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In this paper, an attempt has been made to examine the effectiveness of Neuro-Fuzzy Scheme (NFS), to identify the deterioration of the winding insulation paper (WIP) in a oil-immerged power transformer, and to compare its performance over conventional methods (IEEE/IEC). The comparison of convergence characteristics of IEEE and IEC approach reveal that the NFS approach is quite faster in investigations leading to reduction in computational burden and give rise to minimal computer resource utilization. Simultaneous identification of deterioration of the WIP and operating conditions in oil-immersed power transformer has never been attempted in the past using NFS. The technique proposed in this paper provides not only best dynamic response for the deterioration of the WIP diagnosis and condition assessment of power transformer but also present its appropriate maintenance scenario as well. This approach will address a proactive assertion to the power utilities for effective realization of electrical health of oil-immersed power transformer under consideration. In this paper, testing analysis of 25 transformer samples has been carried out to demonstrates the robustness of the investigated four status conditions (Normal Operation – NO; Modest Concern – MCI; Major Concern – MCMI and Imminent Risk Failure – IRF) for wide changes in operating condition and loading condition perturbation.

Occluded gaseous cavities within the insulating materials are potential sources of electrical trees which can lead to continuous deterioration and breakdown of materials. To determine the suitability of use and to acquire the data for the dimensioning of electrical insulation systems breakdown voltage of insulators should be determined. In this paper, fuzzy logic (FL) method is used to model breakdown voltages of White Minilex Paper samples based on experimental data generated in the laboratory. Different models are proposed with different shapes of the membership functions for the FL under both dc and ac voltage conditions. The cavities are created artificially with different dimensions. Low values of mean absolute errors of the estimated breakdown voltage of the test data show the effectiveness of such models.

The conventional power system stabilizer tuning method is still playing an important part in practical applications. In this short paper, an alternative power system stabilizer gain tuning method is presented to overcome the drawbacks of the existing conventional gain tuning method based on the stability margin test.

In this paper, an approach for placement of voltage regulators (VRs) in traditional distribution systems by considering a local controller model is presented. The main aims of this paper are controlling the voltage level in its permitted range and decreasing the costs imposed to the distribution system companies, such as costs that stem from power losses, VRs’ investment and maintenance. Genetic algorithm (GA) has been used as a tool to determine the number, location and rated power of VRs. Since in traditional distribution systems, tap position determination of VRs is achieved by local controllers, local controller model is established to determine tap operations. A 70-bus distribution system is considered to prove the value of the presented approach. Effectiveness of the proposed approach and ineffectiveness and infeasibility of conventional approaches are presented in numerical studies. The presented approach allowed to eliminate voltage violation in all load conditions and a reduction of power losses of about 6% for the maximum load level.

This paper proposes a method to compensate the network voltage unbalance using the doubly fed induction generator (DFIG) wind turbine connected to a dynamic voltage restorer (DVR). In the configuration employed, a DVR based on a voltage-source converter is connected in series between the generator and the grid. The proposed control uses symmetrical components to calculate the negative sequence current to be injected in the network to compensate the voltage unbalance at the Point of Common Coupling (PCC), and the voltage to be applied at the stator, to avoid torque oscillations. The contribution of this paper consists on proposing a coordinated strategy for compensating the voltage unbalance at PCC and avoiding torque oscillations in the machine. Due to the coordinated use of all resources available for compensation, the proposed method increases the operational range of the existing methods. Basically, the strategy of the proposed method consists on using the remain capacity of the grid side converter of the DFIG for injecting compensating current and, when it reaches its limit, the rotor side converter is controlled to inject compensating current through the machine stator to the grid. The torque oscillations due to the unbalanced operation of the machine is avoided by applying a series voltage by the DVR. Simulation results have validated the proposed method, which maximizes the compensation at the PCC voltage unbalance and guarantees the machine operation with low oscillation in the electromagnetic torque.

Interruptible load management (ILM), as an important incentive-based demand response (DR) program, plays a critical role in power system operation. An improved ILM scheme design method is proposed in the paper. From the perspective of social welfare, the scheme design is described as an optimization problem, and then mechanism design theory is adopted for solving. The novel idea presented in the paper is that the customer baseline load (CBL) is used to parameterize the type of customer (TOC), which is fundamental information for application of mechanism design theory. Being private information, TOC is not directly attainable, but CBL can be estimated based on historical load data (namely the customer performance), and it can reflect the customers’ rational judgments in self-benefit decisions. Firstly, the validity of adopting CBL to determine TOC is demonstrated. Then, the load curtailing potential constraints and the objective function are rebuilt in the expression of CBL correspondingly, so that the mechanism design theory successfully works with CBL instead of TOC. Moreover, adjustment strategies are also proposed to cope with the possible unenforceable scheme scenarios, thus the practicability of the designed scheme is ensured. Finally, simulations are carried out to validate the effectiveness of the proposed method.

This paper discusses an optimal joint placement of phasor measurement units (PMUs) and flow measurement devices for ensuring observability of power systems under N-2 transmission contingencies while excluding single-bus islanding situations. Previous studies mainly focus on system observability under N-1 contingencies, and consider the PMU placement only or the joint placement while restricting PMUs and flow measurements to be adjacent. In comparison, this paper first proposes a single-stage optimal joint placement model which minimizes the total investment cost of PMUs and flow measurements for achieving system observability under N-2 transmission contingencies while excluding single-bus islanding situations. Different topologies corresponding to double-line outage situations and the effect of zero power injection nodes are accurately considered, and system disintegration is adequately addressed for guaranteeing system observability under N-2 transmission contingencies. Moreover, the proposed model allows a flow measurement on a branch to observe one terminal node even if the other terminal is not adjacent to a PMU. The proposed single-stage optimal joint placement model is formulated as a mixed-integer nonlinear programming (MINLP) problem, and is equivalently transformed into a mixed-integer linear programming (MILP) problem and solved via a decomposition algorithm. Furthermore, as system operators may prefer a multi-stage placement plan so as to well spread limited financial budgets among multiple years, the proposed single-stage joint placement model is further extended to a three-stage strategy for incrementally ensuring system observability with respect to the original topology, N-1 contingencies, and N-2 contingencies. Both models are verified via several IEEE power systems. Numerical results show that, as compared to previous studies, the proposed optimal joint placement approaches are advantageous in reducing total investment cost while ensuring system observability, and the three-stage placement model presents an effective strategy to handle limited financial budgets among multiple years. In addition, impacts of other factors on the proposed model, including single PMU failure, substation based optimization, branch PMU based optimization, single-bus islanding inclusion, and zero power injection effect verification, are analyzed and discussed via extensive case studies.

