Decreasing costs and favorable policies have resulted in increased penetration of solar photovoltaic (PV) power generation in distribution networks.As the PV systems penetration is likely to increase in the future, utilizing the reactive power capability of PV inverters to mitigate voltage deviations is being promoted.In recent years, droop control of inverterbased distributed energy resources has emerged as an essential tool for use in this study.The participation of PV systems in voltage regulation and its coordination with existing controllers, such as on-load tap changers, is paramount for controlling the voltage within specified limits.In this work, control strategies are presented that can be coordinated with the existing controls in a distributed manner.The effectiveness of the proposed method was demonstrated through simulation results on a distribution system.

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The rapid growth of distributed generator (DG) capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies, but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study, we investigate distribution system service restoration using DGs as the primary power source, and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore, the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.

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The output uncertainty of high-proportion distributed power generation severely affects the system voltage and frequency.Simultaneously, controllable loads have also annually increased, which markedly improve the capability for nodal-power control.To maintain the system frequency and voltage magnitude around rated values, a new multi-objective optimization model for both voltage and frequency control is proposed.Moreover, a great similarity between the multiobjective optimization and game problems appears.To reduce the strong subjectivity of the traditional methods, the idea and method of the game theory are introduced into the solution.According to the present situational data and analysis of the voltage and frequency sensitivities to nodal-power variations, the design variables involved in the voltage and frequency control are classified into two strategy spaces for players using hierarchical clustering.Finally, the effectiveness and rationality of the proposed control are verified in MATLAB.

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Using electric vehicles (EVs) for transportation is considered as a necessary component for managing sustainable development and environmental issues.The present concerns regarding the environment, such as rapid fossil fuel depletion, increases in air pollution, accelerating energy demands, global warming, and climate change, have paved the way for the electrification of the transport sector.EVs can address all of the aforementioned issues.Portable power supplies have become the lifeline of the EV world, especially lithium-ion (Li-ion) batteries.Li-ion batteries have attracted considerable attention in the EV industry, owing to their high energy density, power density, lifespan, nominal voltage, and cost.One major issue with such batteries concerns providing a quick and accurate estimation of a battery’s state and health; therefore, accurate determinations of the battery’s performance and health, as well as an accurate prediction of its life, are necessary to ensure reliability and efficiency.This study conducts a review of the technological briefs of EVs and their types, as well as the corresponding battery characteristics.Various aspects of recent research and developments in Liion battery prognostics and health monitoring are summarized, along with the techniques, algorithms, and models used for current/voltage estimations, state-of-charge (SoC) estimations, capacity estimations, and remaining-useful-life predictions.

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In order to improve the Power Quality (PQ) of traction power supply system and reduce the power rating and operation cost of compensator, a Static VAR Compensator (SVC) integrated Railway Power Conditioner (RPC) is presented in this paper.RPC is a widely used device in the AC electrified railway systems to enhance the PQ indices of the main network.The next generation of this equipment is Active Power Quality Compensator (APQC).The major concern of these compensators is their high kVA rating.In this paper, a hybrid technique is proposed to solve aforementioned problems.A combination of SVC as an auxiliary device is employed together with the main compensators, i.e., RPC and APQC that leads on to the reduction of power rating of the main compensators.The use of proposed scheme will cause to reduce significantly the initial investment cost of compensation system.The main compensators are only utilized to balance active powers of two adjacent feeder sections and suppress harmonic currents.The SVCs are used to compensate reactive power and suppress the third and fifth harmonic currents.In this paper firstly, the PQ compensation procedure in AC electrified railway is analyzed step by step.Then, the control strategies for SVC and the main compensators are presented.Finally, a simulation is fulfilled using Matlab/Simulink software to verify the effectiveness and validity of the proposed scheme and compensation strategy and also demonstrate that this technique could compensate all PQ problems.

