od-blip/Renewable-Energy-Product-Demand-Forecasting-Analysis-Group-5-

This project aims to forecast the demand for renewable energy products in Nigeria by analyzing historical data on inflation, foreign exchange rates, and renewable energy consumption trends. We developed projections for future energy demands, identifying potential challenges and growth opportunities in the renewable energy sector. # Renewable Energy Product Demand Forecasting Analysis by Group 5 ## Contributors - Ifeka Odira Hillary (Lead) - Adebayo Deborah - Dr Samuel Israel - Convenant Lenu ## Table of Contents 1. Project Overview 2. Datasets and Data Cleaning - Inflation Data - Foreign Exchange Dataset - Renewable Energy Consumption Dataset 3. Data Merging and Preparation 4. Analysis and Forecasting - Forecasting - Additional Charts 5. References ## Project Overview This project aims to forecast the demand for renewable energy products in Nigeria by analyzing historical data on inflation, foreign exchange rates, and renewable energy consumption trends. We developed projections for future energy demands, identifying potential challenges and growth opportunities in the renewable energy sector. ### Forecast Visuals | Title | Visualization| |--------------------|-----------------------------------------------------------------------------------------| |Energy Consumption Forecast | |Renewable Share Forecast in Nigeria | |Exchange Rate forecast | --- ## Datasets and Data Cleaning ### 1. Inflation Data - **Objective**: Analyze how inflation impacts renewable energy consumption. - **Steps**: - Loaded the dataset into Power Query. - Removed irrelevant columns, such as those focused on inflation in specific sectors like food, to streamline analysis. - Merged the "Year" and "Month" columns into a single "Date" column to facilitate time-based analysis, while retaining the "Year" column (2003–2023) for relationship building. Rows with years 2000–2002 were removed. - Added a new column, "Country," with the value set to "Nigeria" for easier dataset merging. - Checked and ensured correct data types (e.g., date for the new "Date" column, numeric for inflation rates). ### 2. Foreign Exchange Dataset - **Objective**: Track how exchange rate fluctuations affect renewable energy costs. - **Steps**: - Loaded the dataset into Power Query. - Retained only the black-market exchange rate columns, "Buying …