This paper presents a novel dynamic clustering equivalent modeling method for a two-staged photovoltaic (PV) station cluster, which is a key tool to analyze the dynamic responses of the distribution network with high PV penetration. In this paper, a dynamic affinity propagation (DAP) clustering algorithm is proposed after studying the indexes that can describe the dynamic characteristics of two-staged PV power station. Then this algorithm is used to group the PV stations in the PV cluster according to their dynamic characteristics. Finally, the dynamic equivalent model of PV cluster is obtained by parameters aggregation of PV stations in the same group and simplification equivalent of the network. The proposed method is verified by a PV cluster distribution network with 20 two-staged PV stations and the simulation results show that the proposed dynamic equivalent model can accurately reflect the dynamic response characteristics of the PV cluster. At the same time, the simplified PV cluster model would reduce the computational complexity and the simulation time significantly.

The use of dc microgrids in the residential and commercial complexes are increasing due to the high reliability, high efficacy, and easy integration with renewable energy sources. This paper presents the voltage stability of dc microgrid based on decentralized control architecture. Droop controllers cascaded with proportional integral (PI) controllers are being used for stability of dc microgrid. Droop control is not effective due to the error in steady state voltages and load power variations. Additionally, PI controllers cannot ensure global stability. It exhibits slower transient response and control parameters cannot be optimized with load power variations. To address the aforementioned limitation, sliding mode hysteresis control is proposed in this paper. Main advantages are high robustness, fast dynamic response and good stability for large load variations. To analyze the stability and dynamic performance of the proposed scheme, a system model is derived and its controllability, observability and stability are verified. Modeled dynamics are graphically plotted and presented. Detailed simulations are carried out to show the effectiveness of SM controller and results are compared with droop controller. The transient behavior on step load is also investigated and presented which shows the good performance of the proposed controller. A scaled down experimental setup of a source is also presented in the Appendix A .

This paper examines dynamic performance of DFIG based wind turbine regarding torsional electromechanical oscillations when the wind turbine is controlled in power control mode. In the power control mode, the stator active power is set to its reference value, where the reference active power is determined based on a predefined power-speed curve. Torsional oscillations associated with the poorly torsional modes may reduce the aerodynamic efficiency, deteriorate the power quality and increase stresses on the drive train system. The paper indeed analytically investigates the drive train dynamics for different operating regions of the power-speed curve. It is shown that under some operating points, torsional oscillations are well damped and the DFIG control improves the damping of torsional modes. On the other hand, at some regions of the power-speed curve, the DFIG control does not provide significant damping action on the torsoinal modes. Then a wind turbine stabilizer (WTS) is implemented to suppress torsional vibrations in the drive train system. The role of the WTS is to add positive damping to the generator rotor oscillations by controlling the active power and providing a component of electrical torque proportional to the rotor speed deviations.

In this paper, customer’s invoiced energy time series in the recent past is analyzed in order to detect the cause of increased total electricity losses in the low voltage network. Period from 2003 to 2017 is included in the recent past. This period is organized in five successive decades whose beginnings are shifted for one year. Fuzzy logic is used as a method for determining a set of suspicious electricity customers in the first phase of electricity fraud detecting. At this phase, every customer located in the area of increased total electricity losses is analyzed. For each customer, a time series of invoiced energy are formed. Selected time series data and their relations are used to create fuzzy sets of suspicion. Then, total suspicion value of each customer is determined by using fuzzy logic. Based on the estimated total and technical energy losses in the customer’s area (region that is supplied by one or more MV/LV transformer stations) and the balance of total, invoiced and energy of losses, a boundary value of suspicion percentage is determined. All customers, whose percentage suspicion value is greater than the boundary value, are declared suspect. Thus, suspicious customers with their locations which need inspection are obtained. On-site inspection of suspected customers is not performed and is not the subject of this paper.

This paper characterizes the bidirectional feature of the transformer-based quasi-Z-source inverter (trans-qZSI) obtained by adding a controllable power device to the input of the circuit. Different arising operation modes and states are analysed and an AC small signal model is proposed accordingly. A controller was designed using the proposed model, and an experimental validation platform was implemented. After the computational and experimental model validation, it was analysed how and when bidirectional Z topology benefits from bidirectional feature, apart from obvious inverse power conversion operation. Robustness increase and fault tolerance of the bidirectional trans-qZSI topology were characterized and validated experimentally for different current demand decrease case studies: when an open circuit is produced in one output phase or when the current demand decreases due to normal operation requirements. The paper characterizes and demonstrates, computationally and experimentally, that it is the bidirectional feature that provides the system with the robustness needed to protect against these kind of failures or operation modes. Not having the additional IGBT could cause the system to enter the discontinuous conduction mode (DCM) zone and destabilize the system’s currents and voltages. In that case the voltage is not able to follow the control reference, which could ultimately lead to the destruction of the components.

