Optimal Battery Storage Operation for PV Systems with Tariff Incentives

Optimisation models providing insights into the benefits of battery storage coupled to photovoltaic (PV) generation system are receiving attention recently. An electricity customer whose electricity demand is supplied by a grid connected PV generation system benefiting from a FiT incentive is simulated in this research work. The system is simulated with the PV modelled as an existing system and the PV modelled as a new system. For a better understanding of the existing PV system with battery storage operation, an optimisation problem was formulated which resulted in a mixed integer linear programming (MILP) problem. Data is available in .pdf and 2 .xlsx files. The pdf file named “AIMMS model formulation” describes the nomenclature and formulation (parameters, objective function, decision variables and constraints) of the AIMMS optimisation model. To run the optimisation model the .xlsx file named “input” is provided to be used as input data. The “input” file has 3 separate tabs (load, pv, and tou). The unit of the data “load” and “pv” tabs is in kW, while the unit of the data in the “tou” tab is in “pence/kWh”. The “load” contains the half-hourly electricity demand of the customer while the “pv” tab contains the daily half-hourly photovoltaic power profile of the customer for a complete year. The data in the “tou” tab is the historical wholesale electricity tariff in pence/kWh. All the 3 tabs have the same data structure: The row heading describes each half-hour of the day (48 data points) while the column heading describes the date of each day of the year (365 data points).

The output file in .xlsx is also provided. It contains 10 tabs. The data in each of the 10 tabs is the result of the optimisation model decision variables described in pdf file named “AIMMS model formulation”. The structure of the “output_results.xlsx” is the same as described in the “input” file.

Research results based upon these data are published at https://doi.org/10.1016/j.apenergy.2017.06.043