Abstract
This paper proposes an algorithmic formulation for optimal PV hosting and placement of distributed energy resources (DER) for network resiliency enhancement. The algorithm incorporates a unique critical infrastructure (CI) ranking scheme to prioritize the CI nodes for the DER placement while ensuring maximum hosting of the DER. The proposed multi-objective non linear programming formulation is validated on an IEEE 34 bus feeder with different outage scenarios caused by a hurricane event. The simulation has produced 18 Pareto Optimal Solutions showing several options of optimally locating the DERs in order to achieve a maximum DER hosting capacity, improve system’s resiliency and minimize the system’s active power loss while satisfying all network and power flow constraints. The results verify the effectiveness of the proposed algorithmic formulation which distribution planners and designers can apply directly to multitude of their network substations to improve the overall system’s resiliency through grid-scale situation awareness.
Highlights
T HERE are several definitions of power system resilience, including those given by the U.S Department of Energy (DOE), the Industrial Control Systems- Computer Emergency Readiness Team (ICS-CERT), and federal labs such as the National Renewable Energy Laboratory (NREL) and the Pacific Northwest National Laboratory (PNNL) [1,2,3,4]
The weights of critical infrastructure (CI) nodes are arranged in descending order such that the node with the highest weight gets a rank of 1, and the node with the least weight gets a rank of |NCI | where |NCI | is the cardinality of NCI
WORK In this paper an optimal distributed energy resources (DER) hosting algorithm to enhance the resilience of power distribution network is proposed
Summary
The proposed work aims to significantly enhance the resiliency of a distribution network by installing DER systems strategically with respect to the network’s CI nodes such that these DER systems and their corresponding local control systems can be treated as individual power plants. The lowest layer of the figure shows the entire PDN prior to identifying the CIs. The CI’s are identified and prioritized in the middle layer while the DER are optimally sized (based on maximum DER hosting) and strategically located to enhanced the PDN’s resiliency as defined in this paper
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