Voltage amplitude is one of the most important parameters of electrical energy, particularly from the viewpoint of sensitive loads connected to the grid. The dynamic state in a power grid (voltage sags/swells/interrupts) originating from dynamic loads, uncontrolled power flow, switching effects, adverse weather condition, etc., might cause defects in sensitive loads and financial losses. The annual damages in Europe due to voltage perturbations is estimated at 10 billion €. This paper presents a three-phase voltage conditioner and power flow controller without DC energy storage unit for the control of phase and voltage amplitude. In comparison to conventional solutions, such as DVR or UPFC, the power electronic AC/AC converter is based on a bipolar matrix-reactance chopper. The main aim of this paper is to analyse the basic properties of the presented solution, especially from the point of view of the ability to compensate voltage sag/swell and interruption and to control phase shift in bidirectional power flow control. The studies have been carried out on a three phase system with passive and active load (two-source system). On the basis of the authors’ research, it can be stated that the described solution gives the possibility to compensate deep voltage sag (50% of nominal voltage), overvoltages (up to 150% of nominal voltage) and single phase interruption. Simultaneously the solution allows independent control of the phase angle of output voltage in the range ± π/3. The paper presents an operational description, theoretical analysis, simulation and the experimental test results of a 1 kVA laboratory model using a conventional PWM control strategy.

The paper proposes a novel methodology to analyze and measure the impact of line tripping on grid vulnerability which may lead to cascade failure in smart power transmission system. The key contributions are analysis of current flow path and identification of critical line from normal to perturbed grid with the knowledge of grid topology. To achieve this two performance indices i.e. power flow index and vulnerability index have been defined on the bases of geometry of current flow path. A power flow index is defined to analyze impact of topological changes on current flow path and identify underloaded and overloaded lines. Probability of the critical line and the location of vulnerability center are identified by the vulnerability index. Analytically defined performance indices are applied analyzed and validate using the benchmark IEEE 30 bus power system. The critical line identified by proposed indices is also verified with the probabilistic framework. The proposed methodology allows to focus attention on the power grid vulnerable areas and can help the control system operator to investigate the changes in power flow on transmission lines and initiate the necessary corrective action. The methodology proposed in this paper can be used in security assessment and centralized monitoring of power flow in future smart grid wide area monitoring protection and control system.

This paper proposes a robust control method for power sharing among dispatchable electronically-coupled distributed energy resources (DERs) in an autonomous microgrid. The DER units operate in parallel to meet the total aggregated load demand. The aggregated load is assumed to be uncertain, unbalanced and/or nonlinear, thus it is considered as a source of unmodeled dynamics. The main objective of this paper is to design an H ∞ robust controller to enable tracking reference commands of the voltages at the output of the DERs in the presence of unmodeled dynamics. In addition, the H ∞ control design problem is combined with other control methods, such as constrained optimal control and regional pole placement, to achieve an optimal control objective, and to improve transient response. The optimal controller is achieved by minimizing an upper bound on H 2 performance. The regional pole placement is achieved by defining a linear matrix inequalities (LMI) region. This multiobjective H 2 / H ∞ problem, combined with regional pole placement are expressed as a set of LMIs, and solved by using standard convex optimization algorithms. To show the effectiveness of the proposed method in maintaining the desired voltage at the DER outputs, in presence of unbalanced and nonlinear loads, simulation results are provided for a single DER unit, and the performance of the proposed control strategy is compared with three different controller strategies. Power sharing among multi DER units in autonomous networks is then demonstrated through digital time-domain simulation studies using MATLAB/SimPowerSystems Toolbox.

This paper describes a new algorithm for longitudinal differential protection of transmission lines. Classic stabilization is an unreliable method for avoiding unnecessary relay tripping in case of current transformer saturation during faults outside the protected zone. There are various methods for detecting current transformer saturation. The paper’s thesis is that rather than the stabilization current, the direction of the currents introduced into the relay should be monitored. The proposed algorithm has been compared to the algorithms used by renowned relay producers. Different types of faults have been simulated, both within and outside of the protected zone, and the paper demonstrates how the relay trips when the algorithm in question is used. The results have proven that current transformer saturation does not affect protection operation, and that a prompt relay response is obtained for faults occurring within the protected zone.

A distribution system might be unbalanced due to various reasons which can cause some major problems. Re-phasing strategy is the most effective method for phase balancing performed manually in distribution networks. Dynamic phase balancing is the main objective of this paper that means re-phasing performance at any time of day when unbalance is more than permissible limit. It is possible only in smart distribution networks by installing the automatic re-phasing switches at busbars. Automatic re-phasing eliminates the customer service interruption cost and labour cost available in the manual re-phasing operation. There are two basic operations in the optimal dynamic phase balancing: detecting the best time for re-phasing and considering the load variations in real distribution networks. This paper consists of two scenarios. First scenario is switches installation at all nodes of feeder and second scenario is switches installation at the limited strategic nodes. First scenario focuses on search space reduction by employing a sensitivity analysis method which improves the convergence along with time saving. In order to solve the proposed optimization problem, the modified shuffled frog leaping algorithm (MSFLA) is implemented. Simulation studies greatly demonstrate the benefits achieved from this operation by reducing power loss cost and improving network phase balancing.

This paper presents an approach to design a nonlinear controller for grid-connected fuel cell (FC) systems in order to provide ancillary services to low or medium voltage power networks. In this paper, these ancillary services mainly refer to the delivery of both active and reactive power from the FC to the grid under different operating conditions. The controller is designed based on the dynamical model of a proton exchange membrane fuel cell (PEMFC) which is developed from the electrical equivalent circuit of a grid-connected PEMFC through a voltage source converter (VSC). Partial feedback linearization technique is then employed to obtain the control laws with an aim of regulating respective currents related to both active and reactive power through the switching action of VSCs. The stability of the internal dynamics of the PEMFC system is also analyzed in this paper as the proposed control scheme cannot be implemented for unstable internal dynamics. A rate limiter is used with the proposed partial feedback linearizing controller to ensure the suitability under the worst-case conditions as well as to prevent the over-modulation in the rate of change of power references. The applicability and performance of the proposed controller is justified on a simple system as well as on a 12-bus balanced test distribution system and the CIGRE low voltage test distribution network under different grid events. The simulation results show the superiority of the proposed controller as compared to the vector controller.