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Integrated energy systems (IESs) represent a promising energy supply model within the energy internet.However, multi-energy flow coupling in the optimal configuration of IES results in a series of simplifications in the preliminary planning, affecting the cost, efficiency, and environmental performance of IES.A novel optimal planning method that considers the part-load characteristics and spatio-temporal synergistic effects of IES components is proposed to enable a rational design of the structure and size of IES.An extended energy hub model is introduced based on the “node of energy hub” concept by decomposing the IES into different types of energy equipment.Subsequently, a planning method is applied as a two-level optimization framework—the upper level is used to identify the type and size of the component, while the bottom level is used to optimize the operation strategy based on a typical day analysis method.The planning problem is solved using a two-stage evolutionary algorithm, combing the multiple-mutations adaptive genetic algorithm with an interior point optimization solver, to minimize the lifetime cost of the IES.Finally, the feasibility of the proposed planning method is demonstrated using a case study.The life cycle costs of the IES with and without consideration of the part-load characteristics of the components were $4.26 million and $4.15 million, respectively, in the case study.Moreover, ignoring the variation in component characteristics in the design stage resulted in an additional 11.57% expenditure due to an energy efficiency reduction under the off-design conditions.

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This paper presents an effective and feasible method for detecting dynamic load-altering attacks (D-LAAs) in a smart grid.First, a smart grid discrete system model is established in view of D-LAAs.Second, an adaptive fading Kalman filter (AFKF) is designed for estimating the state of the smart grid.The AFKF can completely filter out the Gaussian noise of the power system, and obtain a more accurate state change curve (including consideration of the attack).A Euclidean distance ratio detection algorithm based on the AFKF is proposed for detecting D-LAAs.Amplifying imperceptible D-LAAs through the new Euclidean distance ratio improves the D-LAA detection sensitivity, especially for very weak D-LAA attacks.Finally, the feasibility and effectiveness of the Euclidean distance ratio detection algorithm are verified based on simulations.

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In contrast to most existing works on robust unit commitment (UC), this study proposes a novel big-M-based mixed-integer linear programming (MILP) method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore, by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval, a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore, an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX, the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.

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This study considers the performance impacts of false data injection attacks on the cascading failures of a power cyber-physical system, and identifies vulnerable nodes.First, considering the monitoring and control functions of a cyber network and power flow characteristics of a power network, a power cyber-physical system model is established.Then, the influences of a false data attack on the decision-making and control processes of the cyber network communication processes are studied, and a cascading failure analysis process is proposed for the cyber-attack environment.In addition, a vulnerability evaluation index is defined from two perspectives, i.e., the topology integrity and power network operation characteristics.Moreover, the effectiveness of a power flow betweenness assessment for vulnerable nodes in the cyberphysical environment is verified based on comparing the node power flow betweenness and vulnerability assessment index.Finally, an IEEE14-bus power network is selected for constructing a power cyber-physical system.Simulations show that both the uplink communication channel and downlink communication channel suffer from false data attacks, which affect the ability of the cyber network to suppress the propagation of cascading failures, and expand the scale of the cascading failures.The vulnerability evaluation index is calculated for each node, so as to verify the effectiveness of identifying vulnerable nodes based on the power flow betweenness.

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Various distributed cooperative control schemes have been widely utilized for cyber-physical power system (CPPS), which only require local communications among geographic neighbors to fulfill certain goals.However, the process of evaluating the performance of an algorithm for a CPPS can be affected by the physical target characteristics and real communication conditions.To address this potential problem, a testbed with controller hardware-in-the-loop (CHIL) is proposed in this paper.On the basis of a power grid simulation conducted using the real-time simulator RT-LAB developed by the company OPAL-RT, along with a communication network simulation developed with OPNET, multiple distributed controllers were developed with hardware devices to directly collect the real-time operating data of the power system model in RT-LAB and provide local control.Furthermore, the communication between neighboring controllers was realized using the cyber system model in OPNET with an Ethernet interface.The hardware controllers produced a real-world control behavior instead of a digital simulation, and precisely simulated the dynamic features of a CPPS with high speed.A classic cooperative control case for active power output was studied to explain the integrated simulation process and validate the effectiveness of the co-simulation testbed.

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