Conceptual development of a novel digital controller for optimised operation of a hybrid renewable energy system

The popularity of renewable energy has increased dramatically in the last decade as it becomes increasingly apparent that an alternative to fossil fuel is required. In order for this market to continue to grow, there are a number of technical issues which must be overcome. One such issue is the instability of power supplies which rely on unpredictable natural resources. A popular solution to this problem is the use of a number of complementary renewable power sources to create a stable power network serving a small geographical area. In this project, a novel control solution for such a system is proposed and modelled using a new approach. A comprehensive review of the existing research literature was used to place in context the hybrid renewable energy concept. This included identification of a system topology as well as the novel control solution. A model of the system has been developed using a combination of PSim and MATLAB. This model allowed for the operation of the system to be simulated and subsequently verified. Upon completion of successful system level simulation testing, VHDL implementations of the control solution were created and incorporated into the model. Further simulations were then carried out based on a specific hardware target, an All Programmable System-on-Chip (APSOC) device featuring a dual-core CPU and an FPGA fabric. The novel control solution is primarily aimed at the optimal control of the system’s power converters. This controller employs a Neuro-Fuzzy algorithm to provide gain scheduling for a PI type controller. The test results indicate that improvements were achieved in the stability of the power converters in comparison to more traditional approaches, offering improved response times and a reduction of the output voltage error. Moreover, a state-based algorithm is utilised, which was demonstrated to ensure that the renewable energy sources are optimally complementary.