Topology and parameter identification of distribution network using smart meter and µPMU measurements

Incomplete and inaccurate information of network topology and line parameters affects state monitoring, analysis, and control of active distribution networks. To solve this issue, this article proposes a method for identifying distribution network topology and line parameters using the measurements obtained from smart meters (SMs) and microphasor measurement units ( μ PMUs) installed at various locations in a distribution network. A data-driven approach was developed, which uses a probabilistic method (unscented Kalman filter (UKF) based) and a deterministic method (Newton Raphson (NR) based) iteratively for accurate identification of network topology and parameters. The impact of the measurement noise with SMs and μ PMUs is analyzed, and the acceptable noise levels are quantified. The impact of the identification algorithm on the network state estimation is examined. Moreover, optimal installation locations of the μ PMU equipment are identified based on the estimation accuracy of the algorithm. The method is validated on benchmarked IEEE 33-bus and IEEE 123-bus test systems, while the impact of the renewable power injections at the different network nodes is studied as well. The qualitative and quantitative analysis is performed over the state-of-the-art methods, to highlight the effectiveness of the proposed methodology

ICT infrastructure supporting smart local energy systems: a review

Smart local energy systems (SLES) have been reported in the past decade, which are associated with diverse energy carriers, components and objectives. This paper provides a comprehensive review of information and communications technology (ICT) infrastructure of SLES. A systematic survey of existing research work and industrial projects was provided to highlight, categorise and analyse the ICT infrastructure, which lays the foundation for the successful functioning of SLES. First of all, various SLES measurements are described and categorised based on the energy carriers and technologies. Then, communications infrastructure for SLES is described with communications technologies summarised. Moreover, the ICT infrastructures for SLES are categorised and summarised based on their objectives and technologies. Finally, the challenges and recommendations are presented. The findings from this paper are intended to serve as a convenient reference for developing future SLES

Fuzzy logic gain‐tuned adaptive second‐order GI‐based multi‐objective control for reliable operation of grid‐interfaced photovoltaic system

This study presents the fuzzy logic integrator gain‐tuned improved second‐order generalized integrator (GI) for a double‐stage grid‐interfaced photovoltaic (PV) system. The proposed system includes the functionalities of feeding active power to the grid, power factor correction, grid currents balancing and system isolation under grid side faults. Moreover, the smooth system operation is ensured under weak distribution grids where grid voltage is subject to huge diversions. Furthermore, automatic protection scheme for the system under grid‐side faults is also established with the proposed algorithm for increased reliability. The fuzzy‐tuned GI provides advantages of efficient and effective extraction of load current fundamental component under steady‐state and dynamic grid conditions. The non‐linear frequency error variation is compensated here using fuzzy logic‐based self‐tuning integrator gain of the controller. The controller is improved to mitigate the possible DC component in the load current. The neutral current in the loads is nullified by using a four wire system. The adaptive DC bus voltage helps to minimize the switching losses and prevents unexpected tripping of the PV inverter. The system is experimentally verified using a prototype built in the laboratory

Harmonic voltage control in distributed generation systems using optimal switching vector strategy

With increased penetration of renewable power and the nonlinear loads in the distributed generation (DG) systems, increased power quality concerns are exhibited in the active distribution networks, especially the challenges associated with the current and voltage harmonics in the system. Various conventional harmonic compensation techniques are developed for voltage-controlled DG inverters in past, majority involve either multiple proportional-integral (PI) or proportional-resonant (PR) controllers in eliminating grid current harmonics. The current-controlled inverters, on the other hand, are not preferred in industrial applications, accounting to their wide variations in the switching frequency. A novel and adaptive harmonic voltage control is developed here, for voltage-controlled DG inverters, which neither uses any PI regulators nor imposes stability issues associated with nonideal implementation of infinite gains of PR controllers. Interestingly, the developed control logic can be used for DG inverters, both in grid-connected and off-grid operational modes. Furthermore, this strategy allows a network operator to use this as an additional supplement that can be enabled/disabled as per the network requirement. The control logic exploits the property of an optimal-switching-vector controller, i.e., accurate output voltage tracking. Simulations results demonstrate the effectiveness of the controller, to suppress grid current harmonics and load voltage harmonics in grid-interfaced (GI) and off-grid modes, respectively, ultimately satisfying the mandatory IEEE standard-1547. Experimental results verify the viability of the controller for practical applications

Hybrid state-estimation in combined heat and electric network using SCADA and AMI measurements

State-estimation plays a vital role to monitor, observe and understand the combined heat and electric network. In this paper, a hybrid framework is presented to accurately estimate the system states of electric distribution network and heat network, using the limited non-redundant measurements obtained from supervisory control and data acquisition and advanced metering infrastructure systems. The presented hybrid framework involves two steps, namely, the state-forecasting and the state-estimation. The state-forecasting uses a deep neural network to forecast the system states at every fifteen minutes interval, while these forecasted states are further used by the hybrid estimator, which uses a robust extended Kalman filter to estimate the system states with help of both datasets corresponding to supervisory control and data acquisition and advanced metering infrastructure systems, at hourly interval. The proposed framework does not completely rely on the system model at different instants. The effectiveness of the method is validated through thorough comparisons with simulation studies carried out using the Barry Island test system, United Kingdom. Satisfactory performance is observed even with the presence of bad data in the measurements

