OPTIMAL TRACKING OF GRID OPERATED LOAD DEMAND WITH HYDROGEN BASED STORAGE SYSTEM USING MODEL BASED PREDICTIVE CONTROL

It has become imperative for the power and energy engineers to look out for the renewable energy sources such as sun, wind, geothermal, ocean and biomass as sustainable, cost-effective and environment friendly alternatives for conventional sources. However, since they are inherently unreliable, during the last decades the scientific community addressed research efforts to their integration with the main grid by means of properly designed energy storage systems (ESSs). However, due to the complexity of the involved systems in terms of number of inputs, number of outputs, number of decision variables, constraints and costs this topic is still open. In particular, advanced control strategies for the management of ESSs in order to take into account all the reported aspects need to be designed. In this paper we present a model predictive controller (MPC) which operates a hydrogen-based ESS (HESS) within a wind farm fence. The controller is derived in order to minimize the operating and economical costs of the HESS and the difference between the available power and that required by the grid operator through a suitable reference, while satisfying physical constraints and considering the dynamics of the system. In order to capture both continuous/discrete dynamics and transitions among different operating modes, the plant is modelled as a mixed logic dynamic system. The study has been developed within the EU-FCH 2 JU funded project HAEOLUS aiming at building and integrating advanced control strategies for a ESS within a wind farm. Numerical simulations show the feasibility and the effectiveness of the proposed approach.