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Stochastic Convex Cone Programming for Joint Optimal BESS Operation and Q-Placement in Net-Zero Microgrids

doi: 10.3390/en17174292
handle: 1959.4/102853
Microgrids have emerged as a pivotal solution in the quest for efficient, resilient, and sustainable energy systems. Comprising diverse distributed energy resources, microgrids present a compelling opportunity to revolutionize how we generate, store, and distribute electricity, while simultaneously reducing carbon footprints. This paper proposes an optimal battery energy storage system (BESS) management scheme, along with capacitor placement for reactive power (Q)-compensation, and scheduling for the purpose of a renewable-based microgrid’s loss minimization. The proposed model evaluates the impact of BESS management on energy efficiency and analyzes how optimal scheduling of BESS influences system losses. Furthermore, it investigates the coordinated planning and operation of active assets within the microgrid, such as controllable capacitor banks, in enhancing overall efficiency. The model is formulated as a mixed-integer second-order cone programming (MISOCP) problem which is solved for both deterministic and stochastic generation and consumption data. The proposed model is tested on a 21-bus microgrid comprising photovoltaic and hydropower energy resources, and the efficacy of the model is approved by several case studies. The simulation results show that the proposed method can reduce microgrid energy losses by approximately 12 percent using the deterministic approach and around 14 percent with the stochastic approach.
- UNSW Sydney Australia
- University of Tehran Iran (Islamic Republic of)
- University of Sydney Australia
- University of Tehran Iran (Islamic Republic of)
anzsrc-for: 4009 Electronics, Technology, anzsrc-for: 51 Physical sciences, anzsrc-for: 40 Engineering, power losses, renewable energy resources (RESs), anzsrc-for: 4008 Electrical Engineering, 40 Engineering, 13 Climate Action, mixed-integer programming, T, battery energy storage system (BESS), 620, anzsrc-for: 02 Physical Sciences, microgrid, 4009 Electronics, anzsrc-for: 33 Built environment and design, 7 Affordable and Clean Energy, cone programming, 4008 Electrical Engineering, Sensors and Digital Hardware, anzsrc-for: 09 Engineering
anzsrc-for: 4009 Electronics, Technology, anzsrc-for: 51 Physical sciences, anzsrc-for: 40 Engineering, power losses, renewable energy resources (RESs), anzsrc-for: 4008 Electrical Engineering, 40 Engineering, 13 Climate Action, mixed-integer programming, T, battery energy storage system (BESS), 620, anzsrc-for: 02 Physical Sciences, microgrid, 4009 Electronics, anzsrc-for: 33 Built environment and design, 7 Affordable and Clean Energy, cone programming, 4008 Electrical Engineering, Sensors and Digital Hardware, anzsrc-for: 09 Engineering
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
