Daily operation optimisation of hybrid stand-alone system by model predictive control considering ageing model

This article presents a method for optimising the daily operation (minimising the total operating cost) of a hybrid photovoltaic-wind-diesel-battery system using model predictive control. The model uses actual weather forecasts of hourly values of wind speed, irradiation, temperature and load. Five control variables are optimised, and thus their optimal set points values determine the optimal control strategy for each day. This involves the use of an accurate model for estimating the degradation of the batteries by considering the capacity loss due to corrosion and degradation. The model considers the extra costs of maintaining and replacing the diesel generator due to running out of its optimal conditions. The optimisation is carried out by means of genetic algorithms. An example of application compares the total operating cost obtained using the optimal control strategy for each day with the cost of using the optimal control strategy found for the whole year, obtaining savings of up to 7.8%. Also the comparison with the cost of using the “load following” control strategy is analysed, obtaining savings of up to 37.7%.