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Towards a Sustainable Microgrid on Alderney Island Using a Python-based Energy Planning Tool

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Document pages: 7 pages

Abstract: In remote or islanded communities, the use of microgrids (MGs) is necessaryto ensure electrification and resilience of supply. However, even insmall-scale systems, it is computationally and mathematically challenging todesign low-cost, optimal, sustainable solutions taking into consideration allthe uncertainties of load demands and power generations from renewable energysources (RESs). This paper uses the open-source Python-based Energy Planning(PyEPLAN) tool, developed for the design of sustainable MGs in remote areas, onthe Alderney island, the 3$^{rd}$ largest of the Channel Islands with apopulation of about 2000 people. A two-stage stochastic model is used tooptimally invest in battery storage, solar power, and wind power units.Moreover, the AC power flow equations are modelled by a linearised version ofthe DistFlow model in PyEPLAN, where the investment variables are here-and-nowdecisions and not a function of uncertain parameters while the operationvariables are wait-and-see decisions and a function of uncertain parameters.The $k$-means clustering technique is used to generate a set of best(risk-seeker), nominal (risk-neutral), and worst (risk-averse) scenarioscapturing the uncertainty spectrum using the yearly historical patterns of loaddemands and solar wind power generations. The proposed investment planning toolis a mixed-integer linear programming (MILP) model and is coded with Pyomo inPyEPLAN.

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