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• This paper proposes a two-layer operational optimization model of concentrated solar power (CSP) with thermal energy storage system (TESS) and soft open point (SOP) at first time. • According to the demand of load, the upper-layer planning formulates the optimal scheduling strategy of photovoltaic (PV), wind power (WP), CSP, energy storage system (ESS) and power purchase through the schedulability of CSP with TESS. • Then, the upper-layer scheduling results are connected to the lower-layer distribution network, and coordinated control is carried out through SOP, on-load tap changer (OLTC) and capacitor bank (CB).The results show that the proposed model in this paper not only ensures the economy of the power grid but also improves the stability of the voltage. In order to improve the dispatching and grid-connected capacity of new energy, enhance the comprehensive economic benefits, and reduce the voltage offset and fluctuation of the distribution network, this paper proposes a two-layer operational optimization model of concentrated solar power (CSP) with thermal energy storage system (TESS) and soft open point (SOP). Firstly, according to the demand of load, the upper-layer distribution network formulates the optimal scheduling strategy of photovoltaic (PV), wind power (WP), CSP, energy storage system (ESS) and power purchase through the schedulability of CSP with TESS. Secondly, the upper-layer scheduling results are connected to the lower-layer distribution network, and coordinated control is carried out through SOP, on-load tap changer (OLTC) and capacitor bank (CB). Then, the lower model is converted into a linear model, a quadratic cone model and a rotated quadratic cone model, followed by absolute value removal, so as to rapidly and accurately produce the solution of the model. Finally, the model is analyzed on the improved IEEE33 node system. The results show that the proposed model in this paper not only ensures the economy of the power grid but also improves the stability of the voltage. [ABSTRACT FROM AUTHOR]

• Proposes novel dc grid device based on capacitive energy storage. • Reduces fault current and voltage drop of voltage source converters under dc faults. • Reduces overvoltages under pole-to-ground faults in symmetrical monopole grids. • Improves power flow security by preventing converter blocking. • Improves transient dc grid stability. A major and very important challenge in dc grid development is maintaining continuous converter operation under dc faults. This paper proposes a novel capacitive energy storage device which improves security of dc grids by avoiding terminal blocking. The device provides current from the capacitor bank during dc faults, reducing fault current contribution and voltage drop of dc grid converters. Moreover, the device also helps in balancing pole voltages which is of particular significance during pole-to-ground faults in symmetrical monopole systems. Other benefits like improved transient grid stability are also demonstrated. Device's design and performance is assessed using theoretical analysis and verified on a three-terminal offshore dc grid model in PSCAD. The cost of the device's electronics is minimized and the total cost and weight estimation are also shown. [ABSTRACT FROM AUTHOR]

• A distributed multi-time scale voltage control strategy is proposed, that combines distributed control with data-driven SOP. • This DRL method only needs local information to make decisions in the actual control process. • A partition scheme that fits the reactive power compensation capability of SOP is designed. In the context of the increasing penetration level of photovoltaic energy, its intermittence and randomness bring challenges such as voltage over-limit and increased network loss to the distribution network. The paper proposes a real-time two-time-scale voltage regulation method with soft open point (SOP) to solve the reactive power optimization problem. To obtain hourly scheduling strategies for on-load tap changers and switchable capacitor banks, the centralized optimization problem is formulated as a mixed integer second-order cone programming in the first stage. In the second stage, the active distribution system is divided into multiple subsystems according to the proposed partitioning method, and the SOP is regulated to adjust the voltage in real-time through an effective control strategy and local measurement information of the subsystems. The proposed method takes full account of the randomness of photovoltaic, and can conduct distributed real-time voltage regulation in the active distribution system based on the rapid and continuous response of SOP. Compared with traditional methods, this method has lower communication costs, better real-time performance, and does not dependent on an accurate power flow model. Finally, the effectiveness of the proposed method is verified by the IEEE 33-bus and IEEE 123-bus simulation examples. [ABSTRACT FROM AUTHOR]