Modelling of the Electric Vehicle Charging Infrastructure as Cyber Physical Power Systems: A Review on Components, Standards, Vulnerabilities and Attacks

The increasing number of electric vehicles (EVs) has led to the growing need to establish EV charging infrastructures (EVCIs) with fast charging capabilities to reduce congestion at the EV charging stations (EVCS) and also provide alternative solutions for EV owners without residential charging facilities. The EV charging stations are broadly classified based on i) where the charging equipment is located - on-board and off-board charging stations, and ii) the type of current and power levels - AC and DC charging stations. The DC charging stations are further classified into fast and extreme fast charging stations. This article focuses mainly on several components that model the EVCI as a cyberphysical system (CPS)

Enhanced power quality PV-inverter with leakage current suppression for three-phase SECS

This paper presents an enhanced power quality solar-photovoltaic inverter enabling common-mode leakage current elimination. A three-phase transformer-less solar energy conversion system (SECS) is considered here, which, along with peak active-power production from PV-array, ensures different power quality improvement capabilities such as grid current harmonics mitigation, grid-currents balancing, while also offering the grid reactive power support. Unlike conventional power quality inverters, this strategy is a robust with respect to abnormalities in grid-voltages at far radial ends, and does not compromise with the leakage currents caused by parasitic-capacitance of PV-array with ground. Common practice in the PV inverter power quality control is to neglect the PV leakage-currents, however, they considerably affect the system performance by deteriorating the power quality and causing the safety issues of operating personnel. The standards VDE-00126 and NB/T-32004, therefore, compel the transformer-less PV-systems to operate with leakage current under 300mA range. Various simulation and test results show the satisfactory performance of the presented strategy, even under various grid-side abnormalities. The comparative analysis with state-of-art techniques shows the effectiveness of the strategy. Under all test conditions, the harmonics in grid-currents are observed within limits as per the IEEE-519 and IEC-61727 standards, while the PV leakage-currents are maintained well within the range recommended by VDE-00126 standard

Self-synchronizing VSM with seamless operation during unintentional islanding events

This article proposes a predictive optimal switching vector controlled virtual synchronous machine (VSM) for three-phase microgrid applications, which inherits self-synchronization and islanding detection technique within the controller. A novel synchronization signal is introduced here, to modify the frequency reference in VSMs. This integrates the synchronization and islanding detection within the control loop, thereby resulting in smooth system responses without causing stability issues associated with phase-locked loops. Moreover, it totally eliminates proportional-integral (PI) regulators in the system. The traditional pulsewidth modulation controllers use cascaded internal control loops, and they demand multiple PI regulators and synchronous coordinate transformations. They are associated with finite dynamic response time by PI regulators and necessitate rigorous tuning for practical implementation purposes. The proposed controller, however, estimates the behavior of output voltages and uses a minimization criterion to produce optimal inverter switching sequences. The voltage vectors that cause the overcurrents in the inverter are inherently avoided by the minimization function within the controller. The effectiveness of the proposed control strategy is verified through simulations and experiments validate the performance under different operating conditions

Predictive optimal switching vector controller based microgrid enabling switching frequency constraint

This study proposes predictive optimal switching vector controller to generate optimal switching sequences to voltage-controlled inverters in islanded microgrid systems. The conventional pulse width modulation controllers use output voltage and current with inner and outer current loops, thereby demanding the PI (Proportional Integral) regulators and PWM modulators. They are associated with finite dynamic response transient time by PI controllers and necessitate rigorous tuning for practical implementation purposes. To complement this problem, voltage and current predictive optimal switching vector control is proposed here, which completely eliminates the PID regulators, PWM modulators and synchronous co-ordinate transformations. It uses the model of the system to predict behavior of output voltages for each sampling instant. A minimization function is then used to select the switching state for the next inverter switching instant, while limiting the over-currents caused in the inverter. A switching frequency constraint is proposed to reduce the switching losses of the inverter. The proposed control strategy is verified through simulations and is experimentally validated on a prototype of microgrid system built in the laboratory

Finite control-set model predictive control for leakage current suppression in grid interfaced solar PV system

This paper presents a single vector finite control-set model predictive controller for leakage current suppression in a grid interfaced transformer-less PV (Photovoltaic) system. The stray capacitance between PV array and the ground cause considerably high leakage currents in the transformer-less PV system. A control strategy is presented herein, to suppress these leakage currents in a practical solar PV system, by reducing the common mode voltage. The conventional control strategies for leakage current suppression employ multiple additional IGBT (Insulated-Gate Bipolar-Transistor) switches to reduce the leakage currents and their corresponding gating strategy. However, this algorithm eliminates the need for additional switches for reducing the leakage currents. It means the very same standard 3-leg PV-inverter topology can be used while ensuring reduced leakage currents and this strategy is possible to be appended in any voltage-controlled inverter. The controller uses a predictive optimal switching vector strategy for this purpose, which uses the system model to predict the output voltages and then a quadratic function decides the best switching vector at next sampling instant. An additional penalty is imposed on the quadratic function, to reduce the ripple content in common mode voltage of the system, thereby limits the excessive solar PV leakage currents. Simulation and test results validate the strategy