Phase reassignment for load balance in low-voltage distribution networks

This paper presents the results of experiment-based simulation aimed at analyzing the harmonic distortion behavior of nonlinear loads and the background voltage distortion of power supply in building low-voltage (LV) distribution network. The procedure of constructing experiment-based simulation model and harmonic monitoring at various points of common coupling (PCCs) in LV network are introduced for analyzing voltage and current harmonic distortion behavior due to attenuation effect. The model is proposed for future microgrid modeling analysis at different PCCs in LV networks. The simulation model was constructed from captured harmonic data and the corresponding LV network topology. The simulation model has been verified by comparing with field measurement results. The VTHD and ITHD relationship curve and the attenuation effect curve for personal computers (PC) have been proposed by using the simulation model. In particular case study has been conducted to compare the conventional and state-of-art switch mode power supply (SMPS) used in PCs.

The objective of this paper is to show the characteristics of smart meters enabling to monitor and analyze the low-voltage (LV) network. This is achieved by developing use cases, where power quality and outage data are transferred from smart meters through distribution network to the control center. To visualize the monitoring process of LV network, the use cases are mapped into smart grid architecture model. The paper proposes a solution to analyze the LV network interruption and power quality problems (over-voltage, under-voltage, voltage sags, and swells). Thus, this paper provides a smart platform for monitoring LV network.

The high proportion of distributed photovoltaics (PVs) connected to distribution substation areas causes complex operation of the medium- and low-voltage distribution network. New power electronic devices represented by soft open point (SOP) can achieve a flexible interconnection between distribution substation areas. In this paper, a cooperative operation optimization method for medium- and low-voltage distribution networks considering flexible interconnected distribution substation areas is proposed. Firstly, interval affine is used to model the resource aggregation and obtain the flexibility region constraints of distribution substation areas. Then, a multi-scale cooperative operation framework for medium- and low-voltage distribution networks is constructed. The medium-voltage distribution network adopts the centralized method to solve and issue operation strategy instructions. The distribution substation area generates a voltage-reactive power adaptive regulation curve and performs intra-day rolling control. Finally, the case studies show that the proposed method has efficient operation strategy of medium- and low-voltage distribution networks and can alleviate the voltage fluctuation caused by high integration of PVs.

Accurate and reliable state estimation is the core stone for flexible operation and control of active smart grids. Through the current expansion of integrating DG units in low voltage networks, the network operation is becoming more complex than before. However, real-time monitoring and control through state estimation is a routine task for the transmission system operators (TSO's) due to the availability of measurement data. The distribution system operators (DSO's) are trying to extend their monitoring and control for medium and low voltage network in order to enable smart grid applications. With the current rollout of smart meters, which are considered as a key component of future smart grids, there would be enough metering data in the distribution networks (voltage, current, active and reactive power consumption and generation) available at every customer connection point. This paper aims to develop a method to solve the problem of meter placement for low voltage system state estimation through deciding which measurement data from the installed smart meters should be considered in the state estimation algorithms in order to improve on the uncertainty of the estimated voltage and its phase angle at every node in the network. (4 pages)

The rapid increase of distributed energy resources (DERs) installation at residential and commercial levels can pose significant technical issues on the voltage levels and capacity of the network assets in distribution networks. Most of these issues occur in low-voltage distribution networks (LVDNs) or near customer premises. A lack of understanding of the networks and advanced planning approaches by distribution network providers (DNSPs) has led to rough estimations for maximum DERs penetration levels that LVDNs can accommodate. These issues might under- or over-estimate the actual hosting capacity of the LVDNs. Limited available data on LVDNs' capacity to host DERs makes planning, installing, and connecting new DERs problematic and complex. In addition, the lack of transparency in LVDN data and information leads to model simplifications, such as ignoring the phase imbalance. This can lead to grossly inaccurate results. The main aim of this paper is to enable the understanding of the true extent of local voltage excursions to allow more targeted investment, improve the network's reliability, enhance solar performance distribution, and increase photovoltaic (PV) penetration levels in LVDNs. Therefore, this paper reviews the state-of-the-art best practices in modeling unbalanced LVDNs as accurately as possible to avoid under- or over-estimation of the network's hosting capacity. In addition, several PV system modeling variations are reviewed, showing their limitations and merits as a trade-off between accuracy, computational burden, and data availability. Moreover, the unbalanced power flow representations, solving algorithms, and available tools are explained extensively by providing a comparative study between these tools and the ones most commonly used in Australia. This paper also presents an overview of unbalanced optimal power flow representations with their related objectives, solving algorithms, and tools.

In the context of increasingly necessary energy transition, the precise modeling of profiles for low-voltage (LV) network consumers is crucial to enhance hosting capacity. Typically, load curves for these consumers are estimated through measurement campaigns conducted by Distribution System Operators (DSOs) for a representative subset of customers or through the aggregation of load curves from household appliances within a residence. With the instrumentation of smart meters becoming more common, a new approach to modeling profiles for residential customers is proposed to make the most of the measurements from these meters. The disaggregation model estimates the load profile of customers on a low-voltage network by disaggregating the load curve measured at the secondary substation level. By utilizing only the maximum power measured by Linky smart meters, along with the load curve of the secondary substation, this model can estimate the daily profile of customers. For 48 secondary substations in our dataset, the model obtained an average symmetric mean average percentage error (SMAPE) error of 4.91% in reconstructing the load curve of the secondary substation from the curves disaggregated by the model. This methodology can allow for an estimation of the daily consumption behaviors of the low-voltage customers. In this way, we can safely envision solutions that enhance the grid hosting capacity.

