Contribution type: lightning talk and poster
MicroGridsPy: A Multi-Resolution and Multi-Energy Framework for Bottom-Up Energy Access Planning
Presenter: Alessandro Onori, Politecnico di Milano - SESAM Research Group
Description:
MicroGridsPy is an open-source modelling ecosystem for bottom-up energy planning in remote and underserved areas. It supports robust and transparent decision-making when electrification strategies must balance technical feasibility, economic viability, social priorities and environmental impacts. The ecosystem integrates stochastic demand assessment, renewable resource characterization, long-term capacity expansion, dispatch simulation, and LV/MV network design with load-flow validation. Its energy-planning model optimizes renewables, storage, dispatchable generators and grid interaction using hourly typical-year or multi-year formulations, while accounting for uncertainty, demand growth, phased investments, reliability, emissions and other externalities.
The contribution will focus on two developments within my ongoing PhD research.
The first is a multi-resolution planning architecture that soft-links spatial network design with long-term energy-system optimization. The topology module generates and compares alternative electrification architectures, including full LV networks, hybrid grid and stand-alone solutions, and MV backbones supplying local LV service zones. Candidate networks are built from georeferenced customers and roads, sized through iterative conductor and transformer reinforcement, and validated through AC load-flow analysis. This allows network costs, voltage limits, losses, service obligations and priority users to inform long-term planning without requiring a single, computationally prohibitive integrated model.
The second is a multi-energy modelling mapping with the aim of extending electricity-access planning to water, heating and cooling, biomass and productive uses of energy. The objective is to capture synergies and trade-offs such as flexible water pumping, biomass allocation between electrical and thermal services, and productive activities acting as anchor loads.
Background:
Mini-grid planning involves decisions at very different spatial and temporal scales. Distribution-network design depends on individual customer locations, settlement morphology, road infrastructure and electrical constraints, whereas energy-system optimization typically considers hourly operation, multi-year demand evolution, technology replacement and uncertain future conditions. At the same time, energy access cannot be adequately assessed through electricity supply alone. Households and communities require a wider set of energy services, including clean cooking, water pumping, heating, cooling and energy for income-generating activities. These services interact with electricity demand, local biomass resources, infrastructure requirements and environmental outcomes. Treating them separately may therefore overlook important synergies, resource competition and unintended trade-offs.
This work is being developed within my PhD research at Politecnico di Milano and builds on the modular MicroGridsPy ecosystem. The research investigates how open-source tools operating at different resolutions can be connected without creating an excessively large or opaque integrated model. More broadly, it explores how energy-access planning can progress from electricity-only least-cost optimization towards comprehensive, uncertainty-aware and socially informed infrastructure planning that accounts for multiple energy carriers, services and sustainability dimensions.
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