Highlights • Convex model for simultaneous capacitor allocation and feeders' reconfiguration. • Convex voltage-dependent models for loads and capacitor banks. • Strategy to reduce the number of candidate nodes for capacitor banks allocation. • Analysis of the impact of the voltage-dependent models on the problem's solution. Abstract This paper presents a study about operation planning for radial distribution systems using a mixed-integer second-order cone programming formulation. The proposal consists of a complete model for solving the problems of the reconfiguration of feeders and allocation of capacitor banks simultaneously, with the objective of achieving a minimum overall investment, in both fixed and switchable capacitor banks, and operational costs, related to the cost of energy losses. The approach includes a voltage-dependent load representation, as well as a precise representation of the operation of capacitor banks, which is also voltage dependent. The use of a mixed-integer second-order cone programming model guarantees convergence to optimality using existing optimization software. A strategy to reduce the number of candidate nodes of the system for capacitor banks allocation is also presented. Several tests are performed using the 69-node distribution system and a real 2313-node distribution system, demonstrating the effectiveness of the proposal. The results indicate that better solutions can be obtained by performing the simultaneous optimization of the reconfiguration and allocation of capacitor banks than by solving the two problems sequentially, which may even lead to infeasible solutions. It is also verified that both the load and capacitor banks models have an influence on the problem's solution. [ABSTRACT FROM AUTHOR]

Highlights • A bi-level robust planning model for active management elements is proposed. • Variables in both investment level and operation level are associated together. • The planning model can be formulated as a mixed integer second order conic problem. • The renewable uncertainties in four seasons is addressed by a typical budget uncertainty set. • The two-stage robust mathematical model is solved by CCG algorithm. Abstract The distribution companies will face huge challenges in upgrading the existing network due to the uncertain integration of distributed renewable generations. In this paper, we propose a bi-level robust planning model for active management elements (AMEs) including on-load tap changer (OLTC), electrical storage system (ESS), capacitor bank (CB), and static VAR compensation (SVC) in order to accommodate uncertain development of wind power and photovoltaic power. The planning problem is constructed in two levels which are investment level and operation level. To overcome the poor convergence of the bi-level model, variables in both investment level and operation level are associated together. After equivalent transformation for non-linear terms the planning model can be formulated as a mixed integer second order conic programming (MISOCP) problem by some special means such as second order conic relaxation (SOCR) and big-M approach. We address the renewable uncertainties in four different seasons by a typical budget uncertainty set with adjustable budget. Then a two-stage robust mathematical model is proposed to decide a robust AME deployment scheme and solved by column and constraint generation (CCG) algorithm. [ABSTRACT FROM AUTHOR]

• A new centralized voltage regulation method for a distribution network is proposed. • The voltage fluctuation issues in a distribution network containing high levels of photovoltaic power are solved. • The probability-based worst-case voltage scenarios of a distribution network are established. • A fast decision-making algorithm is developed to select the best solution from the Pareto optimal set. One of the most significant current concerns in distribution networks is the voltage fluctuations resulting from sharp changes of the active power of photovoltaic (PV) plants. Therefore, this paper proposes a novel worst-case voltage scenarios (WCVSs) based centralized voltage regulation method to suppress the voltage fluctuations of all buses in distribution networks, where the WCVSs are established according to probabilities of bus voltages exceeding the required voltage range. A mixed integer nonlinear programming (MINP) model is developed to coordinate on-load tap changers (OLTCs), capacitor banks (CBs), and PV plants, aiming at reducing switching operations of OLTCs and CBs, bus voltage variations, operating losses of distribution networks, and active power curtailments of PV plants. This paper employs the NSGA-II algorithm to find the Pareto optimal set of the established MINP model, and a fast decision-making algorithm is proposed to select the best solution from the Pareto optimal set. The proposed methods are conducted on a modified IEEE 33-bus distribution network with high penetrations of PV power. Simulation results show that the proposed voltage control methods can not only effectively deal with voltage fluctuation issues in the distribution network, but also reduce the operating costs of the distribution network. [ABSTRACT FROM AUTHOR]

