Cyber-Physical Co-Simulation Testbed for Real-Time Reactive Power Control in Smart Distribution Network

Existing electric power distribution systems are evolving and changing as a result of the high renewable energy sources integration. Hence, future smart distribution networks will involve various technical challenges; one of them is real-time monitoring and controlling the network to operate it effectively and efficiently. This paper develops and analyzes a cyber-physical co-simulation testbed for real-time reactive power control in the smart distribution network. The testbed is a two-layer system, with Typhoon HIL 604 representing the physical layer and the other layer as a cybernetic layer. The cybernetic layer is used to model a test system and control reactive power from smart inverters in real-time. The implementation of real-time reactive power control of smart inverters on a CIGRE MV distribution network is shown in this study. The proposed testbed's usefulness in real-time reactive power control is demonstrated through simulation results

Data-Driven Distributed Modeling, Operation, and Control of Electric Power Distribution Systems

The power distribution system is disorderly in design and implementation, chaotic in operation, large in scale, and complex in every way possible. Therefore, modeling, operating, and controlling the distribution system is incredibly challenging. It is required to find solutions to the multitude of challenges facing the distribution grid to transition towards a just and sustainable energy future for our society. The key to addressing distribution system challenges lies in unlocking the full potential of the distribution grid. The work in this dissertation is focused on finding methods to operate the distribution system in a reliable, cost-effective, and just manner. In this PhD dissertation, a new data-driven distributed ($D^3M$) framework using cellular computational networks has been developed to model power distribution systems. Its performance is validated on an IEEE test case. The results indicate a significant enhancement in accuracy and performance compared to the state-of-the-art centralized modeling approach. This dissertation also presents a new distributed and data-driven optimization method for volt-var control in power distribution systems. The framework is validated for voltage control on an IEEE test feeder. The results indicate that the system has improved performance compared to the state-of-the-art approach. The PhD dissertation also presents a design for a real-time power distribution system testbed. A new data-in-the-loop (DIL) simulation method has been developed and integrated into the testbed. The DIL method has been used to enhance the quality of the real-time simulations. The assets combined with the testbed include data, control, and hardware-in-the-loop infrastructure. The testbed is used to validate the performance of a distribution system with significant penetration of distributed energy resources

Assessment of daily cost of reactive power procurement by smart inverters

The reactive power control mechanisms at the smart inverters will affect the voltage profile, active power losses and the cost of reactive power procurement in a different way. Therefore, this paper presents an assessment of the cost–benefit relationship obtained by enabling nine different reactive power control mechanisms at the smart inverters. The first eight reactive power control mechanisms are available in the literature and include the IEEE 1547−2018 standard requirements. The ninth control mechanism is an optimum reactive power control proposed in this paper. It is formulated to minimise the active power losses of the network and ensure the bus voltages and the reactive power of the smart inverter are within their allowable limits. The Vestfold and Telemark distribution network was implemented in DIgSILENT PowerFactory and used to evaluate the reactive power control mechanisms. The reactive power prices were taken from the default payment rate document of the National Grid. Simulation results demonstrate that the optimal reactive power control mechanism provides the best cost–benefit for the daily steady-state operation of the network.Intelligent Electrical Power Grid