Abstract

High initial investment and the intermittent nature of resources are major challenges for large scale renewable generation. The size of photovoltaic (PV) and wind turbine (WT) farms in the microgrid needs optimized to avoid curtailment and to efficiently meet the demand of a power system. Battery energy storage systems (BESSs) may also be used to improve flexibility. This paper explores the optimal sizing for PV and wind generators, as well as a BESS at the utility level for a large grid-connected net zero energy (NZE) hybrid microgrid considering characteristics such as initial investment, levelized cost of energy (LCOE), operating costs, net present cost (NPC), and renewable fraction. Multi-objective formal optimizations were formulated as single objective problems with constraints and solved using the HOMER Pro computational engine. Ten optimizations with different utility charge rates are performed using actual data for the load profile, weather, and utility buy-back rates of Glasgow, KY. Simulation results demonstrated that various utility charge rates result in different optimal sizes for the solar PV and the WT farms, as well as for the BESS capacity.

Document Type

Conference Proceeding

Publication Date

11-2019

Notes/Citation Information

Published in 2019 8th International Conference on Renewable Energy Research and Applications (ICRERA).

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The document available for download is the authors’ manuscript version that is accepted for publication. The final published version is copyrighted by IEEE and will be available as: E. S. Jones, H. Gong, and D. M. Ionel, “Optimal Combinations of Utility Level Renewable Generators for a Net Zero Energy Microgrid Considering Different Utility Charge Rates,” 2019 8th International Conference on Renewable Energy Research and Applications (ICRERA), Brasov, Romania, 2019, pp. 1014-1017, doi: 10.1109/ICRERA47325.2019.8996529.

Digital Object Identifier (DOI)

https://doi.org/10.1109/ICRERA47325.2019.8996529

Funding Information

The direct support of the Schneider Electric Corporation and the University of Kentucky Department of Electrical and Computer Engineering Undergraduate Research Fellowship Program is gratefully acknowledged.

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