• A new MILP formulation for volt-var optimization of distribution systems. • Clustering method to select scenarios of chronological operation of loads and DERs. • Decentralized volt-var control of capacitor banks and voltage regulators. • Formulation of a current hysteresis controller of automatic capacitor banks. • Tap operation control of voltage regulator with line drop compensation and saturation. This paper presents a mixed-integer linear programming model for volt-var optimization considering the chronological operation of distribution systems containing distributed energy resources (DERs). The proposed model describes the operation problem of capacitor banks (CBs) and voltage regulators (VRs), and it is further based on the steady-state operation during each time interval contained in typical scenarios of distribution systems. A procedure using a K-means clustering algorithm is used to select the scenarios, thus preserving the simultaneity and chronological combination of different loads and DERs. According to the formulation that we developed, the regulation devices become sensitive to downstream load variations, since we use explicit current variables to control automatic CBs, and since we include means to compensate voltage drops along distribution lines in the control of VRs. The model is validated by comparing the results obtained during several tests of two typical cases with those obtained through nonlinear power flow. The typical case studies presented in the paper highlight the good agreement between the results obtained with the linearized model and with power flow method; further, the practical results confirm that the use of typical scenarios allows representing different levels of loads and DERs, while keeping the validity and performance of the proposed model. [ABSTRACT FROM AUTHOR]

The progression towards smarter grids, incorporating clean energy resources, has increased the integration of distributed generators (DGs) into power distribution networks. The DGs often cause a rise in voltage at their points of common coupling. Ordinary voltage regulation devices such as on-load tap changers (OLTCs) are not capable of addressing these issues adequately without careful coordination with DGs. In this paper, a new supervisory control and data acquisition-based two-stage voltage control scheme for the coordination of an OLTC transformer, capacitor banks (CBs) and the DGs is presented. The proposed scheme sets forth a new criterion for the selection of tap positions of an OLTC. In the first stage, tap positions of the OLTC are changed optimally using the micro genetic algorithm, whereas in the second stage, a recursive genetic algorithm is run to minimise the power losses in order to find the optimal reactive powers for the distribution network. Stochastic modelling of wind speed and solar irradiance data is also performed. The scheme is verified by studying it under four different test cases. An OLTC, CBs, photovoltaic panels, wind power DGs and dispatchable DGs are installed in the distribution network, and an IEEE 37-node test feeder is used for the verification of the proposed scheme. The simulation results show that the scheme achieves the objective of voltage regulation. [ABSTRACT FROM AUTHOR]

• This paper presents a novel spatiotemporal feature learning for cause identification of the EMTE in transmission systems. • Five EMTE events, i.e., line energization, capacitor bank energization, lightning, fault, and high-impedance fault are considered. • The event classification framework is formulated using the convolutional neural network (CNN). • The results of this work can benefit the utilities to increase the situational awareness of very fast electromagnetic transient events. This paper presents a spatiotemporal feature learning method for cause identification of electromagnetic transient events in power grids. The proposed method is formulated based on the availability of time-synchronized high-frequency measurements and using the convolutional neural network as the spatiotemporal feature representation along with softmax function for the classification. Despite the existing threshold-based, or energy-based events analysis methods, such as support vector machine autoencoder, and tapered multi-layer perceptron neural network, the proposed feature learning is carried out with respect to both time and space. The effectiveness of the proposed feature learning and the subsequent cause identification is validated through the Electromagnetic Transients Program (EMTP) simulation of different events such as line energization, capacitor bank energization, lightning, fault, and high-impedance fault in the IEEE 30-bus, and the real-time digital simulation of the Western System Coordinating Council (WSCC) 9-bus system. [ABSTRACT FROM AUTHOR]

