The growth of Distributed Energy Resources is accelerating, causing significant changes in utility distribution systems due to the bidirectionality of power flow. As a result, protection systems will require upgrades to operate with these new requirements. The current-only directional relay (CODR) is a novel proposal that detects the direction of fault currents without the need for new devices, but instead upgrades the software logic of existing devices, making it a cost-effective solution. This work provides a complete description of how to implement a hardware testbed to review the CODR method. Findings show that CODR performs successfully in a real environment, but its algorithm needs to be upgraded if used in distribution systems where lines have a non-negligible resistive component. / Master of Science / The use of renewable energy sources, such as solar panels and wind turbines, is growing rapidly. This is causing changes in the way electricity is distributed, as power can now flow in both directions. To keep up with these changes, the systems that protect the electricity grid need to be updated. One cost-effective solution is to use a new type of relay, called the current-only directional relay (CODR), which can detect the direction of fault currents without the need for new devices. This work describes how to test the CODR method using a hardware testbed. The results show that the CODR performs well in a real environment, but its algorithm needs to be updated for use in certain types of distribution systems.

In this research, the problem of real-time congestion management in a modern distribution system with massive active elements such as electric vehicles (EVs), distributed energy resources (DERs), and demand response (DR) is investigated. A novel hierarchical operation and management framework is proposed that can take advantage of the demand side contribution to manage the real-time congestion. There are five main steps in this framework as 1) the aggregators send their demand to the microgrid operators (MGOs), 2) the MGOs send their demand to the distribution system operator (DSO), 3) the DSO detects the congestions and calls the engaged MGOs to reduce their demand, 4) the MGOs update the electricity price to motivate the aggregators to reduce the overall demand, and 5) the DSO dispatches the system according to the finalized demand. The proposed framework is validated on two modified IEEE unbalanced test systems. The results illustrate two congestion cases at t=8:45 am and t=9:30 am in the modified IEEE 13-bus test system, which needs 363kW and 286 kW load reductions, respectively, to be fully addressed. MG#1 and MG#2 are engaged to maintain the 363 kW reduction at t=8:45, and MG#3 and MG#4 are called to reduce their demands by 386 kW at t=9:30 am. The overall interactions can relieve the congested branches. The DSO’s calculations show three congestions at t=1 pm, t=3 pm, and t=9 pm on the IEEE 123-bus test system. These congestion cases can be alleviated by reducing 809 kW, 1177 kW, and 497 kW from the corresponding MGs at t=1 pm, t=3 pm, and t=9 pm, respectively. The second part of the simulation results demonstrates that the proposed real-time data estimator (RDE) can reduce the DSO’s miss-detected congestion cases due to the uncertain data. There are two miss-detected congestions in the IEEE 13-bus test system at t=1:15 pm and t=1:30 pm that can be filtered for t=1:15 pm and minored for t=1:30 pm using the RDE. The proposed RDE can also reduce the miss-detected congestions from 18 cases to four cases in the IEEE 123-bus test system. As a result, the RDE can minimize the extra costs due to the uncertain data. The overall results validate that the proposed framework can adaptively manage real-time congestions in distribution systems.