Research-backed optimisation for complex energy planning.

A field-defining review co-written by two Sympheny founders and the wider Empa group. It sets out the core modelling questions for distributed multi-energy systems - technology choice, temporal and spatial resolution, uncertainty, and optimisation - and is one of the most-cited references for why this class of problem needs a structured optimisation approach rather than a spreadsheet.

Primary reference for the structured-design argument: energy systems need reusable, digital, multi-layer workflows because sector coupling and distributed resources make manual planning too complex. The paper includes a public Modelica/Sympheny district dataset.

Foundational practice paper for Sympheny's product logic. It identifies iterative stakeholder workflows, temporal decomposition, automation, and KPI visualisation as the missing link between mature optimisation research and real planning adoption.

Core scaling paper behind city and district optimisation. It connects building-level detail to larger district models and reports 10-100x computational speed improvements with minimal accuracy loss.

Shows how full-year operating strategy optimisation can be solved faster without relying only on typical-period shortcuts.

Combines technology sizing, hourly operation, and district heating network layout in one optimisation model. The case study found a 23% emissions reduction at the same cost.

Adds electrical grid constraints to distributed energy system optimisation, showing that grid-aware design and operation can reduce emissions and defer grid upgrades.

Open-source precursor showing how raw district descriptions can be translated into executable optimisation models and interpretable outputs.

Compares MILP thermal-network approximations with thermal-hydraulic simulation, clarifying where simplified optimisation is reliable and where extra constraints improve design quality.

Explains why decarbonised, digitalised energy systems require a jump toward more holistic modelling, simulation, and optimisation workflows.

Turns energy supply security into a quantitative planning framework, useful for policy, resilience, and infrastructure investment decisions.

A direct Sympheny application: the Swiss Rhine port of Basel-Kleinhüningen modelled as a multi-hub integrated energy system. Using hourly MILP optimisation, the 2035 concepts cut greenhouse-gas emissions by 82-97% and energy imports by 39-44% at comparable annual cost - published evidence of the platform on a live infrastructure decision.

Links the design of local energy systems to a decarbonising grid above them, using linearised AC power flow and grid-upgrade options. It shows how the cost-optimal mix of district heating and distributed technologies shifts as the surrounding electricity grid gets cleaner - the kind of forward-looking question utilities and cities actually face.

Extends the multi-scale method: a clustering schema that estimates where district heating networks pay off across a whole city, based on building characteristics. It is the bridge between building-level detail and city-scale screening that lets planners find network opportunities without modelling every building by hand.