• Propose a double-time-scale voltage control based on MPC for unbalanced ADNs. • Design a tailored solution method combining McCormick envelopes and Branch-and-Bound algorithm. • Develop an ADMM-based distributed solution method for the proposed voltage control scheme. With the increasing penetration of distributed generators (DGs) in the distribution system, the distributed coordinated optimal control of DG and voltage control devices has become imperative. This paper proposes a double-time-scale distributed voltage control scheme for unbalanced distribution networks with distributed generators based on model predictive control (MPC) and alternating direction method of multiplier (ADMM) to regulate the voltage profile across a network. To better coordinate the economical operation and voltage regulation, the voltage control devices with different temporal characteristics are separately adjusted. In the fast-time-scale control, the decision variables are the active and reactive power outputs of DGs. In the slow-time-scale control, the on-load tap changer, step voltage regulators and capacitor banks are optimized. A tailored solution method based on McCormick envelopes and branch-and-bound algorithm is developed to efficiently solve the optimization problems by transforming the mixed-integer nonlinear program (MINLP) into a second order cone program (SOCP). The voltage control scheme is a combinatorial optimization problem whose computational complexity grows exponentially with the number of binary variables. To resolve this issue, a distributed optimal voltage control strategy is developed based on the alternating direction method of multipliers (ADMM). Through the ADMM, the optimization problem is distributed among the zones of the distribution networks, without requiring a central controller. The modified IEEE 123-node system is used to verify the effectiveness of the proposed control scheme as a test system. [ABSTRACT FROM AUTHOR]

To meet ever increasing load demand in a sustainable way, reinforcement of photovoltaic (PV) array, wind turbine (WT) and capacitor bank in distribution network is proposed in this paper. A comprehensive planning model is presented to determine location and required installation capacity of multiple PV array, WT and capacitor units in an electric power distribution network under heavy load growth situation. Intermittent power generation of renewable energy sources (RESs) are quantified with suitable probability distribution functions and incorporated in the planning model. The planning approach considers several welfare areas in the distribution systems, viz., increment of profit margin, reduction of carbon-di-oxide emission, minimization of distribution power losses, enhancement of voltage stability level and improvement of the network security considering power flow, voltage limit, line capacity, RES penetration, capacitor penetration and utility economy constraint. Non-dominated sorting based multi-objective particle swarm optimization algorithm along with fuzzy decision making criteria is used to find the best allocation alternative for mix RES and capacitor planning problem. The effectiveness of the proposed model has been tested on a typical 28-bus Indian rural distribution network. The results show that more efficient techno-eco-environmental optimization can be obtained from combined RES and capacitor planning model. [ABSTRACT FROM AUTHOR]

• Determining the influence of the prestrike characteristics of four types of VCBs combined with two types of controlled switching strategies on the suppression effect of the inrush current. • Proposing a novel controlled switching strategy which the closing command depends on the 50% pre-arcing time t a50 of the VCBs. • The spiral-type TMF double-break VCB combined with the novel controlled switching strategy is the best choice for applying back-to-back capacitor bank controlled switching. Controlled switching of capacitor banks is an effective way to suppress the inrush current during capacitive-making operations. The objective of this paper is to determine the influence of the prestrike characteristics of four types of vacuum circuit breakers (VCBs) combined with two types of controlled switching strategies on the suppression effect of the inrush current. The four types of VCBs are cup-type axial magnetic field (AMF) single-break VCB, spiral-type transverse magnetic field (TMF) single-break VCB, cup-type AMF double-break VCB and spiral-type TMF double-break VCB. The prestrike characteristics of the four types of VCBs are investigated by synthetic tests. The two types of controlled switching strategies are the traditional controlled switching strategy (the closing command depends on the mechanical touch instant of the two contacts in VCBs) and the novel controlled switching strategy (the closing command depends on the 50% pre-arcing time t a50 of the VCBs). The results show that the spiral-type TMF double-break VCB combined with the novel controlled switching strategy is the best choice for applying back-to-back capacitor bank controlled switching. © 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