This paper presents an optimal coordinated voltage control scheme for preserving long-term voltage stability of power systems. Linear quadratic integral (LQI) controller is employed to construct this scheme. Also, this paper considers the detailed dynamic model of doubly-fed induction generator (DFIG) wind turbine, synchronous generators, over excitation limiter (OEL) and under-load tap changer (ULTC) system, which are important elements influencing voltage stability of power systems. The proposed approach at each time instance involves following two major steps: First, the power system nonlinear equations are linearized and optimal controllers are obtained by LQI technique. Then, in the second step the system dynamic behavior is investigated via time-domain simulations by applying the attained optimal control signals at the first step. The impact of the proposed coordinated voltage control scheme is evaluated by time domain simulations on a well-known test system, under variable wind speed and fault conditions.

This paper presents a multi-objective optimal operation of meshed AC/DC power grids including multi-terminal voltage-source-converter-based high-voltage direct current (VSC-MTDC) systems. The proposed approach is modeled as a corrective security-constrained optimal power flow (CSC-OPF) problem, with the minimization of both the operation cost and power loss as the objectives. Moreover, it provides a cost-effective solution to assist in decision-making, and improves the system security during operation. The N − 1 contingency security criterion is enforced for both AC and DC transmission networks, and corrective control is used to eliminate or alleviate post-contingency security violations. The corrective control actions used in this paper include not only secure operation control actions, but also economical post-contingency corrective control of the multi-terminal VSC-HVDC. To increase the computation speed, a contingency screening technique is applied to CSC-OPF by efficiently selecting the most severe case of the N − 1 contingency, as obtained using a voltage security index (VSI). The proposed approach uses the non-dominated sorting genetic algorithm (NSGA-II) to find multi-objective OPF solutions by checking the post-contingency state feasibility while taking into account post-contingency corrective actions. Simulation results confirm the validity and effectiveness of this approach.

The priority to reactive power contribution from the Voltage Source Converter (VSC) based High Voltage Direct Current (HVDC) connection to support the grid during faults as suggested by the modern Network Code (NC) for HVDC affects the distance protection of transmission lines. Moreover, suppressing the negative sequence current during an unbalanced condition also interferes with the proper operation of the distance relays. This is because the current contribution from the converter is limited in magnitude and modified in the waveform in order to protect the power electronic devices during the fault in comparison to the synchronous generator fault current characteristics. This paper discusses the cause as well as the severity of the problems faced by the distance protection of transmission lines connected to the VSC based HVDC system by analyzing the apparent impedance analytically and in the simulation. The response of the relay to balanced and unbalanced faults lying on transmission lines is investigated. It is shown that the VSC limited reactive support and suppressed negative sequence current affect fault detection, forcing the relay to malfunction. The results of this paper can be used as a reference for understanding the effects of VSC-HVDC system on the operation of the distance protection during faults.

The use of a static var compensator (SVC) as a component of flexible alternating current transmission system (FACTS) devices to control power systems has been investigated for decades. Its aim is to regulate the system voltage and improve the stability and loadability of power systems. A typical assumption in such a system is that the parameters of the controlled system are known accurately, which is rarely satisfied in practice. This paper explores the development of a simple but effective controller for a single-machine infinite-bus power system with SVC subjected to both matched and mismatched disturbances where the controller derivation is based on the assumption that all parameters used in the system modeling are unknown , but bounded in size. The research in this paper illustrates how an indirect robust control can be incorporated with a modified disturbance observer-based feedforward term to attenuate the influence of parameter variations and disturbances from the outputs of the system. Simulation results are presented to confirm the effectiveness of the proposed scheme.

The paper presents an important aspect in the research and development process of control algorithms of FACTS devices. It reveals the details of the time-optimal current control (TOCC) algorithm for STATCOM and deals with its implementation on the digital signal processor (DSP). It has been recognized that discretization of the control process within the DSP deteriorates the operation of the controller and consequently the device itself and calls for new control algorithm improvements, which are addressed within the paper. To evaluate the modified implementation of the control algorithm, the results of the ideal EMT simulations within the PSCAD are compared to the results of the real-time simulations of the controller hardware-in-the-loop carried out with the RTDS simulator and a TI F28335 control card. The comparison shows that the new feature of the control algorithm, namely the delay compensation, improves the performance of the controller while the limited processing power deteriorates its optimal operation.

The presence of flexible ac transmission system (FACTS) controllers in transmission lines causes mal-operation of distance relays. The series-shunt FACTS devices have larger influence on the performance of the relays compare to the other FACTS controllers. Furthermore, high-resistance fault is another factor that relay become under-reach and cannot correctly identify the fault. In this paper, a method is provided based on synchrophasors to eliminate the effects of unified power-flow controller (UPFC) and fault resistance on the distance relay. In the presented method, the data of voltage and current signals of buses will be sent to system protection center (SPC). In SPC, an algorithm is provided based on active power calculation in buses which is able to eliminate the effects of both mentioned factors. The main advantage of the proposed method, in addition to the simplicity of the algorithm, is the ability to operate in all types of faults and in high-resistance faults. Furthermore, a technique is presented in this paper to calculate UPFC data. A comparison has been performed between this technique and another method where UPFC data is directly transmitted to SPC by communication channel. In modeling of UPFC, detail model is used based on 48-pulses voltage source converters. 1 2017 Elsevier Ltd Scopus

The number of fully-rated converter wind turbine generators equipped with a Permanent Magnet Synchronous Generator (PMSG) has sensibly increased in the late years. The optimal utilization and controllability of a PMSG is achieved using a Pulse Width Modulation – Voltage Source Converter (PWM-VSC) that allows interfacing the electric machine with the distribution network by means of a DC link. The generator/Machine-Side Converter (MSC) controls the operation of the PMSG. This paper proposes a methodology to assess the feasibility of the steady-state working points of PMSG based wind turbines without running a set of time-consuming time-domain simulations. Three control objectives for MSC are usually considered: stator voltage control, unitary power factor control and torque control. The aim of the present paper is that of providing an analytical methodology to check the feasibility of the steady-state working points dictated by different control strategies of the MSC starting from the specific operational constraints provided by the wind power plants characteristics. The effectiveness of the proposed methodology is demonstrated comparing numerical results of a MATLAB® implementation against dedicated time-domain simulations. Simulations results demonstrated the appropriate performance of the proposed methodology characterized by the almost negligible computational time required.

