LAUSR

Heat pumps and hot water tanks in local energy systems require sizing to increase on-site renewables self-consumption; decrease costs through variable electricity pricing; and utilise low-cost wind power. While detailed tools can capture these mechanisms, planning-level tools lack functionality and miss these benefits. In this paper an open-source planning-level modelling tool, PyLESA, is presented and applied to a sizing study to demonstrate the capturing of these benefits at the planning-level. Specific aims of the study were to investigate: (i) model predictive control vs. fixed order control, (ii) existing and future wind-influenced electricity tariffs, and (iii) optimal cost size combinations of heat pump and hot water tank. The lowest levelized cost of heat for the existing tariffs was for a time-of-use tariff, 750 kW heat pump and 500 m 3 hot water tank combination. For the future wind-influenced tariff a 1000 kW heat pump and 2000 m 3 hot water tank was cost optimal and showed model predictive control benefits over fixed order control with levelized heat costs reducing 41 %, and heat demand met by renewables increasing 18 %. These results demonstrate PyLESA as capable of capturing flexibility benefits at the planning stage of design and quantify the advantage of combining flexible tariffs with model predictive control.