Frequency Control and Inertia Support for Solar PV Plants Using Integrated Hybrid Energy Storage Systems

In recent years, the concept of renewable energy resources (RES) has gained global recognition to progress towards sustainable energy generation. Considering the ever-increasing electric power requirement, most nations are committing to unprecedented large-scale installation of RESs, such as Saudi Arabia targets 41-GW solar installation by 2032, India 130-GW by 2022 and United Kingdom leans towards large scale wind power installation by 2050. Subsequently, the photovoltaic (PV) market procured substantial growth with an annual installation of 115-GW in 2019, achieving a cumulative installation of about 5600-GW, making PV one of the largest markets in the world. Nevertheless, the most critical challenge of RES is their intermittency and uncontrollability that severely depletes their commercial significance and imposes a systematic challenge in each technical phase. Among other solution, the concept of energy storage system (ESS) has been adopted as an energy buffer that provides ancillary support for optimal generation, transmission and demand side management. This project utilizes the emerging concept of hybrid energy storage systems (HESS). Since a single type of ESS cannot efficiently address the voltage and frequency challenges associated with RES based hybrid microgrids (MGs) and subjective inertia response requirement of ESS in a grid-connected conditions. The hybridization of different ESS like that of batteries and supercapacitors is a more feasible approach. These two technologies constitute a powerful combination since battery has high energy density and supercapacitor has high power density. These complementary features can be appropriately mingled to enhance the performance and lifespan of the ESS as well as enhance their potential to circumvent numerous challenges. A practical model for the HESS is designed, that accounts for various constraints of charging/discharging rates, state-of-charge and temperature coefficients. While the PV based MG model maintains the supply-demand balance continuously, the main objective is to effectively allocate power between HESS and enhance their contribution towards voltage regulation of the DC microgrid and inertia and frequency support to the AC side. This goal is achieved via developing computationally efficient algorithms for optimal energy management, keeping in view the realistic system limitations and practical considerations. An optimal control-based approach with adaptation to ESS characteristics requirement is considered such as low/high pass filters, k-type compensators, neural networks and model predictive control, that will be best suited for exploitation of battery as well as supercapacitor towards their respective power quality support. Additional consideration is also done for reduction of voltage and current sensing devices to obviate their inherent delay, effecting the voltage regulation. Although PV is particularly focussed on this proposal, the methodology is quite general which can easily be extended to other types of renewables such as wind. The successful completion of this project will offer an insight to power system operators to reliably design and operate large-scale RESs while satisfying the technological constraints and grid codes. Hence this project can become valuable step to meet the objectives of the Saudi Arabia Vision 2030 for RES integration into the electric utility and can also bring benefits for future electric power requirement and environmental preservation.