• Improving the voltage in a wind farm by a self-corrective static VAR compensator. • Considering the steady-state and transient modes under harsh faults in analysis. • Enhancing the system performance by employing an optimized Battery Energy Storage. • Reporting the results in different cases, with or without the mentioned equipment. Maintaining synchronism and voltage stability, especially in the presence of wind farms, has a crucial role in confirming the reliability requirements of the power grid, as the natural fluctuations of wind speed result in intermittency and uncontrollability of power generation. To this end, an optimized Battery Energy Storage System (BESS) was suggested to make an equilibrium between the generation and consumption in wind farms under harsh conditions. Additionally, the instability of wind farms is very likely after transmission line faults occur. To overcome this problem, in this paper, the impact of a constant capacitor bank, connected in parallel with the wind generators, is investigated. Also, a novel self-corrective Static Volt-ampere reactive Compensator (SVC) is proposed to overcome the variations of voltage and damp the reactive power oscillations after occurring the faults. The proposed SVC compares the network voltage profile as the reference voltage with the voltage deviations in a control block diagram. For this purpose, three similar wind farms of Permanent Magnet Synchronous Generator (PMSG) type are considered in a wind park. The simulation case studies are performed in Matlab/Simulink under different conditions of transient and steady-state voltage stabilities in the presence of proposed BESS including, only capacitor bank (without self-corrective SVC), and with self-corrective SVC. The results authenticate the ability of the proposed SVC strategy to correct the voltage deviations, and voltage stability improvement of the under study system. [ABSTRACT FROM AUTHOR]

Capacitor banks are commonly used in electric distribution networks as a kind of reactive power sources. These sources are located in distribution networks for power factor correction, loss reduction, and voltage profile improvement. For these purposes optimal capacitor placement is needed to determine capacitors types, sizes and locations. Distribution system with Distributed Generation (DG) can have micro-grid that it will operate in both grid-connected and islanded modes of operation. The aim of this paper is to provide a method for optimal capacitor (fixed and switchable) placement in such a distribution network. The effect of different operation modes of DGs on the network is also investigated. The proposed method can guarantee the benefits of capacitor installation at different load levels. It is based on genetic algorithm (GA) with new coding and operators. Switching table of the allocated capacitors can be found through the proposed structure of the chromosome. Some case studies developed to illustrate the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, two new algorithms are implemented to solve optimal placement of capacitors in radial distribution systems in two ways that is, optimal placement of fixed size of capacitor banks (Variable Locations Fixed Capacitor banks-VLFQ) and optimal sizing and placement of capacitors (Variable Locations Variable sizing of Capacitors-VLVQ) for real power loss minimization and network savings maximization. The two bio-inspired algorithms Bat Algorithm (BA) and Cuckoo Search (CS): search for all possible locations in the system along with the different sizes of capacitors, in which the optimal sizes of capacitor are chosen to be standard sizes that are available in the market. To check the feasibility, the proposed algorithms are applied on standard 34 and 85 bus radial distribution systems. And the results are compared with results of other methods like Particle Swarm Optimization (PSO), Harmonic Search (HS), Genetic Algorithm (GA), Artificial Bee Colony (ABC), Teaching Learning Based Optimization (TLBO) and Plant Growth Simulation Algorithm (PGSA), as available in the literature. The proposed approaches are capable of producing high-quality solutions with good performance of convergence. The entire simulation has been developed in MATLAB R2010a software. [ABSTRACT FROM AUTHOR]

• Utilizing some uncomplicated calculations to detect and determine the number of faulty elements. • Discriminating the capacitor units' failures that may happen simultaneously or with sub-cycle delays in one phase. • The proposed algorithm will help the capacitor units be easily monitored for the different protection design (i.e., fuseless and internally fused units). • Eliminating the transient DC component in the case of external short circuit fault conditions. Failure in quick detection and location of internal failures in Shunt Capacitor Banks (SCBs) may lead to the negligence of necessary repair processes, consequently laying undesirable effects on the power system operation. This paper puts forward a failure detection and fault location method in SCBs with the double wye connection. The proposed method provides a criterion for relay decision-making based on the neutral voltage and current fundamental phasor component, capable of distinguishing the faulty capacitors and determining the number of capacitor failures in the case of multiple faulty phases. The proposed algorithm can be applied for double wye SCBs considering different protection designs, namely fuseless and internally fused units. The proposed method is designed to monitor and detect consecutive failures based on the existing data from commercial relays. Implementation and performance evaluations are conducted in PSCAD and MATLAB software and also with the help of practical data. Performance evaluations are conducted under different circumstances, namely harmonic distortion and voltage unbalance conditions, multiple internal fault locations, and external faults from the grid. Simulation results show the significance and salient features of the proposed method under different conditions. [ABSTRACT FROM AUTHOR]

