Innocentaniekan/Hybrid-Solar-Diesel-Battery-Optimization

Python and Power BI project for optimizing hybrid solar–diesel–battery energy systems for residential electricity supply in Nigeria. # Hybrid Solar–Diesel–Battery Energy Optimization Dashboard for Nigerian Households A data-driven renewable energy analytics project that models and evaluates the technical, economic, and environmental performance of a hybrid solar photovoltaic (PV), diesel generator, and battery energy storage system for residential electricity supply in Nigeria. The project combines Python for energy system modelling and Power BI for interactive dashboard visualization to demonstrate how hybrid renewable energy systems can reduce diesel consumption, lower carbon emissions, improve battery utilization, and support sustainable household electrification. ## Table of Contents - Project Overview - Objectives - Dataset - Mathematical Model - Dashboard Overview - Dashboard Preview - Results & Discussion - Repository Structure - Installation Guide - Future Improvements - About the Author - License ## Project Overview Reliable electricity remains a major challenge in many Nigerian communities, resulting in widespread dependence on diesel generators for residential power supply. While diesel generators provide backup electricity, they are associated with high operating costs, fuel price volatility, greenhouse gas emissions, and environmental pollution. This project investigates the integration of solar photovoltaic (PV) generation, diesel backup generation, and battery energy storage into a hybrid energy system designed for Nigerian households. Using solar irradiation data obtained from the NASA POWER database, the system simulates daily energy production, battery charging and discharging, diesel generator operation, and overall system performance throughout the year. The simulation results are analysed using Python and visualized through an interactive Power BI dashboard that presents key performance indicators (KPIs), monthly trends, economic metrics, environmental benefits, and battery performance. The project demonstrates how renewable energy analytics can support evide …