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Voltage unbalance and magnitude violations under normal operating conditions have become main power quality problems in many low voltage (LV) distribution networks. Maintaining the voltage level in an LV network within the standard limits is the main constraining factor in increasing the network hosting ability for rooftop photovoltaic (PV). This study presents a new effective method for voltage management in unbalanced distribution networks through the implementation of optimal residential demand response (DR) and on-load tap changers (OLTCs). The proposed method minimises the compensation costs of voltage management (cost of DR and network loss), while prioritises the consumer consumption preferences for minimising their comfort level violations. A modified particle swarm optimisation algorithm (MPSO) is utilised to identify the optimal switching combination of household appliances and OLTC tap positions for the network voltage management. The proposed method is comprehensively examined on a real three-phase four-wire Australian LV network with considerable unbalanced and distributed generations. Several scenarios are investigated for improving the network voltage magnitude and unbalance considering individual and coordinated operations of DR and OLTCs (three phase tap control and independent phase tap control). Simulation results show that the coordinated approach of DR and OLTC, especially, DR integrated with OLTC independent phase tap control effectively improves the network voltage and increases the PV hosting capacity. [ABSTRACT FROM AUTHOR]

Time of Use (TOU) pricing is a cost-reflective electricity pricing scheme; it has proven to be an effective approach for reducing peak electricity demand in the residential sector around the world, especially in developed countries. The implementation of TOU pricing in low and lower-middle income economies is less appealing than in other settings. This is mainly because a traditional TOU pricing scheme may increase the cost of electricity for low income consumers. The lack of a suitable TOU pricing strategy for these countries results in high peak demand, poor utilization of network infrastructure and, consequently, higher electricity prices than necessary. The purpose of this study is to analyse and propose a TOU pricing scheme for the residential sector that will be suitable for countries with a high percentage of low income household consumers. In this study, Bangladesh will be used as an exemplar of a lower-to-middle income developing country. In Bangladesh, the residential sector is responsible for half the country's total electricity consumption, and constitutes an even greater proportion of the peak demand. Residential consumers currently pay inclining block usage rates that provide no financial incentive for them to shift their electricity usage from peak to non-peak periods. The proposed TOU pricing scheme is a combination of the traditional TOU and inclining block usage pricing schemes, based on a realistic load shifting capacity that is applicable to Bangladesh, and to other similar developing countries. Analysis of this pricing system for different income levels of residential consumers shows that the proposed scheme effectively reduces the peak demand, while ensuring minimum impact on consumer monthly energy bills and comfort levels. [ABSTRACT FROM AUTHOR]

Until now, microgrids were assumed to operate either in grid-connected or islanded modes. As a third alternative, neighboring microgrids may interconnect to support each other during faults in a section of one MG, or in the course of overloading. They may also interconnect to reduce the cost of electricity generation in their systems. Thereby, a microgrid will experience a significant transformation in its structure, when coupled with one or more neighboring microgrids. Before the formation of the system of coupled microgrids, the stability of the new system is vital to be cautiously examined to intercept the transformation, if instability is to occur. An eigenanalysis-based small signal stability evaluation technique is developed in this paper which can be used to allow/deny the interconnection of the microgrids. The analysis also defines the suitable range of control parameters for the energy resources of the CMG to guarantee the stability of the new system, if it was determined unstable. Numerical analyses, realized in MATLAB, are performed for the interconnection of a few sample microgrids. The accuracy of the developed technique is validated by comparing its results with the time-domain performance of the similar system, realized in PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]

Abstract: The experiences of the loss reduction projects in electric power distribution companies (EPDCs) of Iran are presented. The loss reduction methods, which are proposed individually by 14 EPDCs, corresponding energy saving (ES), Investment costs (IC), and loss rate reductions are provided. In order to illustrate the effectiveness and performance of the loss reduction methods, three parameters are proposed as energy saving per investment costs (ESIC), energy saving per quantity (ESPQ), and investment costs per quantity (ICPQ). The overall ESIC of 14 EPDC as well as individual average and standard deviation of the EISC for each method is presented and compared. In addition, the average and standard deviation of the ESPQs and ICPQs for the loss reduction methods, individually, are provided and investigated. These parameters are useful for EPDCs that intend to reduce the electric losses in distribution networks as a benchmark and as a background in the planning purposes. [Copyright &y& Elsevier]