Successfully detecting High Impedance Faults (HIFs) is a challenge for distribution systems' protection specialists due to the random behavior and low magnitude of the fault current. To contribute to this problem's solution, this paper proposes a new approach for HIF detection based on the energy variation of the low harmonic orders obtained by the Stockwell transform and an adaptive threshold used to ensure high sensitivity and secure detection. Tests with the IEEE 34-node test feeder were performed using actual HIF currents recorded experimentally at a test field, considering different soil types. The proposed method also considered the HIF distinction from other events, such as capacitor banks and lateral branches switching, transformer energizing, motor starting, and linear and non-linear loads (arc furnace and a rectifier) connection. A thorough analysis regarding false operation has shown that the proposed approach is effective for distinguishing HIFs from other events. Furthermore, test results indicated that the method is a secure and promising technique for HIF detection, even with noise in the current measurements. • The method detects high impedance faults using harmonics energy variation. • It uses a self-adaptive threshold strategy that considers the conductor fall period. • The method presents high accuracy and reliability even in noisy conditions. • Method validated with real high impedance fault currents at multiple fault locations. • It shows unprecedented false operation analysis, correctly distinguishing the faults. [ABSTRACT FROM AUTHOR]

• A new fault classification approach is presented for series-compensated line. • One-end current-based fault location method is proposed. • Different series-capacitor compensation configurations are analyzed. • The scheme is economic, reliable, fast, and generalized. This paper proposes a new efficient method for fault detection, faulty phase selection, and fault point identification on series capacitor-compensated transmission line. The method is based on sensing only the three phase current at the relay site. A reverse synchronous reference frame (RSRF) approach is proposed for fast fault detection and classification. Then, an analytical algorithm based on symmetrical components theory is presented for accurate estimation of fault location. Three possible arrangements of the series capacitor bank (SCB) on the line are analyzed. The SCB and the associated protective metal oxide surge arrestor (MOV) are modeled thoroughly to characterize its behavior during fault. In addition to its simplicity and practicality, the proposed scheme is equipped with decaying DC offset removal technique that allows fast extraction of the current phasors within one fundamental cycle. The proposed method works well for all ground and non-ground faults; it does not need pre-fault information; does not require any communication facilities; avoids high voltage measurement; and works smoothly for a wide range of fault resistance values. The efficacy of the proposed method is proved by a large number of simulated cases under a variety of operating conditions. [ABSTRACT FROM AUTHOR]

• New HIF method for distribution networks with the presence of non-linear loads. • Online monitoring of 3rd harmonic phase angle sample-by-sample for fault detection. • Requires only a single measurement point on the substation. • Detection method not affected by system characteristics or fault location. • Overall detection rate of 99.32%, with no false positives. This paper presents a new high impedance fault (HIF) detection method considering the presence of non-linear loads in the distribution network. It adopts a cumulative error-based index to monitor the third harmonic phase angle, which is extracted with Stockwell transform and compared to a self-adaptive threshold for fault detection and classification. The proposed method requires only a single measurement device on the substation. Results show that the proposed method is able to quickly detect HIF in all simulated cases, considering several fault locations and different contact surfaces, not being affected by conditions such as fault inception angle, system loading percentage, or fault location. Additionally, results suggest that it can distinguish HIF from capacitor banks switching, low impedance faults, transformer energizing, and feeder energizing along with linear and non-linear loads switching. HIF real oscillographic records are also used for validation. The proposed method achieved a fast detection, in less than 11 cycles for most cases, and a high detection rate, over 99%, with no false positives. [ABSTRACT FROM AUTHOR]

