Energy Demand Forecasting

Course Overview

A practical, forecasting‑focused course that teaches learners how to model and predict short‑, medium‑, and long‑term energy demand across electricity, gas, oil, and renewable sectors. The course covers load‑profile analysis, weather‑driven demand modelling, time‑series forecasting, peak‑demand prediction, scenario planning, and the impact of economic, behavioural, and policy factors on energy consumption.

Target Audience

• Energy analysts, forecasting teams, and market operations professionals

• Utilities, grid operators, and demand‑planning teams

• Oil & gas, LNG, and renewable energy companies

• Data analysts, BI developers, and modelling specialists

• Students or professionals entering energy markets, forecasting, or analytics roles

Course Outcomes

• Understand energy demand drivers, consumption patterns, and sector‑specific dynamics

• Analyse historical load profiles, seasonal trends, and weather‑sensitive demand

• Apply time‑series models (ARIMA, ETS, Prophet) and machine‑learning techniques for forecasting

• Evaluate peak‑demand risks, load variability, and grid‑stability implications

• Use scenario modelling to assess economic, policy, and behavioural impacts on demand

• Build dashboards for demand monitoring, forecasting accuracy, and operational insights

• Identify anomalies, demand shocks, and emerging consumption trends

• Communicate forecasting insights clearly to operations, planning, and leadership teams