MPC-based energy management system for hybrid renewable energies

Environmental pollution and the gradual depletion of conventional energy have induced significantresearch in energy supply systems equipped with renewable and conventional sources. Although wind andsolar energy sources emerge as the most promising renewable energies, a supply system comprising two ormore sources is recommended to fulfill local loads, as the power generated by renewable sources depends onweather conditions. The main idea of any energy supply system is to fulfill the energy demand with theminimum cost, considering the operational constraints related to the components. As a result, some issues,such as security of supply, improvement in the combination of energy sources, efficiency, energy saving,improvement in access to isolated systems, and the development of renewable energy, should all be takeninto account. Up to now, cost reduction and energy saving have been understood almost exclusively as thetechnological improvement of renewable sources: wind turbines, solar panels, solar collectors, etc. Themisconception of “the best system is made with the best components” is still used for the design of energysupply systems. Technological advances in renewable sources should be coupled with a sophisticated energymanagement system.This paper proposes an energy management system based on control ideas. Therefore, the design of ahybrid controller based on predictions of energy, estimated from physical models and previousmeasurements, is considered in order to satisfy the energy supply. Model Predictive Control (MPC) has beenchosen as the main control strategy since it is able to handle variations in the supply of renewable energy;while, in the energy demand, MPC includes a cost function to be minimized and adds the constraints on themanipulated and controlled variables. The cost function takes into account the value of the energy generated,the cost of storing energy locally, and the aging of the components. It is selected to be simple because thefuture control actions computed by the optimizer take into account the integration of the model along theprediction horizon.Hybrid process models are then considered in the proposed MPC. Although this gives formulationproblems, Mixed Logical Dynamic (MLD) involves continuous variables (involved in linear dynamicequations), discrete variables (specified through propositional logic statements), and the mutual interactionbetween the two. In this case, the resulting mixed integer quadratic programming (MIQP) could presentproblems for real time implementation, because the solution is computationally complex and dependsexponentially on the number of binary manipulated variables. To simplify the MPC problem, the use ofbinary manipulated variables is avoided by the parameterization of the binary manipulated variables intocontinuous variables. This transforms the mixed integer optimization into a nonlinear optimization made upof only by continuous manipulated variables (NMPC). To illustrate the applicability and effectiveness of theproposed predictive control, four energy supply systems have been considered: a Solar and Wind basedMicrogrid for Desalination, a Solar Gas Air Conditioning Plant, a Hydrogen based Microgrid, and a SolarDesalination Plant. The study and applicability of these energy supply systems will be carried out throughoutthe different chapters. The implementation has been done as a modular structure to facilitate changes. Therenewable energy library facilitates the training of technicians and engineers in how to operate energy supplysystems, how to check different configurations and control strategies, before implementing them, and how tofacilitate their design.

Keywords:

MPC , Energy management , hybrid renewable energies