• The multi-period active-reactive coordination scheduling strategy considering the operation characteristics and reactive power adjustment ability of adjustable resources is proposed to formulate a reasonable and efficient scheduling plan. Meanwhile, the effectiveness and practicality of the proposed strategy are verified through four typical operating scenarios and three proposed evaluation indicators. • An efficient solution method for active-reactive coordinated scheduling model is proposed based on the accurate linearization modeling of ESS, CB and OLTC. Then, the MISOCP are further converted into 0–1 MISOCP to solve accurately and efficiently. Finally, the excellent performances of the proposed linear modelling method have been validated by four operating schemes. • The sensitivity for adjustment step and action time of discrete controllable devices are analyzed in depth. Meanwhile, the adjustment step and action time of discrete controllable devices influence on the optimization results is discussed in detail. Nowadays, the active distribution network (ADN) is facing great challenges on safe operation and coordinated scheduling. To resolve these issues, a novel multi-period active-reactive coordination scheduling strategy efficient solution method is proposed in this paper after addressing the uncertainty of DG and load by probabilistic scenario method. Firstly, based on the second-order cone relaxation (SOCR), the power flow equations are convexized and relaxed to transform the original model into mixed integer second-order cone programming (MISOCP). Then, the controllable resources such as on-load tap changer (OLTC), capacitor banks (CB) and ESS are accurately linearized, so the model is converted to 0–1 MISOCP problem. Finally, compared with the existing strategies, numerical tests on the modified IEEE 33-bus test system demonstrate that on the premise of realizing the maximum utilization of DG, the proposed strategy can also achieve the purposes of energy-saving, loss reduction and improvement in voltage level and the utilization of ESS. Meanwhile, the accuracy and efficiency of the 0–1 MISOCP model are verified through four operating schemes. In addition, the sensitivity analysis of adjustment step and action time of the discrete adjustment devices on optimization results is carried out in detail. [ABSTRACT FROM AUTHOR]

• Determining the proper size of the SCB to minimum risk of the self-excitation. • Detecting and preventing the SCB self-excitation. • Limiting the SCB switching transients. • The proposed strategies for limiting SCB transients are verified using comprehensive simulation studies. Medium voltage shunt capacitor banks (SCBs) are widely used for improving voltage profile and providing reactive power in electrical networks. Transient oscillations caused by SCBs, e.g., switching and self-excitation phenomena, may damage sensitive equipment in electrical networks. This paper provides an analytical description of the SCB transients and proposes efficient techniques to limit such transients, which include (i) determining the proper size of the SCB to minimum the risk of the self-excitation, (ii) detecting and preventing the SCB self-excitation using a novel protection scheme, and (iii) limiting the SCB switching transients by developing some approaches for medium voltage application. The proposed strategies for limiting SCB transients are verified using comprehensive simulation studies conducted on an actual power system. [ABSTRACT FROM AUTHOR]

• Uncertainties of PHEV's load demand is incorporated into renewable DG planning. • An unaccustomed type of point estimate method is used to handle uncertainties. • Pareto optimal front is obtained considering different penetration levels of PHEVs. • Chance-constrained programming is used to handle smooth constraints. • Robustness evaluations made by MC simulation prove the efficiency of the method. • Ignoring the uncertainties can severely increase constraint violation probability. The increasing penetration of solar distributed generations (SDGs) and wind distributed generations (WDGs) together with plug-in electric vehicles (PEVs) will lead to a promising amount of reduction in greenhouse gas emissions. Nevertheless, they bring about adversities such as uncertainty in production-load sides, augmented power loss, and voltage instability in the power system, which should be carefully addressed to increase the reliability. In this concern, this paper proposes a multi-objective optimization methodology for sizing and siting of SDGs, WDGs, and capacitor banks (CBs) in the power system considering uncertainties stemmed from PEVs load demand, solar irradiance, wind speed, and the conventional load. The understudy objectives are the voltage stability index, green-house gas emissions, and the total cost. An unconventional point estimate method (PEM) is used to handle the related uncertainties, and chance-constrained programming method is deployed to deal with smooth constraints. The corresponding probability distribution functions of output variables are estimated by the maximum entropy method. Furthermore, robustness analysis is made by Monte Carlo simulation (MCS). The proposed methodology is applied to a typical radial distribution network. The results show that the presence of PEV's significantly increases the load demand, which results in voltage collapse in the distribution system without the presence of distributed generations. However, the proposed probabilistic method ensures the safe operation of the distribution system with the optimal allocation of renewable distributed generations and CBs. Moreover, the results of deterministic and probabilistic cases are compared under different penetration levels of PEVs. The best tradeoff solution of the Pareto front is selected by the fuzzy satisfying method. [ABSTRACT FROM AUTHOR]