The research “Behavior Change and Energy Use” (US Department of Energy and Climate Change, 2011) [1] shows that with better information in the monthly electricity bill, the Energy Performance Certificate (EPC) can encourage people to reduce their energy usage. That is why smart meters - the emerging technology to help people to know their monthly energy consumption, are gradually replacing mechanical power meters. In this paper, we investigate a special energy monitoring process named Non-Intrusive Appliance Load Monitoring (NIALM), which is potentially the best method to give consumers pertinent information with respect to power consumption. However, real-time feedback feature in a low cost NIALM system is still a big challenge in such technology because of the complication in NIALM’s algorithms. System on Chip (SoC) technology can solve this challenge. Besides including high-speed interconnection and multi-processors, integrating Field-Programmable Gate Array (FPGA) into SoCs may be the most important evolution, which provides developers a powerful tool to develop a low cost but high performance system. Therefore, in this paper we proposed a development of a real-time NIALM system based on the SoC with FPGA acceleration.

This paper presents a new approach to the design of robust proportional-integral (PI) load frequency controller (LFC) with overlapping structure in the presence of generation rate constraint (GRC) and time-varying communication delays. The power system is decomposed into overlapping areas with tie-lines being the overlapping (shared) parts between the areas. The overlapping LFC design is based on the expansion-contraction principles, where the power system is first expanded in such a way as to decouple the areas from each other. Then, for obtaining an appropriate level of performance, robust local stabilising PI controllers are designed for each of the decoupled areas using an iterative linear matrix inequality (ILMI) algorithm such that asymptotic stability with a minimal H ∞ performance level is achieved. Finally, the designed robust local H ∞ controllers are contracted (transformed) to a robust overlapping LFC for implementation on the multi-area power system. Although the approach is applicable to multi-area power systems, a time-delay three-area interconnected power system experiencing communication delays is considered in this paper. Simulation results under different scenarios clearly illustrate an improved performance obtained with the overlapping structured LFC of this paper compared with existing decentralized LFCs.

This paper focuses on improving the dynamic response of autonomous microgrids (MGs) by proposing a grid-forming inverter controlled as a virtual synchronous generator (VSG), in combination with a supercapacitor (SC)-based energy storage system (ESS). By this arrangement, the MG-forming VSG is designed to react only in transitory regimes, the steady-state load being distributed to other MG-supporting inverters spread within the MG. In this way, the MG-forming VSG can maintain its full power reserve capacity for dynamic response. The paper details the control solution for the MG-forming inverter, including the VSG and SC-ESS control. The control method for the MG-supporting inverters that allow achieving the proposed control approach is also described. To prove the concept, the paper includes simulation results and experiments accomplished on a complex laboratory MG system based on three parallel inverters, one being controlled as MG-forming VSG, while the others operating as MG-supporting inverters.

This paper presents a decision support system (DSS) for multi-objective dispatch of an electric microgrid considering cost of operation, peak load reduction, and emissions. Discrete compromise programming (DCP) is used as the multi-criteria decision analysis (MCDA) technique for providing the decision support to the distribution system operator (DSO) by ranking various alternatives based on preference of the objectives. The focus of this paper is the application of DCP-based MCDA to select feasible dispatch solutions closest to the preference of the DSO when multiple objectives are considered in the microgrid dispatch. This technique obtains non-dominated solutions in case of conflicting objectives without generating a Pareto front, and hence avoiding prohibitive computational cost. DCP can be used for MCDA in both exact and metaheuristic dispatch algorithms. Uncertainty in renewable energy forecasting and load demand is included through a scenario-based approach by sampling empirical distributions. The dispatch algorithm considers a two hour look-ahead time horizon. Simulations are performed on a notional electric microgrid with diesel generator, solar photovoltaic, and energy storage. The microgrid is based on the IEEE 13-node test feeder and the results are presented.

This paper presents a methodology for the testing of intelligent electronic devices (IEDs) in IEC 61850-based substation automation systems (SAS), without any service interruption to the end users, during the testing process. IEC 61850-based SAS provides opportunities for a new level of substation operation, enhancing operating efficiency, and protection reliability based on Ethernet-based communication networks. Due to these changes to the conventional substations, importance and dependency on IEDs is increasing rapidly. Frequency of faults occurring in the power systems is random in nature and is unpredictable. It is necessary to test and maintain the IEDs to ensure their proper operation at crucial times. This paper presents a novel methodology for testing the IEDs, without compromising the service reliability during the testing process. The proposed methodology exploits the inherit characteristics of IEC 61850 standard i.e. Network - based communication, interchangeability between multivendor IEDs, and engineering based on substation configuration language (SCL) files. The feasibility and robustness of the proposed method has been verified by performing several performance verification tests with different performance metrics.

The harmonic currents injected by high speed electric trains cause not only the pollution of power quality (PQ), but can also excite harmonic resonance in the traction power supply system (TPSS) of high speed railway (HSR). It is essential to build a proper harmonic distribution and prediction model for high speed electric trains. This paper presents an approach to obtain the probability density of harmonic current based on a non-parametric Kernel density estimation method, which can describe the probability distribution characteristics using a data-driven mechanism. A prediction algorithm for harmonic current based on confidence intervals, which can simulate harmonic current injection using a continuous sampling method, is presented in this paper. The new high speed CRH380AL electric multiple units (EMU) are used to illustrate the method. The results show that the proposed approach and algorithm can be useful for harmonic source simulation in harmonic power flow calculation and PQ assessment.

