Research-backed optimisation for complex energy planning.

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.