Mitigating Energy Losses Under Incremental Load Variations in Distributed Power-Flow Systems While Ensuring User Comfort

Sadiq Muhammad, Saher Javaid, Iacovos Ioannou, Yuto Lim () and Yasuo Tan
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Sadiq Muhammad: Graduate School of Advanced Science and Technology, Japan Advanced Institute of Science and Technology, Nomi 923-1292, Ishikawa, Japan
Saher Javaid: Graduate School of Advanced Science and Technology, Japan Advanced Institute of Science and Technology, Nomi 923-1292, Ishikawa, Japan
Iacovos Ioannou: Department of Computer Science, University of Cyprus, Nicosia 1678, Cyprus
Yuto Lim: Graduate School of Advanced Science and Technology, Japan Advanced Institute of Science and Technology, Nomi 923-1292, Ishikawa, Japan
Yasuo Tan: Graduate School of Advanced Science and Technology, Japan Advanced Institute of Science and Technology, Nomi 923-1292, Ishikawa, Japan

Energies, 2025, vol. 18, issue 21, 1-37

Abstract: Renewable energy sources (RESs) such as photovoltaic (PV) and fuel cells (FCs) introduce variability that complicates reliable, loss-aware operation of distributed power-flow systems (DPFSs) in smart homes. Frequent charge/discharge cycling of energy storage systems (ESSs) can inflate losses and jeopardize user comfort when generation and demand are mismatched. This paper addresses the gap in multi-load, multi-source coordination under fluctuating RESs by proposing a Multiple-Load Power-Flow Assignment (MPFA) framework that explicitly minimizes storage-related losses while maintaining demand satisfaction. We evaluate four logical interconnection scenarios among generators (PGs), loads (PLs), and storage (PSs), and compare three control algorithms—total-demand-based (TDPF), adaptive-demand-based (ADPF), and grid-based (GBPF). Using measured PV/FC data across seasons, MPFA consistently reduces storage-related losses as interconnections increase, with GBPF guaranteeing full daily demand satisfaction by flexibly supplementing local generation with grid power. ADPF performs strongly when grid support is limited by prioritizing critical loads and optimizing storage utilization. The results provide actionable guidance for designing smart-home energy management that emphasizes sustainability, reliability, and user comfort.

Keywords: energy storage systems; power flow control; renewable energy sources; smart homes; energy losses; reliability; user comfort; Multiple-Load Power-Flow Assignment (MPFA) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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