The presence of power electronic-based wind turbines and photovoltaic systems in distribution networks has provided distribution companies an opportunity to implement voltage control through using the reactive power of these systems. In this paper, a decentralized method based on fuzzy logic is proposed to control the reactive power of distributed generations (DGs) regarding the technical constraints. The fuzzy system is optimized by gradient descent algorithm (GDA) and then implemented on various DG technologies including a photovoltaic (PV) system, permanent magnet synchronous generator (PMSG) wind turbine and also a doubly fed induction generator (DFIG) wind turbine. The system under study is tied to a real distribution network. Having simulated the system, the paper shows that the fuzzy system can appropriately determine the desired reactive power that should be produced by each DG based on the voltage variation of the bus at which the DG is connected. Furthermore, a centralized voltage control is also applied to the same network to verify the performance of the method proposed. The verification indicates that the method is capable of finding the near-optimal solution. A scenario in which an unwanted conflict appears in the DGs’ function is defined in detail and then a strategy is presented to resolve the situation. In addition to this, the coordination between the stator of the wind turbines and grid side converter (GSC) is examined. To investigate the robustness of the proposed method in different distribution networks, simulation results are also presented for IEEE 33-bus distribution test system. The numerical results show that the fuzzy system can effectively control the voltage of the DG connection bus.

Integration of wind power generation into power distribution grid may result in stability and power quality challenges. In this way, this paper first reviews the grid integration issues of wind power generation. Then, as the main contribution, the paper develops in-depth theoretical analyses for examination the grid integration issues such as voltage rise, output power fluctuations, and static and dynamic voltage variations created due to grid integration of wind turbines and corresponding aerodynamic power fluctuations. Besides, the paper addresses these issues by proposing elaborate control approaches and by using the static compensator (STATCOM). The paper first addresses the problem of voltage rise by active power curtailment through pitch control. However, this method may result in a large waste of wind energy that may not be cost effective. Next, the STATCOM is implemented and efficient control approaches are proposed for addressing the problem of voltage rise, improvement of voltage profile and suppression of voltage and power fluctuations. At the end, simulation studies for the study distribution grid are given. The study system is an actual distribution grid in Iran with approximately 7.9 MW wind power generation and 21.9 MW load.

The main objective of this paper that distinguishes it from other similar articles is to employ predictive control strategy to improve the stability of power systems (4- machines and 10-machine) in presence of wind farms based on Doubly Fed Induction Generator (DFIG), using Static Synchronous Series Compensator (SSSC) and Super Capacitor Energy Storage System (SCESS). In this paper, SCESS is used to control the active power in the Grid Side Convertor (GSC) and SSSC is employed to reduce low frequency oscillations. The proposed strategy based on the predictive control can be simultaneously used to control the active and reactive power of the Rotor Side Convertor (RSC) as well as damping controller design for SCESS and SSSC. A function is used in the predictive control strategy to reduce computational complexity in selecting the input paths of Laguerre functions. Moreover, the sampling time is reduced by means of employing the exponential data weighting. Simulation results for the function-based predictive control using disturbance scenario in the field of non-linear time are compared with the other two methods, model-based predictive control and classic model (without using the predictive control). The effectiveness of the proposed strategy in improving stability is confirmed through simulation result.

This paper proposes the application of fictitious reference iterative tuning (FRIT) method to optimize the gains of dc voltage controller of grid connected photo-voltaic (PV) system. It may be difficult to achieve good control of dc voltage using conventional PI controller having only one-degree-of-freedom (1-DOF) due to the trade-off between overshoot (in step response) and disturbance response. In this paper, the optimal control of dc voltage is proposed with improved disturbance response by implementing 2-DOF PI controller structure. FRIT method has been programmed in MATLAB based upon the particle swarm optimization (PSO) algorithm. The fundamental idea related to FRIT method is the extraction of input and output data, reference model setting and range of controller gains. The performance of dc voltage control for the optimized 2-DOF PI controller is also compared with the fuzzy logic controller (FLC) response.

Transmission systems, connection of distributed generation to the grid are increased due to increase in power demands. This fact causes the increase in short circuit level of power networks. The occurrence of fault in such networks leads to large short circuit currents throughout the system, which may exceed the rating of existing circuit breakers and can damage system equipment. There are some approaches to reduce this fault current such as power network reinforcement and utilization of fault current limiter (FCLs) in power systems. Power system reinforcement is too difficult if not impractical. Therefore, the utilization of FCLs can provide an effective way to suppress fault currents. The effectiveness of FCL depends on the number of FCLs and their installation location. In this paper, a novel approach is presented to determine the optimal number and location of FCLs to improve the power network reliability and fault current reduction based on different conflicting objective functions. IEEE 39 BUS system and IEEE 57 BUS system are considered to evaluate the effectiveness and feasibility of the proposed method. The objective functions considered for the optimal allocation are reliability of power system, economic impact and short circuit current reduction. Unlike what has been previously done in literature, in this paper Pareto based optimization algorithms, namely non-dominated sorting algorithm, multiobjective particle swarm optimization and multiobjective evolutionary algorithm based on decomposition, are utilized to deal with this problem. The use of these methods made it possible to obtain the Pareto optimal front in which these objective functions are optimized simultaneously.

Under the thermal storage strategies in present studies, the power generation unit (PGU) in combined cooling, heating, and power (CCHP) system is turned on/off only based on the state of storage tank; or the operation state of PGU is determined by thermal demand or/and electric demand, which has no relationship with the state of storage tank. For these traditional strategies, either energy demands or state of storage tank is considered for the operation of system. This paper proposes a novel thermal storage strategy (TSS2) for CCHP systems, which determines the operational state of the PGU based upon electric demand, thermal demand and the state of thermal storage device. In this paper, the operation principle of TSS2 is described and compared with the traditional strategies. A hospital in Shanghai was used to evaluate and compared the performance of the system operating under different storage strategies. The results show that TSS2 improves the performance of CCHP system more significantly compared with the traditional strategies. TSS2 can make both PGU and capacity of thermal storage tank be fully used by CCHP system to produce more electric and thermal energy to meet demands of building. Compared with system without thermal storage, the minimum and maximum increase rates of annual total cost saving for traditional strategies are 0% and 14.84%, respectively. However, for TSS2, they can reach 3.79% and 20.22%. Similar conclusions could be achieved for CO2 emission reduction and primary energy saving. The effect of TSS2 on the CCHP system performance is different under different operation strategies.

