energy Sources (RES) on a real-world power system.