• An approved method based on the RLS algorithm is presented. • Comparison between the standard RLS algorithm and the proposed method. • The proposed method performances are confirmed by experiment tests. This paper describes another way to perform the on-line induction machine's parameter identification using the standard linear form of the recursive least-squares algorithm (RLS), which is commonly applied to estimate the machine parameters in motoring mode using an appropriate linear form machine model. The proposed approach shows that with this same methodology, better results could be obtained when the considered machine is running in self-excited generating mode. The on-line parameter estimation task is performed just during the beginning of the voltage build-up process where the magnetizing machine curve is linear and both saturated and non-saturated machine models present the same dynamic behavior. Since the rotor is driven at a constant speed and the required reactive power is provided by a capacitors bank connected to the stator windings terminals, this fact allows a direct application of the standard RLS estimation algorithm to the frequently linear machine model without any voltage measurements and without any additional restrictions generally imposed by the motoring mode. These potential advantages will contribute to significantly reduce the estimation algorithm complexity. Simulation results validated by experimental tests confirm the effectiveness of the proposed approach with improved accuracy. [ABSTRACT FROM AUTHOR]

• Voltage variation caused by the PV can be mitigated without additional investment. • Proposed strategy is fully distributed, which is flexible, scalable and robust. • Voltage regulation and the reactive power dispatch can be achieved simultaneously. Distributed rooftop PV generator systems have been increasing significantly in distribution networks. However, due to the intermittent nature of the PV power generation, it is challenging to handle the fast voltage variation of the distribution system through dispatching traditional low response speed devices such as load tap changers and capacitor banks. In this paper, a distributed hierarchical control strategy is proposed to deal with the voltage fluctuation issues through real-time regulating the injection or consumption reactive power of the fast response PV inverters. The proposed control strategy includes a primary droop control level and an agent-based distributed secondary control level. The droop-based primary level control can quickly regulate the voltage of PV inverter with locally measured information to overcome the fast voltage variation. The agent-based secondary level control can guarantee the average bus voltage restoration and proportionally reactive power sharing among the PV inverters through distributed communication between neighboring agents. With the proposed control strategy, both the average bus voltage restoration and proportionally reactive power sharing can be satisfied, which improves the stability of the distribution system. Furthermore, the proposed strategy is a fully distributed method that can distribute the computational and communication tasks among the local controllers through working in parallel, which is more flexible, scalable, and insusceptible to single-point failure. [ABSTRACT FROM AUTHOR]

• A novel expansion planning model for active distribution system with multiple active network managements is proposed. • Optimal load shedding is originally proposed and shows an obvious better stability performance in case study. • A SOCP approach and some linearization means are applied to solve the MINLP model. • A two-stage optimization algorithm is developed and proved to have great ability to solve this problem. • Simulation results based on a modified 37-bus system indicate the technical and economic superiority of the proposed model. In this paper, a new expansion planning model for an active distribution system considering multiple active network management schemes is proposed, where demand management considering the optimal load-shedding direction is innovatively introduced into the planning model. This model optimizes the investment decisions of all the infrastructures as well as the corresponding operational strategies in a coordinated manner. Therefore, the final solution is identified by the optimal type, location and size of the feeders, distributed generators, capacitor banks, static var compensators, voltage regulators, energy storage systems, and transformer substations. To incorporate the optimal load reduction into active network management, the optimal load-shedding direction is first introduced, and an iterative method is developed to compute it. On this basis, the coordination planning model of an active distribution system is established, and the operational strategy of all the active management devices is integrated into the expansion planning problem of an active distribution system. By applying the second-order cone relaxation method, the original mixed-integer nonlinear model is converted into a mixed-integer second-order cone programming model that be efficiently solved. Finally, a two-stage optimization algorithm is proposed to obtain the final solutions. Simulation results based on a 37-bus system and a 122-bus system corroborate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]