Design and Control of Battery Energy Storage System for Microgrids

Today, climate change and global warming have commenced a fast pace of technological advances in renewable power industry. Many countries are moving towards cleaner energy sources, which have made the concept of distributed power generation from renewable energy (RE) resources more desirable. The fast emerging concept of microgrids (MGs) is a solution proposed to control the impact of distributed generation on the conventional grids. Due to the increase in the development of new power generators, such as wind and solar PV, integrating renewable and non-renewable distributed generators in the main electricity grid becomes a challenging subject. While renewable energies can provide more sustained power and relieve several environmental concerns, they may also harm the quality and reliability of the grid due to their uncertain generated power and the critical challenges for its integration into existing power grids cannot be neglected. A potential solution is to utilize one of the energy storage technologies, though all of them are still very expensive for such applications especially at large scale. Therefore, optimal capacity calculations for energy storage system is vital to realize full benefits. Energy storage can provide more flexibility and balancing to the grid and it can improve the management of distribution networks, reducing costs and improving efficiency. However, one of the main challenges in integrating the energy storage devices is in modelling the charging and discharging rates based on different operational modes. Currently battery energy storage technology has been accepted as most promising for renewable power applications. In this proposal, we focus at battery storage technology and propose a generic methodology for optimal capacity calculations for battery energy storage system (BESS) coupled with a MG. Furthermore, innovative control strategies will be explored and implemented for an intelligent energy management of MGs integrated with intermittent RE resources and energy storage systems. Adaptive control is one of the advanced control approaches used to control the systems with uncertain and time varying parameters, for example, adaptive control schemes can be proposed in the context of MGs, which can experience unexpectedly change in their modes due to disturbances in the power grid and/or from RE resources. Furthermore, new power dispatch algorithms will be proposed based on wind power forecasting, solar power prediction and demand prediction to optimize the overall cost of MG system. The concept of dynamic programming in control will be utilized in order to incorporate the future behaviour of the system into its predictive optimization. The successful completion of the proposed project will enable and/or facilitate higher penetration of renewable power particularly wind and solar into Kingdoms energy mix with minimum possible cost and higher power quality.