Electricity-Consumption-Prediction-in-Egypt

Energy Sustainability Project README

Overview

This project aims to address Egypt's energy challenges by leveraging data-driven solutions. With increasing demand from urban centers and industries, conventional approaches such as random power cuts have proven ineffective. To tackle this issue, we are adopting a proactive strategy grounded in data analytics. Drawing insights from analogous situations, particularly England's energy landscape, we aim to comprehend electricity usage patterns influenced by geographical, demographic, and climatic factors. By developing predictive models and efficient management strategies, our goal is to enhance energy sustainability and overcome supply problems.

Key Features

• Data Integration: Utilize Hadoop and Apache Spark frameworks to manage and analyze vast datasets efficiently.
• Risk Management: Identify and mitigate potential risks including data quality issues and external variables.
• Predictive Modeling: Develop models to forecast electricity demand and optimize resource allocation.
• Collaborative Approach: Foster interdisciplinary collaboration to extrapolate actionable insights from data.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/energy-sustainability-project.git

2. Install dependencies:

   pip install -r requirements.txt

3. Set up Hadoop and Apache Spark according to the project requirements.

Usage

1. Ensure that the dataset is properly integrated and preprocessed.
2. Run the main analysis scripts to generate insights and develop predictive models.
3. Collaborate with cross-functional teams to interpret results and refine strategies.
4. Monitor and evaluate the performance of the implemented solutions regularly.