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Operational performance in the low-voltage distribution network (LVDN) can be undermined by its inherent unbalances, which may become worse as the penetration of rooftop solar continuously increases. To address this issue, load balancing via phase-reconfiguration devices (PRDs), which can change phase positions of residential customers as required, provides a cost-efficient option. However, most reported approaches to control PRDs require that demands of all residential customers are available, which are not viable for many LVDNs without smart meters or advanced metering infrastructure (AMI) installed. To bridging the gap in this field, this paper proposes a novel method to control PRDs purely based on measurable data from PRDs, and its controller. Based on limited information, sensitivity analysis in the network with PRDs is studied, followed by the optimization model that comprehensively considers operational requirements in the network. Moreover, slack variables are introduced to the model, and penalized in the objective function to assure either a strategy that is secure or with minimized violations can always be provided. The model is a challenging mixed-integer non-convex programming (MINCP) problem, which is reformulated as an efficient solvable mixed-integer second-order cone programming (MISOCP) based on exact reformulations or accurate linear approximations. Simulations based on two modified IEEE systems, and a real system in Australia demonstrate that an efficient strategy can be provided to mitigate unbalances in the network. [ABSTRACT FROM AUTHOR]

As residential PV generation penetrates in the low-voltage distribution network (LVDN), the unbalance issue may be intensified due to the asymmetry of generations/loads in different phases. Phase-reconfiguration device (PRD), which can reconfigure connected phases of residential customers, provides an effective method to address this issue. Noting that although the benefit brought by PRDs can vary if they are placed at different locations in the network, little literature has been reported on this topic. To bridge the research gap, this paper presents a novel method to optimally place PRDs in an LVDN aiming at minimizing the power unbalance running through the distribution transformer. The problem considers both installation, operational constraints, and boils down to a challenging mixed-integer non-convex programming problem, which is then reformulated as an efficient solvable mixed-integer linear programming problem. Moreover, operational constraints are relaxed with slack variables penalized in the objective function, which makes sure a feasible solution is always available without or with minimal operational violations. Case studies based on a modified IEEE system and a practical system in Australia demonstrate that an efficient strategy can be provided to address the unbalance issue while improving the network's power supply qualities. [ABSTRACT FROM AUTHOR]

As rooftop solar PVs installed by residential customers penetrate in low voltage distribution network (LVDN), some issues, e.g. over/under voltage and unbalances, which may undermine the network's operational performance, need to be adequately addressed. To mitigate unbalances in LVDN, phase-switching devices (PSDs) and static var compensator (SVC) are two equipment that is cost-effective and efficient. However, most existing research on operating PSDs is based on inflexible heuristic algorithms or without considering the network formulation, which may lead to strategies that violate operational requirements. Moreover, few pieces of literature have been reported on mitigating unbalances in LVDN via SVC and PSDs together. This paper formulates the decision-making process as a mixed-integer non-convex programming (MINCP) problem after developing an SVC model for dispatch purpose. Compared with existing work, the proposed method aims at minimizing current unbalance based on their phasor values and takes the network's operational requirements into account. To efficiently solve the challenging problem, the MINCP is reformulated as a mixed-integer second order-cone programming (MISOCP) problem based on either exact reformulations or accurate approximations, making it possible to employ efficient off-the-shelf solvers. Simulations based on two modified IEEE systems and a practical Australian LVDN demonstrates the efficiency of the proposed method in mitigating unbalances in LVDN. [ABSTRACT FROM AUTHOR]