What is multi-energy hub modelling?
Multi-energy hub modelling evaluates electricity, heat, cooling, gas, hydrogen, and storage together in a single optimisation model. This page explains the method, why it matters for district energy planning, and how it works in practice.
What is an energy hub?
An energy hub is a node in an energy system where multiple energy carriers — electricity, heat, cooling, gas, hydrogen — are converted, stored, and distributed. The concept appears in peer-reviewed energy systems literature as a framework for modelling facilities that take in multiple energy inputs and deliver multiple energy outputs through combinations of conversion and storage technologies.
A building with a gas boiler is a simple single-carrier hub. A district energy centre with solar PV, a heat pump, battery storage, a gas backup boiler, and a thermal store is a multi-energy hub.
Multi-energy hub modelling is the computational practice of representing these nodes mathematically — defining their technology options, their constraints, and their connections — and then optimising across all of them simultaneously to find the system configuration that best meets specified targets for cost, CO₂, capacity, or some combination.
Single-carrier hub
A gas boiler serving a building's heat demand. One input carrier, one output carrier, no sector coupling.
Multi-energy hub
A district energy centre with solar PV, a heat pump, battery storage, a gas backup boiler, and a thermal store. Multiple carriers interact — the heat pump turns cheap overnight electricity into stored heat; the battery absorbs excess solar.
Multi-hub system
Multiple hubs connected by network links — district heating pipes, electricity cables — constitute a district-scale or city-scale multi-energy system model. Scale ranges from a single building to a municipal area.
What a multi-energy hub model contains
A complete model has five components. Each is necessary — missing any one of them produces results that cannot be trusted for planning decisions.
Technology candidates
The set of conversion and storage technologies allowed at each hub — solar PV, heat pump, gas boiler, battery, thermal store, electrolyser, CHP unit, and so on. The model optimises which subset to install and at what capacity.
Hourly demand profiles
Demand for each energy carrier — electricity, heat, cooling, and others — at hourly resolution over a reference year. Hourly resolution is necessary to capture the temporal interactions between generation, storage, and demand.
Cost and performance parameters
Capital cost, efficiency, lifetime, and maintenance cost for each technology candidate. These are the inputs the optimisation uses to evaluate the life-cycle economics of each configuration.
Energy balance constraints
Mathematical constraints that ensure supply meets demand at every hub and every hour. These are the equations that make the model physically consistent — no energy appears from nowhere, and no demand goes unmet.
Objective function
The target the optimisation minimises or maximises — typically life-cycle cost, CO₂ emissions, or a Pareto trade-off between them. The objective function determines what 'optimal' means for the specific project.
The optimisation method used to solve this model is called Mixed-Integer Linear Programming (MILP). For a detailed explanation of how MILP works and why it is appropriate for energy system design, see the page on MILP optimisation for energy systems .
Frequently asked questions
What is a multi-energy hub?
An energy hub is a node in an energy system that converts, stores, and distributes multiple energy carriers — electricity, heat, cooling, gas, and hydrogen — simultaneously. Unlike single-carrier infrastructure such as a gas boiler or an electricity substation, a multi-energy hub models all conversion and storage technologies at a site together, allowing sector-coupling interactions to be captured and optimised.
How is multi-energy hub modelling different from traditional energy system modelling?
Traditional approaches model energy carriers — electricity, heat, gas — in separate studies that do not interact. Multi-energy hub modelling places all carriers, technologies, and their interactions into a single mathematical model, which reveals optimisation opportunities that single-carrier studies miss, particularly where technologies convert between carriers (heat pumps, electrolysers, CHP units).
What scale of project is multi-energy hub modelling suited to?
The method applies from a single building to city-wide systems. Individual hubs can represent buildings, blocks, campuses, or industrial facilities; multiple hubs connected by network links (district heating, electricity cables) model district-scale or municipal energy systems.
Is multi-energy hub modelling the same as AI or machine learning?
No. Multi-energy hub modelling is based on mathematical optimisation — typically Mixed-Integer Linear Programming (MILP). It is deterministic: the same inputs always produce the same outputs, and every result can be traced to its underlying equations. Machine learning is not involved.
What software is used for multi-energy hub modelling?
Sympheny is a cloud platform built specifically for multi-energy hub modelling. It provides a GIS-enabled hub builder, a technology database, and a MILP optimisation engine that evaluates 50,000+ technology and capacity combinations per run, producing client-ready outputs directly in the browser.
See multi-energy hub modelling on a project like yours
Book a 30-minute demo. We'll walk through a project setup, show how hubs are configured and connected, and run a scenario so you can see the outputs before you commit.