Optimised operation of an off-grid hybrid wind-diesel-battery system using genetic algorithm

In an off-grid hybrid wind-diesel-battery system, the diesel generator is often not utilised efficiently, therefore compromising its lifetime. In particular, the general rule of thumb of running the diesel generator at more than 40% of its rated capacity is often unmet. This is due to the variation in power demand and wind speed which needs to be supplied by the diesel generator. In addition, the frequent start-stop of the diesel generator leads to additional mechanical wear and fuel wastage. This research paper proposes a novel control algorithm which optimises the operation of a diesel generator, using genetic algorithm. With a given day-ahead forecast of local renewable energy resource and load demand, it is possible to optimise the operation of a diesel generator, subjected to other pre-defined constraints. Thus, the utilisation of the renewable energy sources to supply electricity can be maximised. Usually, the optimisation studies of a hybrid system are being conducted through simple analytical modelling, coupled with a selected optimisation algorithm to seek the optimised solution. The obtained solution is not verified using a more realistic system model, for instance the physical modelling approach. This often led to the question of the applicability of such optimised operation being used in reality. In order to take a step further, model-based design using Simulink is employed in this research to perform a comparison through a physical modelling approach. The Simulink model has the capability to incorporate the electrical and mechanical (Simscape) physical characteristics into the simulation, which are often neglected by other authors when performing such study. Therefore, hybrid system simulation models are built according to the system proposed in the work. Finally, sensitivity analyses are performed as a mean of testing the designed hybrid system's robustness against wind and load forecast errors.