This paper is proposed to establish a new control algorithm for UPQC (unified power quality conditioner) to improve power quality and manage effectively equal reactive power sharing between shunt and series inverter of UPQC under unbalanced source voltage condition. The extraction of instantaneous power angle for reactive power sharing faces difficulty with unbalanced source voltage condition. This paper presents a new SRF (synchronous reference frame) based PAC (power angle control) method using decoupled load current parameters for efficient utilization and coordination of UPQC inverters. The proposed controller contributes in improvement of source current and load voltage harmonic profile, provides efficient way of load reactive power compensation and load voltage compensation for sag, swell and unbalanced condition. Effect of source voltage variations in the form of sag, swell or unbalancing on variable power angle estimation and reactive power calculations are also validated through a mathematical analysis. SRF based PAC control approach and PAC based UVT (unit vector template) control approach is adapted for estimating the reference signals of shunt and series inverter respectively and thus reducing the need of extra computation. The simulation and experimental analysis is carried out using Matlab/Simulink software package for computer simulation and a dSPACE based experimental setup for real time verifications.

Electric Vehicles (EVs) have been suggested as alternatives to conventional vehicles for reducing petrol consumption and carbon dioxide (CO 2 ) emissions. When a large number of EVs connect to the grid, they can cause a large amount of power loss. Where to install multiple charge stations in the grid, so as to mitigate losses caused by EVs when providing energy to those EVs, is becoming vitally important. In this paper, a distribution test-network model is described. A new analytical method is proposed, using the stations’ cooperation in terms of optimal active and reactive power dispatch as well as power flow analysis for locating the optimal placement of charge stations, so as to reduce power losses. This method is compared with the previously developed current density method for single charge stations using system simulation results. It was demonstrated that the methods proposed in this paper are more accurate than the current density method, and that 17% of the average active power loss can be saved for three different types of load profile. In addition, 27% of the average active power loss was saved by installing two charge stations rather than no charge stations in the test-line. It is shown that this could represent a 2.6% annual yield above inflation for investing in installing and running such charge stations.

This paper considers a three-phase, low voltage community network with both grid-connected and autonomous modes of operation, which is composed of a group of residential houses and some single-phase, converter-interfaced distributed energy resources (DER) with equal and arbitrarily scattering of the DERs among the phases. The vigorous operation of such a microgrid system is examined with the proposed management techniques. In such a network, it is highly probable for one phase to have a high generation capacity while the other phases experience a higher demand; a technically challenging problem for a network operating in autonomous mode. In this paper, it is proposed for the single-phase DERs of such a system to operate under a droop-based voltage control technique while an appropriate technique is proposed to facilitate the transmission of the excess power from one phase to other phases. The proposals are validated by extensive digital simulations in PSCAD/EMTDC for several scenarios to demonstrate the feasibility of operating such a system and the efficacy of the proposed techniques.

This paper discusses the losses analysis of low power high-frequency Wireless Power Transfer Systems (WPTSs). Ideal models for efficiency evaluation of WPTS can predict performances that are quite far from the real ones. The model proposed in this paper includes semiconductor devices losses, as well as modulation of duty-cycle and phase for the secondary side rectifier. The global influence of semiconductor devices and control parameters on the overall WPTS performances is numerically determined by solving the herein discussed non linear equations system. Experimental measurements realized on a 2 W@6.78 MHz WPTS demonstrate the validity of this analysis.

This paper describes the overall dynamic models of tidal current turbine driving either a doubly fed induction generator (DFIG) or a direct drive permanent magnet synchronous generator (DDPMSG) connected to a single machine infinite bus system including controllers to improve system stability. Testing with ranges of controller gains is carried out to establish zones of stability. The overall results show the advantages of using the DDPMSG over the DFIG. In this paper we used two different models for each machine; the full model and the reduced order model. Also IEEE-9 bus system is used in this work for multi-machine system and tested for a small signal stability analysis.

In this paper, STATCOM performance for voltage–reactive power control is investigated by comparing different tuning methods, used to evaluate gain parameters of STATCOM controller in presence of high probabilistic uncertainty in input wind power and reactive power load demand. To control voltage transient response in least time, reactive power demand is managed by STATCOM. The conventional methods for tuning gain parameters of STATCOM controller do not satisfactorily operate in case of random disturbances and therefore, advanced controllers such as Genetic Algorithm (GA), Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) are required. The main contribution of the paper is: (i) Investigation of STATCOM performance in presence of high probabilistic uncertainty with step changes in input wind power and reactive power load demand, (ii) system studies during dynamic conditions with composite load model in lieu of static load model in the system, (iii) comparison of voltage control and STATCOM reactive power using various tuning methods. Results comparison through all tuning methods show that advanced tuning methods are able to preserve optimal performances over wide range of disturbances using Integral of Square of Errors (ISE) criterion.

This paper proposes a novel strategy to forecast the short-term wind power using model structure selection in combined with data fusion technique. The available inputs are usually treated as an integrated one for the predictive modeling, which ignores the fusion of the different types of inputs. This results the relationship between the multi-inputs and desired outputs are not effectively reflected in forecasting procedure. Moreover, the performances of the various types of data fusion methods are susceptible to the wind power distribution and critical factors such as smoothness, overlapping, the intrinsic amount of information evaluation and the number of neighbor points. These outlined factors can result the lower generality ability of the proposed methods due to the insufficient optimization of the model structure. So this paper presents short-term wind power forecasting method using model structure selection technique in combined with four representative fusions of dimensionality reduction methods to optimize the model structure, promote the computational efficiency and improve the forecasting accuracy. Experimental evaluation based on the real data from the wind farm in Jiangsu province is given to verify the effectiveness of the proposed method by comparing the traditional techniques.

