G Gu Ye

Voltage dip state estimation in distribution networks by applying Bayesian inference

The performance of the system regarding voltage dips is commonly characterized with the SARFIx index, which gives the average frequency of voltage dips. Due to the limited number of measurement points, the actual residual voltages of many nodes are not taken into account when the index is calculated. As its impossible to measure the dip level at every node of a feeder, the voltage dips occurring at nonmonitored nodes should be estimated from the values recorded at monitored nodes with the consideration of measurement accuracy. This paper proposes a voltage dip state estimation method based on Bayesian inference. The performance of the proposed method is assessed through case study applied in a typical distribution network. Monte Carlo simulation is used to obtain the statistic results. The proposed method shows the flexibility of different measurement quantities and the adequacy for the analysis of distribution networks.

Assessment of the voltage level and losses with photovoltaic and electric vehicle in low voltage network

Livelab from Alliander, a network operator, is a program which started to measure electrical and power quality data in the Dutch distribution network since 2013. A proper probability distribution can be used to model load distribution on feeders. This paper presents a methodology to generate the residential load profiles by cumulative distribution function based on Livelab measured data. Applying Monte Carlo simulation, a probabilistic three phase Load Flow program is developed to investigate the voltage level and network losses (where harmonic loss is considered) of a typical low voltage network with the consideration of variable loads and random locations. The prospective impact to voltage level and losses due to the grid- connected photovoltaic power generation systems and electrical vehicles are discussed. Monte Carlo simulations are carried out with the different penetration rates of photovoltaic generation and electrical vehicles, maximum capacity of grid-connected equipment can be estimated and the possible network losses are calculated.

Performance comparison of different filter applications in three-phase PFC rectifier

In this paper, a 3-phase AC/DC converter (six switches) with power factor correction (PFC) is presented. In order to reduce the harmonics due to the high switching frequency of the converter (20kHz); a L-filter, a LCL passive filter and three LCL active filters are designed for comparison with eachother. The paper concentrates on the methods to find the parameters of these filters and discusses their control mechanism. Comparison of these different filters is carried out by simulation results and discusses their pros and cons over one another.

Appliance-based residential harmonic load modelling

An adequate modelling of the harmonic load is required to analyse the harmonic impact and perform propagation studies. Since more and more nonlinear loads are connected with the network, such as energy saving lamps, electric vehicles, photovoltaics systems etc., the accurate modelling of the harmonic injection of new appliances becomes more important. In this paper, a bottom-up stochastic model is proposed for the modelling of harmonic loads in residential networks. First a Markov Chain Monte Carlo approach is employed for household occupancy modelling with time use survey database. The occupancy, weather conditions, neighbourhood features and behavioural survey data are subsequently applied to obtain loading patterns of the household appliances. The harmonic spectra of various appliances are established based on measurements. Based on these, a harmonic load flow can be run to calculate the harmonic load of each household. Measurements of harmonic magnitude carried out in a residential low voltage network in the Netherlands are used to validate the proposed approach.

Integrating direct and indirect load control for congestion management in LV networks

With the energy transition, capacity challenges are expected to occur more frequently in low-voltage (LV) distribution networks. In the literature, several direct and indirect load control methods have been suggested as solutions to alleviate network congestion. Direct methods involve the network operator directly controlling appliances at the households, while indirect methods aim to motivate end-users to shift their consumption through price changes. In this research, the direct and indirect methods are combined into an integrated approach, making use of the advantages of both methods. An agent-based architecture is adopted so that distributed and computational intelligence can be combined to ensure a smooth coordination among the actors. A sensitivity- based curtailment scheme is used to incorporate the unbalanced loading condition of the LV networks. The efficiency of the proposed integrated approach is investigated through simulations in the unbalanced IEEE European LV test feeder. Simulation results reveal up to 94\% reduction in congestion by the integrated approach, while maintaining the required levels of supply in the network.

Bayesian-Inference-Based Voltage Dip State Estimation

Voltage dip state estimation (VDSE) tries to estimate the voltage dip characteristics at nonmonitored buses from measured voltage dip values at monitored buses. In this paper, the VDSE is addressed through the method based on Bayesian inference. A priori including the fault position among other grid conditions is used to estimate the residual voltage at each bus based on the measurement quantities, including their uncertainties. The dip duration is calculated with the time setting of protection system incorporating the uncertainties due to dip detection algorithm of the root mean square values. The proposed method has been applied to the IEEE 13-bus and IEEE 123-bus distribution test systems for multiple simulation scenarios, such as with or without distributed generation and different types of faults. The simulation results show good observability of the network.

A study on harmonic current summation using field measurement data

Due to the diversity of harmonic phase angles, the total harmonic current from a combination of loads is lower than the arithmetical sum of their magnitudes, which is also known with the summation effect. Conventionally, the summation effect is analysed through the summation law and expressed as the summation coefficient. In this paper, the summation coefficients are calculated with the field measurement data in several sites and compared with the recommended values of standard. To investigate the performance of summation coefficient, two indices are defined and calculated. More analyses have been done on the phase angles of harmonic currents. Some guidelines about harmonic summation estimation are given.

Influence of high frequency current harmonics on (Smart) energy meters

(Smart) meters which use Rogowski coils are verified to be sensitive for the high frequency signals. This will lead to incorrect records of consumers energy consumption. Power electronic devices are the possible harmonic sources. In this paper, the output currents of photovoltaic (PV) systems are measured in the range 2-150kHz and the high frequency harmonic currents are regenerated in the laboratory to investigate their influence on the smart energy meters. It is realized that the insufficient dynamic range in the meters could be the possible reason of inaccuracy. After the experiments, it is concluded that the high frequency current can make the output signal of the Rogowski coil beyond the dynamic range of smart meters and sequentially less registered energy.

Influence of RMS calculation methods on the measurement of voltage dips

This paper presents the results of the analysis on the influence of different RMS calculation methods to the detection and characterization of voltage dips. The analytical calculation of measurement parameters for voltage dips and the systematic deviations in characterization due to the dip detection algorithms are discussed for the general RMS calculation methods, sliding window and half cycle methods. Stochastic processes are carried out with different fault types, fault locations and event occurring instants in a real medium voltage network, an evaluation study is presented with the statistic results.