raygee642-bit/Nigeria-Electricity-Grid-Optimization-Analysis-2024-

## **Project Overview** This project analyzes the performance of electricity grid optimization across various Nigerian Distribution Companies (DisCos). By leveraging data-driven insights, the analysis tracks key performance indicators (KPIs) such as revenue recovery, load loss reduction, and regional efficiency to improve the stability and profitability of the national power sector. ## **Tools Used** * **Microsoft Excel:** Data sourcing, structural cleaning, and preliminary data processing. * **Power BI:** Advanced data modeling, KPI development, and interactive dashboard visualization. ## **Problem Statement** The Nigerian electricity grid suffers from systemic power and revenue losses during transmission and distribution, resulting in significant financial leakages and energy waste. Despite optimization efforts, performance remains inconsistent across regions; while some areas show improvement, others like **Benin, Abuja, and Port Harcourt** continue to demonstrate minimal progress and optimization inefficiencies. Without real-time monitoring and targeted interventions, especially during peak load periods, the grid remains unstable, leading to a potential loss of billions in revenue and hundreds of thousands of megawatts in power supply,. ## **Project Aim** The primary aim of this analysis is to **maximize grid efficiency and financial recovery** across all Nigerian Distribution Companies (DisCos). This project evaluates 2024 optimization performance data to: * Recover lost revenue (targeting a baseline of **₦688.63bn**) and power load (**144.43k MW**). * Identify high-loss regions and analyze peak-period demand patterns to improve grid stability,. * Provide actionable recommendations for increasing optimization frequency in underperforming regions. ## **Methodology** 1. **Data Preparation:** Cleaned and standardized 2024 grid performance data in **Excel**. 2. **KPI Development:** Built DAX measures in **Power BI** to track revenue and load savings …