Power systems require a reliable supply and good power quality. The impact of power supply interruptions is well acknowledged and well quantified. However, a system may perform reliably without any interruptions but may have poor power quality. Although poor power quality has cost implications for all actors in the electrical power systems, only some users are aware of its impact. Power system operators are much attuned to the impact of low power quality on their equipment and have the appropriate monitoring systems in place. However, over recent years certain industries have come increasingly vulnerable to negative cost implications of poor power quality arising from changes in their load characteristics and load sensitivities, and therefore increasingly implement power quality monitoring and mitigation solutions. This paper reviews several historical studies which investigate the cost implications of poor power quality on industry. These surveys are largely focused on outages, whilst the impact of poor power quality such as harmonics, short interruptions, voltage dips and swells, and transients is less well studied and understood. This paper examines the difficulties in quantifying the costs of poor power quality, and uses the chi-squared method to determine the consequences for industry of power quality phenomenon using a case study of over 40 manufacturing and data centres in Ireland.

Minimization of the discrimination time between the backup and main overcurrent relays is one of the most important issues in the relays coordination of a power system. Finding the Time Setting Multipliers (TSMs) by the evolutionary algorithm has been investigated in the previous papers. In this paper, in addition to TSM, different characteristics of the overcurrent relays are considered to improve coordination. On the other hand, the coordination problem can be considered as an optimization problem, which can be solved by artificial intelligent methods. Recently, a novel optimization algorithm, Hyper-Sphere Search (HSS) algorithm, has been introduced. The HSS algorithm is adapted to the problem of this paper, in order to select the characteristics of the overcurrent relays and their TSMs. The result of HSS is compared with the genetic algorithm which is used in the previous studies. The simulation results on the sample network show the effectiveness of HSS and relays characteristics in terms of better coordination.

Post-deregulation era of power system operation produces more pressure on Independent System Operator (ISO) to ensure congestion free transmission network without destroying system security. In order to relieve transmission congestion, ISO initiates correct methods by maintaining system reliability and security. This paper considers a novel efficient technique for congestion management like generator real power rescheduling by integrating a pumped storage hydro unit (PSHU) in the system. This paper presents an optimization model for congestion management by incorporating the calculation of two factors like generator sensitivity factor (GSF) and bus sensitivity factor (BSF). Optimal location of PSHU is identified using the value of BSF’s and the numbers of participated generators for congestion management by rescheduling their outputs are determined using the value of GSF’s. The impact of PSHU has been investigated to manage transmission congestion which further reduces the congestion cost and improves security of the system. The proposed method for congestion management considering PSHU is tested on modified IEEE-39 bus New England test system and the validity is obtained by considering the same problem without the presence of PSHU. The result of proposed work with proper utilization of PSHU illustrates the impact of PSHU towards the congestion management and also exploration of firefly algorithm for minimizing the transmission congestion cost.

There are different approaches to provide high power quality for sensitive loads in fault conditions. In this research, “Dynamic Voltage Restorer (DVR)” is used to compensate the harmful effects of disturbances on voltage. In order to improve the performance of DVR’s controller from point of view of power quality indices, voltage sag and THD are considered as first and second object respectively so a new structure is suggested for this controller. The proposed controller is based on human brain learning which is a self-tuning PI controller that is called emotional controller. In that paper a bi-objective structure emotional learning is recommended. Also using this controller, system had better performance during fault conditions in term of both these power quality’s indices. Furthermore, considering voltage THD as second goal influence on major goal considerably which is voltage sag. Power systems sometimes have complicated dynamic behavior especially during faults. Most controllers have difficulty doing their best performance in these situations. Therefore, in order to modify the performance of this controller from point of view of mentioned power quality indices, we make a decision to regulate this controller’s parameters with an optimization algorithm. Self Adaptive Modified Bat Algorithm (SAMBA) is considered as a powerful optimization algorithm in this paper. This optimization algorithm is a modified version of Bat algorithm. The optimization algorithm can overcome to some problems which are common in other optimization algorithms. The algorithm has had a considerable performance rather than standard Bat and PSO algorithm. Also according to simulation results, this proposed method works significantly better than classic PI controller, bi-objective emotional controller and some intelligent controllers that have introduced in other researches already.

This paper addresses the implementation of a real time simulator based on an existing electromagnetic simulating program called ATP-EMTP. The simulator is developed to stream sampled values on an Ethernet network using the protocol IEC61850-9-2. This implementation is done on a general purpose PC. The minimum simulation time step and the maximum sample rate achieved were 69 μs and 240 S/cycle respectively. The main components of the development as well as the evaluation of the performance of the simulator for different cases are described in this paper.

Transient stability constrained optimal power flow (TSCOPF) is becoming an effective tool for many problems in power systems since it simultaneously considers economy and dynamic stability of system operations. It is increasingly important because modern power systems tend to operate closer to the stability boundaries due to the rapid increase of electricity demand and the deregulation in power sector. TSCOPF is, however, a nonlinear optimization problem with both algebraic and differential equations which is difficult to solve even for small power network. In order to solve the TSCOPF problem efficiently, a relatively new optimization technique, named as krill herd algorithm (KHA), is employed in this paper. KHA simulates the herding behavior of krill swarms in response to specific biological and environmental processes to solve multi-dimensional, linear and nonlinear problems with appreciable efficiency. To accelerate the convergence speed and to improve the simulation results, opposition based learning (OBL) is also incorporated in the basic KHA method. The simulation results, obtained by the basic KHA method and the proposed oppositional KHA (OKHA) algorithm, are compared to those obtained by using some other recently developed methods available in the literature. In this paper, case studies conducted on 10 generator New England 39-bus system and 17 generator 162-bus system indicate that the proposed OKHA approach is much more, computationally, efficient than the other reported popular state-of-the-art algorithms including the basic KHA and the proposed method is found to be a promising tool to solve the TSCOPF problem of power systems.