Journal
IEEE ACCESS
Volume 10, Issue -, Pages 57902-57913Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2022.3177143
Keywords
Microgrids; Switches; Batteries; Planning; Inverters; State of charge; Photovoltaic systems; Photovoltaic; microgrid; switch placement; loss of load probability; optimization
Categories
Funding
- U.S. Department of Energy's Office of Electricity
- Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy Technology Office
- U.S. Department of Energy's National Nuclear Security Administration [DE-NA0003525]
- Federal Emergency Management Agency
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The proposed approach aims to minimize the Loss of Load Probability by finding ideal switch locations to connect distant PV systems with critical loads in a microgrid setup.
Many Electric Power Systems (EPS) already include geographically dispersed photovoltaic (PV) systems. These PV systems may not be co-located with highest-priority loads and, thus, easily integrated into a microgrid; rather PV systems and priority loads may be far away from one another. Furthermore, because of the existing EPS configuration, non-critical loads between the distant PV and critical load(s) cannot be selectively disconnected. To achieve this, the proposed approach finds ideal switch locations by first defining the path between the critical load and a large PV system, then identifies all potential new switch locations along this path, and finally discovers switch locations for a particular budget by finding the ones the produce the lowest Loss of Load Probability (LOLP), which is when load exceed generation. Discovery of the switches with the lowest LOLP involves a Particle Swarm Optimization (PSO) implementation. The objective of the PSO is to minimize the microgird's LOLP. The approach assumes dynamic microgrid operations, where both the critical and non-critical loads are powered during the day and only the critical load at night. To evaluate the approach, this paper includes a case study that uses the topology and Advanced Metering Infrastructure (AMI) data from an actual EPS. For this example, the assessment found new switch locations that reduced the LOLP by up to 50% for two distant PV location scenarios.
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