A dynamic reference voltage adjustment strategy for Open-UPQC to increase hosting capacity of electrical distribution networks

In low-voltage distribution networks, the integration of novel energy technologies can be accelerated through advanced optimization-based analytics such as network state estimation and network-constrained dispatch engines for distributed energy resources. The scalability of distribution network optimization models is challenging due to phase unbalance and neutral voltage rise effects necessitating the use of 4 times as many voltage variables per bus than in transmission systems. This paper proposes a novel technique to limit this to a factor 3, exploiting common physical features of low-voltage networks specifically, where neutral grounding is sparse, as it is in many parts of the world. We validate the proposed approach in OpenDSS, by translating a number of published test cases to the reduced form, and observe that the proposed "phase-to-neutral" transformation is highly accurate for the common single-grounded low-voltage network configuration, and provides a high-quality approximation for other configurations. We finally provide numerical results for unbalanced power flow optimization problems using PowerModelsDistribution.jl, to illustrate the computational speed benefits of a factor of about 1.42.

The low-voltage distribution networks have some structural features, such as short supply line, more lines branch and influence of transition resistance of the short-circuit current. These characteristics seriously affect the development of fault location technology. The paper, based on the basis of the structural features about the low-voltage distribution networks, create the distribution networks of description matrix by knowledge of mathematical topology and use the distribution network fault location algorithm based on web-based structure matrix. By the algorithm, the area of fault judgment and the actual distribution network fault location are fully consistent. The new theory provides a new way of thinking for fault location in low-voltage distribution networks.

Battery Energy Storage Systems (BESS) distributed over the Low Voltage (LV) network have been proposed as means of providing ancillary services in active distribution grids. Hence, optimal planning of BESS places and sizes is important so as to ensure economic and technical viability of such solutions. Most of the existing approaches for the optimal planning rely on previous knowledge of the network topology which, especially in low voltage networks, may not be available in practice. The paper assumes knowledge of P, Q, V measurements from smart meters placed in network leaf nodes only. At first, a topology identification algorithm is applied in order to estimate the network topology. Next, an algorithm for optimal sizing of BESS is applied on both the identified and original networks in order to assess the impact of topology identification potential errors in the planning procedure. Finally, the proposed algorithm is demonstrated on characteristic network cases.

Probabilistic framework for evaluating droop control of photovoltaic inverters

Recent investigations on the evaluation of solar PV hosting capacity in LV distribution networks constrained by voltage rise

Local control method and simulation analysis of hybrid AC/DC low-voltage distribution networks with high-proportion photovoltaics

With the roll-out of smart meters, data-driven methods based on smart meter data have become an important technical direction for consumer phase identification in low-voltage distribution network (LVDN). However, as a result of poor communication quality, human error, electricity theft and other reasons, the obtained power consumption data of consumers is incomplete and cannot fully reflect the power consumption of LVDN, which affects the recognition performance of the existing consumer phase identification methods. Under this background, this paper proposes a consumer phase identification algorithm based on the correlation characteristics to improve the accuracy of consumer phase identification with incomplete data. Firstly, the correlation characteristics among consumers and that between consumers and three-phase buses on the low voltage side of distribution transformer are deduced. Then, a preliminary phase identification method is proposed according to the correlation characteristics between consumers and three-phase buses on the low voltage side of distribution transformer. Finally, the correlation characteristics among consumers are used to correct the preliminary identification results. The proposed algorithm is applied on a real-world LVDN in Guangdong, China. The comparison analysis between the proposed method and other published methods are also investigated. The results indicate that the proposed method effectively increases the consumer phase identification accuracy compared with the published methods when the obtained power consumption data of consumers is incomplete.

Network reconfiguration for load balancing is the determination of switching-options for a particular set of loads on a distribution system that improves load balancing the most and is performed altering the topological structure of distribution feeders by changing open/closed status of sectionalizing and tie-switches. By transferring loads from the heavily loaded feeders to the lightly loaded ones, network reconfiguration can balance feeder loads and alleviate overload conditions of a network. In this paper a novel method is proposed by formulating an algorithm to reconfigure distribution networks for load balancing. Systematic logical approach is used to determine the feasible switching combinations, select the status of the switches, and find the best combination of switches for maximum improvement in load balancing. The algorithm has been developed in two stages. In the first stage, a limited number of switching combinations is formed by trinary logic principle. A simultaneous switching approach is applied logically to find the best combination by selecting the appropriate switching options, connecting the switches accordingly, and assigning the loads for the newly formed combinations. In the next stage, the search is extended to investigate whether any other switching combination gives rise to maximum improvement in load balancing, compared to the improvement obtained in the first stage. This is carried out by considering one after another, the branches next to the open-branches of the best configuration, and the switching configuration that gives the maximum improvement in load balancing is identified. The proposed method has been tested on a 69-bus test system, and the test results indicate that the algorithm proposed is able to determine the appropriate switching-options of the optimal (or near optimal) configuration with less computation. This paper proposes a scheme to implement the simultaneous switching algorithm for real-time on-line control of three-phase distribution networks, with symmetrical loading per phase.