Grid ancillary service using distributed computational intelligence based control of renewables and storage systems in a distribution network

The large-scale integration of renewable energy sources (RESs) at the distribution network level provides several benefits and opportunities for the distribution network as well as the transmission network, despite having some technical challenges such as intermittency handling, network voltage control, etc. Such RESs are typically accompanied with battery storage systems (BSSs) to mitigate effects of their intermittency. The RES-BSS systems can therefore be used to provide ancillary services to the transmission network while providing technical benefits to the distribution network operator (DNO) and economic benefits to the RES owners. Further, computational intelligence based techniques can provide a near-optimal solution within fewer iterations of the algorithm, which is a critical requirement in fulfilling ancillary service requests. Therefore, this paper presents a fully distributed computational intelligence based technique so that the distribution network could handle ancillary service requests by the transmission system operator (TSO) in real-time. Specifically, an agent is associated with each node of the distribution network and it utilizes computational intelligence and communication with nearby agents to achieve the solution. Simulation studies on a modified IEEE 30-node test system are shown to validate our aforementioned thesis.