Technological advancement, environmental concerns, and social factors have made plug-in electric vehicles (PEVs) popular and attractive vehicles. Such a trend has caused major impacts to electrical distribution systems in terms of efficiency, stability, and reliability. Moreover, excessive power loss, severe voltage deviation, transformer overload, and system blackouts will happen if PEV charging activities are not coordinated well. This paper presents an optimal charging coordination method for a random arrival of PEVs in a residential distribution network with minimum power loss and voltage deviation. The method also incorporates capacitor switching and on-load tap changer adjustment for further improvement of the voltage profile. The meta-heuristic methods, binary particle swarm optimization (BPSO) and binary grey wolf optimization (BGWO), are employed in this paper. The proposed method considers a time-of-use (ToU) electricity tariff such that PEV users will get more benefits. The random PEV arrival is considered based on the driving pattern of four different regions. To demonstrate the effectiveness of the proposed method, comprehensive analysis is conducted using a modified of IEEE 31 bus system with three different PEV penetrations. The results indicate a promising outcome in terms of cost and the distribution system stress minimization.
Integration of plug‐in electric vehicles (PEVs) in a smart grid largely deteriorates the performances of the system. This paper proposes a two‐stage optimization approach to optimize customer satisfaction as well as grid performances when fixed charge–rate PEV coordination, switching capacitor and on‐load tap charger (OLTC) are coordinated simultaneously. To coordinate PEV charging, capacitor and OLTC, an efficient binary particle swarm optimization (BPSO) has been applied. The main consideration in this optimal coordination is to minimize the daily power loss and voltage deviation while maximizing customer satisfaction. Simulation results are compared with the variable charge–rate coordination that is proposed previously. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Plug-in electric vehicles (PEVs) are gaining popularity as an alternative vehicle in the past few years. The charging activities of PEVs impose extra electrical load on residential distribution system as well as increasing operational cost. There are multiple conflicting requirements and constraints during the charging activities. Therefore, this paper presents multiobjective PEV charging coordination based on weighted sum technique to provide simultaneous benefits to the power utilities and PEV users. The optimization problem of the proposed coordination is solved using binary particle swam optimization. The objectives of the coordination are to (i) minimize daily power loss, (ii) maximize power delivery to PEV, and (iii) minimize charging cost of PEV considering time-of-use tariff. In order to determine balance weighting factor for each of these objectives, analytic hierarchy process is applied. By using this approach, the best result of charging coordination can be achieved compared to uncoordinated charging. A 23-kV residential distribution system with 449-nodes is used to test the proposed approach. From the attained results, it is shown that the proposed method is effective in minimizing power loss and cost of charging with safe operation of distribution system.
Research on network reconfiguration (NR) considering distributed generations (DG) is typically concerns on the issues of power loss, voltage deviation, DG sizing as well as its placement, which are important and required in the planning stage. On the other hand, another important aspect which often neglected in this stage is coordination of protection devices which is essential to prevent the network from damages following system breakdown. Without sufficient attention given to the protection coordination during NR, there is a possibility for the protective devices to miscoordinate and consequently lead to system blackout, due to changes in current flow and fault level. Therefore, this paper proposed an NR method for distribution networks with DG, incorporating protection devices. The proposed method aims to find the optimal configuration and DG size with minimum power loss, and at the same time ensuring protective devices operate correctly during normal and fault condition. Constraints on protection coordination and DG size are explicitly formulated in the proposed method. The validity of the proposed method is analyzed on three commonly used IEEE 33-bus, 69-bus and 118-bus distribution systems, employing the firefly algorithm (FA) and evolutionary programming (EP) algorithm. Comparative studies are done to prove the validity and robustness of the proposed method. HAZLIE MOKHLIS (M'01-SM'18) received the B.Eng. and M.Eng.Sc. degrees in electrical engineering from the
In this work a review of existing fire-detector types has been carried out along with the development of a low cost, portable, and reliable microcontroller based automated fire alarm system for remotely alerting any fire incidents in household or industrial premises. The aim of the system designed is to alert the distant property-owner efficiently and quickly by sending short message (SMS) via GSM network. A Linear integrated temperature sensor detects temperature beyond preset value whereas semiconductor type sensor detects presence of smoke or gas from fire hazards. The sensor units are connected via common data line to ATMega8L AVR microcontroller. A SIM300CZ GSM kit based network module, capable of operating in standard GSM bands, has been used to send alert messages. The system is implemented on printed circuit board (PCB) and tested under different experimental conditions to evaluate its performances.
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