birirv/Kenya_Electricity_Demand_and_Energy_Risk_Analytics

This is a data analytics project focused on understanding electricity demand patterns, generation mix and energy related risks in Kenya( 2000 - 2024) .The tools used are MS Excel, SQL, Python and Power BI. # Kenya Electricity Demand & Energy Risk Analytics # Project Overview This project analyzes Kenya's electricity sector from 2000 to 2024 focusing on historical demand patterns, generation trends, risk assessment and forecasting future consumption. Using IEA generation data and Our World in Data per capita energy consumption. The project delivers actionable insights for policymakers, utilities and investors. # Objectives - Identify trends in electricity generation and per capita demand. - Forecast future energy demand to 2030. - Quantify risks: volatility, tail risks, and dependency on variable sources. - Provide interactive dashboards and visualizations to support decision-making. Deliverables - Interactive Power BI dashboards - Python notebooks and SQL scripts - Forecasts of electricity demand to 2030 - Risk assessment metrics (volatility, tail risk, risk index) - Markdown/PDF reports summarizing insights Data Sources - IEA: Electricity generation by source (GWh, 2000-2024) -iea.org - Our World in Data: Per capita primary energy consumption (kWh/person, 2000-2023) - ourworldindata.org Tools & Stack - Python (pandas, Prophet, scikit-learn, matplotlib/seaborn) - SQL (SQLite/PostgreSQL) - Excel for initial cleaning - Power BI for dashboards and DAX-based metrics Work in progress. © 2026 Victor Kibirir - Kenya Electricity Demand & Energy Risk Analytics Project