Simplifying the Data for the Optimal Sizing and Operation of PV and Storage in a Household by Linear Transformations

Abstract

Optimal sizing and operation of a household with photovoltaic (PV) and storage requires a proper consideration of some uncertain parameters, as demand and PV generation. A one-year case study, including several scenarios and hourly discretization, may be very efficiently solved using an off-the-shelf solver on a laptop. However, getting those data is not always an easy task. In this work, we study whether it would be possible to get an approximate solution by using aggregate measures for those uncertain parameters and how should the problem be transformed to handle that aggregated information. By taking into account the average values of consecutive periods, we propose a linear transformation of the constraints and a set of additional ones to get this goal. Results over a case study show that the proposed procedure provides reasonable values, although the precision could be improved if some additional information, apart from the average values of the uncertain input data, is considered.