A direct approach for unbalanced three-phase distribution load flow solutions is proposed in this paper. The special topological characteristics of distribution networks have been fully utilized to make the direct solution possible. Two developed matrices-the bus-injection to branch-current matrix and the branch-current to bus-voltage matrix-and a simple matrix multiplication are used to obtain load flow solutions. Due to the distinctive solution techniques of the proposed method, the time-consuming LU decomposition and forward/backward substitution of the Jacobian matrix or Y admittance matrix required in the traditional load flow methods are no longer necessary. Therefore, the proposed method is robust and time-efficient. Test results demonstrate the validity of the proposed method. The proposed method shows great potential to be used in distribution automation applications.

Utilizing battery storage systems (BSSs) can reduce the intermittent output of PV generation systems (PVGSs) and make them dispatchable. The aim of this paper is to design an optimal charging/discharging scheduling for BSSs such that the line loss of distribution systems interconnected with sizeable PVGSs can be minimized. A mathematical model for BSSs which can be used to simulate the charging procedures such as the commonly-used constant current to constant voltage (CC-CV) charging method, the discharging procedures and the state of charge (SOC) is proposed first. The minimum line loss problem considering the intermittent output of PVGSs and the scheduling of BSSs is then formulated based on the BSS mathematical model. The optimal charging/discharging scheduling of BSSs can then be obtained by a genetic algorithm (GA) based method. Test results demonstrate the validity of the proposed mathematical model and optimal charging/discharging scheduling for BSSs.

This paper uses a charging selection concept for plug-in electric vehicles (PEVs) to maximize user convenience levels while meeting predefined circuit-level demand limits. The optimal PEV-charging selection problem requires an exhaustive search for all possible combinations of PEVs in a power system, which cannot be solved for the practical number of PEVs. Inspired by the efficiency of the convex relaxation optimization tool in finding close-to-optimal results in huge search spaces, this paper proposes the application of the convex relaxation optimization method to solve the PEV-charging selection problem. Compared with the results of the uncontrolled case, the simulated results indicate that the proposed PEV-charging selection algorithm only slightly reduces user convenience levels, but significantly mitigates the impact of the PEV-charging on the power system. We also develop a distributed optimization algorithm to solve the PEV-charging selection problem in a decentralized manner, i.e., the binary charging decisions (charged or not charged) are made locally by each vehicle. Using the proposed distributed optimization algorithm, each vehicle is only required to report its power demand rather than report several of its private user state information, mitigating the security problems inherent in such problem. The proposed decentralized algorithm only requires low-speed communication capability, making it suitable for real-time implementation.

Commercial lithium-ion batteries are playing important roles as supplies for mobile phones, laptop computers, and other electronics. In order to maximize the performance of lithium-ion batteries, an advanced rapid charging pattern is required. In this paper, an Ant-Colony-System (ACS)-based algorithm is presented. The proposed ACS-based algorithm can be integrated into a commercially available battery tester to search for the optimal rapid charging pattern. Experimental results show that the obtained rapid charging pattern is capable of charging the lithium-ion batteries to 70% capacity in 30 min. The obtained pattern also provides 25% more cycle life than the conventional constant current-constant voltage method.

Fault indicating devices such as fault indicators (FIs) have been widely used in distribution systems to improve reliability and reduce outage duration. Recently, FIs with communication interfaces are integrated into distribution automation (DA) to further reduce fault-finding time by reporting FIs' statuses back to control center. When faults occur, a lot of alarms and fault information are received from Outage Management System (OMS), Trouble Call System (TCS) and Customer Information System (CIS) and are shown to system operators. As a result, the identification of faulted line sections in a wide-ranging distribution system from FIs' statuses is not an easy task, especially when multiple faults occur simultaneously and/or distributed generators (DGs) are connected. An automatic and fast faulted line-section location method for distribution systems based on FIs is proposed in this paper. The line sections between adjacent FIs can be treated as a possible fault location (PFL) and the fault current detected by the FI can be considered as line current (LC) flowing between the adjacent PFLs. A relationship matrix between PFLs and LCs is then derived and used to design the proposed automatic and fast faulted line-section location method. The faulted line sections can then be located effectively and efficiently by the proposed method. Test results for an actual distribution system demonstrate the validity of the proposed faulted line-section location method.