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Automation in power distribution systems and supervisory control and data acquisition (SCADA), which perform network switching automatically and remotely, allows distribution companies to flexibly control distribution power grids. Cross-section switches also has a significant role in the automation in distribution systems, in that the operational optimization of these switches is able to enhance the supply power quality and reliability indicators, and can be a prosperous solution to increase the reliability, efficiency and overall service quality in services to customers. In this regard, in this work, the genetic optimization algorithm (GOA) approach which integrated the Steepest Descend Technique (SDT) is proposed and enhanced based on the features of the mentioned issue to sketch the optimal location and control of automatic and manual cross-section switches and protection relay systems in distribution power systems. The GOA is able to search globally that can prevent the result from locally convergence, also, GOA gives superior primary solutions for the SDT. Thus, the SDT can search locally with higher performance which increase the solutions’ accuracy. Therefore, an optimization formulation is proposed to improve the value-based reliability of the suggested layout considering the cost of customer downtime and the costs related to segmentation of switches and relay protection devices. Also, a distributed generation (DG) system in distribution networks is considered based on the islanded state of generation units. The effectiveness of the optimal suggested procedure is evaluated and represented via performing a practical test system in the distribution network of Ahvaz city in Iran. The results show that using proposed method and by optimally allocating switches maneuver, energy losses without switches are reduced from 310.17 (MWh) to 254.2 (MWh), and also by using DG, losses are reduced from 554.01 to 533.61 which confirms the ability and higher accuracy of the proposed method to improve reliability indices.

In this paper, a nonlinear, bounded, distributed secondary control (DSC) method is proposed to coordinate all the distributed generators (DGs) in islanded AC microgrids (MGs). This proposed consensus-based DSC strategy can not only guarantee the restoration control of frequency and voltage but also realize an accurate active power sharing control. Through introducing a nonlinear dynamic from beta cumulative distribution function (CDF), the convergence speed of DSC is accelerated, the asymptotical convergence of DSC is ensured, and the transient overshoot of DSC is diminished compared with traditional DSC. Moreover, by ensuring the Lipchitz continuity characteristic of the control algorithm, the common chattering phenomenon in non-Lipchitz DSC scheme is eliminated. The stability and performance of the proposed DSC are also analyzed in this paper. An islanded AC microgrid test system with four inverter-based DGs is built in MATLAB/SIMULINK to further validate the effeteness of the proposed DSC strategy.

Lithium-ion batteries are generally regarded as a leading candidate for energy storage systems. The safe and reliable operation of lithium-ion batteries depends largely on accurate estimation of the state of charge (SOC), which requires an accurate battery model. Bearing strong mechanisms, the electrochemical model (EM) can mimic the battery dynamics with high fidelity, and thus the EM-based methods can produce more reliable SOC estimates. This paper proposes a novel EM-based SOC estimation method for lithium-ion batteries from the electrochemical mechanism perspective. Firstly, a single particle model is employed to gain a direct insight into the electrochemical reactions inside the battery, and it is found that the model output voltage and SOC are strongly related to the lithium-ion concentrations of solid phases. A simple negative voltage feedback module is then applied to observe the voltage error between the cell referenced terminal voltage and the model output voltage. To eliminate the voltage error and achieve a precise estimate, a quantitative relationship between the voltage error and corrected amount of lithium-ion concentrations is deduced based on the Nernst equation. The performance of proposed method has been systemically evaluated under different operating conditions, including various charging and discharging current rates, erroneous initial SOCs, and cell aging levels. Although an erroneous initial SOC of 50% is applied to the proposed algorithm, promising estimates with the mean absolute errors of 0.22% and 1.35% can be still achieved under the constant and dynamic loading conditions, respectively.

In this paper, we investigate downlink cooperative multiple-input single-output wireless sensor networks with the nonorthogonal multiple access technique and simultaneous wireless information and power transfer over Nakagami-m fading. Specifically, the considered network includes a multiantenna sink node, an energy-limited relay cluster, a high-priority sensor node (SN) cluster, and a low-priority SN cluster. Prior to transmission, a transmit antenna, a relay, a high-priority SN, and a low-priority SN are selected. In this paper, we propose three antenna-relay-destination selection schemes, i.e., sink node-high-priority, sink node-relay, and sink node-low-priority. In each proposed scheme, we consider two relaying strategies, i.e., decode-and-forward and amplify-and-forward, and then, we derive the corresponding closed-form expressions of outage probability at the selected SNs. In addition, we introduce two algorithms: 1) the powersplitting ratio optimization algorithm and 2) the best antenna-relay-destination selection determination algorithm. Finally, we utilize the Monte Carlo simulations to verify our analytical results.

Unexpected natural disasters or physical attacks can have various consequences, including extensive and prolonged blackouts on power systems. Energy systems should be resistant to unwanted events, and their performance is not easily affected by such conditions. The power system should also have sufficient flexibility to adapt to severe disturbances without losing its full version; it should restore itself immediately after resolving the disturbance. This critical feature of the behavior of infrastructure systems in power grids is called resilience. In this paper, the concepts related to resilience in the power system against severe disturbance are explained. The resilience and evaluation process components are introduced; then, an optimal design of resilient substations in the Noorabad city distribution grid against physical attack is presented. This research proposes an optimal solution for simultaneously allocating the feeder routing issue and substation facilities and finding the models of installed conductors and economic hardening of power lines due to unexpected physical attacks on vital urban operational infrastructure. The values of distribution networks are calculated using the grey wolf optimization (GWO) algorithm to solve the problem of designing an optimal distribution network scheme (ODNS) and optimal resilient distribution network scheme (ORDNS). Obtained results confirm the effectiveness of the proposed resiliency-cost-based optimization approach.

The integration of battery energy storage (BES) with photovoltaic (PV) systems is becoming economically attractive for residential customers. The conventional approach for the interconnection of PV and battery systems requires at least two separate power converters that results in multistage power conversion for some power flows. The dc-dc three port converters (TPCs) are an alternative solution. These converters have many topological variants and possess different operating principles, topological benefits and limitations, and complexities. This paper concentrates on the topological study of TPCs for integrated PV and BES systems applications in the power range from a few hundred watts to 350 kW. These are classified into three different categories based on their isolation features between the ports to establish a topological mapping of the reported TPCs. This provides a framework that systematically explores the full range of technical benefits and limitations of each TPC topology. This paper also examines the possible extension of the TPC topologies for grid-interactive PV-BES systems where bidirectional power flow capability is required between grid and BES systems. This extensive review will provide a useful framework and a strong point of reference for researchers for the selection of TPC topologies to meet the system requirements for PV and energy storage applications.

The recent increase in electricity tariff and the introduction of feed-in tariff from renewable resources have increased the interest of energy consumers, such as those in commercial and residential buildings, in reducing their energy usage. This paper proposes a smart power socket and central control system that utilizes the Zigbee communication protocol to control energy usage. The system is designed such that smart sockets wirelessly provide the necessary data to a central controller. Then, the system analyzes the data to generate control commands to turn the devices attached to the smart socket ON or OFF. Experimental results show that the proposed smart socket can correctly read the power consumption of wirelessly connected devices from up to 18 m away without loss of data. The central controller can effectively control multiple sockets on the basis of a scheduled user program code. A 24-min implementation of the proposed energy management algorithm shows a reduction of 0.811 kWmin (0.0134 kWh) in energy usage after the use of the smart sockets as load controllers. Thus, the proposed smart socket system can be fully utilized in a home energy management system with a proper scheduling algorithm.