Quasi-SoC Balancing Control for Networked Ad-hoc Microgrids Against Natural Disasters

After natural disasters, mobile containerized renewable energy-based Ad-hoc microgrids could be an emergency solution to maintain power supply to critical loads. In this paper, a novel two-layer coordinated control for individual and networked Ad-hoc microgrids is proposed. The first layer deals with the internal coordination between RE and ESS to maintain a stable operation within an Ad-hoc microgrid by using bus frequency, thereby without communication links to reduce power consumption. When forming the networked Ad-hoc microgrids to a critical load with higher load demand, the regulations on the bus frequency from each Ad-hoc microgrid will result in instability. Therefore, a quasi-SoC balancing control strategy for the networked Ad-hoc microgrids is further proposed with only binary information exchanges to mitigate the interactions caused by the internal coordination control among the Ad-hoc microgrids. To verify the effectiveness of the proposed control approach, simulation results with Matlab/Simulink are presented.</p

Efficient Power centric Resilience Maximization Model for Distribution System Using Adaptive Configuration

The resilience is the most dominant factor in any disaster condition which has been approached by various techniques in literature. Some of the methods consider only the power availability and grid states for the resilience maximization. However, they suffer to achieve higher performance in voltage distribution. To solve this issue, an efficient Power Centric Resilience Maximization Model (PCRMM) is presented in this paper. The model monitors the incoming voltage and generates adaptive configuration for the distribution system by considering number of grids, their states, emergency units, essential units, service sectors and so on. By considering all these factors, the method computes the resilience support for different micro grids according to the available voltage. Also, the method computes the functional support for the cycle and based on that dynamic configurations are generated. According to the configuration, the distribution system would trigger the voltage supply to various micro grids to feed voltage to the selected units. The proposed method improves the performance of power distribution with least voltage loss

Stochastic Resource Allocation for Electricity Distribution Network Resilience

In recent years, it has become crucial to improve the resilience of electricity distribution networks (DNs) against storm-induced failures. Microgrids enabled by Distributed Energy Resources (DERs) can significantly help speed up re-energization of loads, particularly in the complete absence of bulk power supply. We describe an integrated approach which considers a pre-storm DER allocation problem under the uncertainty of failure scenarios as well as a post-storm dispatch problem in microgrids during the multi-period repair of the failed components. This problem is computationally challenging because the number of scenarios (resp. binary variables) increases exponentially (resp. quadratically) in the network size. Our overall solution approach for solving the resulting two-stage mixed-integer linear program (MILP) involves implementing the sample average approximation (SAA) method and Benders Decomposition. Additionally, we implement a greedy approach to reduce the computational time requirements of the post-storm repair scheduling and dispatch problem. The optimality of the resulting solution is evaluated on a modified IEEE 36-node network.Comment: 6 pages, 5 figures, accepted to 2020 American Control Conferenc