Systems, Architecture and Systems Architecture

In this series, I’ll present a step-by-step guide to designing a scalable cloud architecture for a multi-energy, multi-step forecasting platform.

This first post focuses on applying Domain-Driven Design (DDD) to structure the problem space and lay the foundation for implementation.

Drawing from the 2025 paper “A Multi-Energy Meta-Model Strategy for Multi-Step Ahead Energy Load Forecasting” (Mystakidis et al.), I explore how the forecasting challenge can be modeled through:

✅ Identifying the core domain
✅ Defining bounded contexts (Feature Engineering, Forecast Modeling, Forecast Serving)
✅ Mapping out domain aggregates
✅ Designing a component-level UML architecture based on these concepts

The goal of this first delivery is to demonstrate how a forecasting strategy can be clarified and prepared for scalable implementation — before writing any code.