Abstract: This paper presents an analytical method to analyze the effect of X to R ratio as well as impedance value of branches on observability of a network based on un-decoupled formulation of state estimation (SE) and null space of matrices. The results showed that the X to R ratio of branches had no effect on the observability of networks. In addition, it was shown that observability of some networks was affected by impedance values while some others were not affected. In addition, for branch observability analysis of radial network, a simple and quick method is developed. Illustrative examples of the network under transmission and distribution voltages demonstrate the effectiveness of the proposed methods. [Copyright &y& Elsevier]

Highlights • Updating pseudo data considering the impact of spatial-temporal correlation. • Studying the impact of load aggregation and PV penetration on spatial-temporal correlation. • Developing a non-iterative computationally efficient DSSE algorithm. • Proposing a time series state estimation framework suitable for unbalanced LV distribution networks. Abstract The increasing complexity of distribution networks calls for advancement in distribution system state estimation (DSSE) to monitor the operating conditions more accurately. A sufficient number of measurement devices is imperative for a reliable and accurate state estimation. The limitation on the measurement devices is generally tackled with using the so-called pseudo measured data. However, the errors in pseudo data by current techniques are quite high leading to a poor DSSE. As customer loads in distribution networks show high cross-correlation in various locations and over successive time steps, it is plausible that deploying the spatial-temporal dependencies can improve the pseudo data accuracy and estimation. Although the role of spatial dependencies in DSSE has been addressed in the literature, one can hardly find an efficient DSSE framework capable of incorporating temporal dependencies present in customer loads. Consequently, to obtain a more efficient and accurate state estimation, we propose a new non-iterative DSSE framework to involve spatial-temporal dependencies together. The spatial-temporal dependencies are modeled by conditional multivariate complex Gaussian distributions and are studied for both static and real-time state estimations, where information at preceding time steps are employed to increase the accuracy of DSSE. The efficiency of the proposed approach is verified based on the quality and accuracy of the indices, standard deviation and computational time. The method applied to a combination of residential and industrial customer loads in three different balanced medium voltage (MV), and one unbalanced low voltage (LV) distribution case studies for evaluations. [ABSTRACT FROM AUTHOR]

• Coordinating conventional Volt-VAr devices with distributed energy resources. • Incorporating demand response program into the Volt-VAr control problem. • Utilizing ε-constraint approach to generate Pareto optimal solutions. • Using IGDT to develop a robust decision-making approach. • Developing a mixed-integer linear programing framework. Distributed energy resources (DERs), such as renewable energy sources (RESs) and energy storage systems (ESSs), are inevitable parts of future power grids. However, the high penetration of RESs may cause voltage violation issues in distribution levels. To this end, the application of the Volt-VAr management (VVM) scheme is highlighted. This paper aims to maintain voltage levels within standard ranges with optimal coordination of different resources at minimum operational costs and voltage deviation. In more detail, this article develops a new VVM in distribution networks to effectively coordinate novel smart grid technologies such as PV inverters, time of use demand response program (TOU-DRP), energy storage systems (ESSs) with traditional devices, including on-line tap changer transformer (OLTC) and switchable capacitor banks (SCBs). Because the coordinated VVM is a bi-objective model that minimizes both operating cost and voltage deviation, it is proposed to use the ε-constraint technique to identify optimal Pareto solutions. To handle the uncertainty related to RESs and load demands, a robust technique based on information gap decision theory (IGDT) is also utilized. The formulation is configured as a mixed-integer linear program (MILP) and solved by CPLEX. It was implemented on the 118-bus distribution network under various conditions. The simulation results clearly show that the coordination of DERs and traditional devices has a significant impact on maintaining voltage levels within permissible ranges while minimizing operational costs. A higher degree of uncertainty radius can also be obtained if DRP participates in the VVM scheme. [ABSTRACT FROM AUTHOR]

The optimal operation of active distribution systems in the presence of private renewable-based entities is one of the primary challenges of future power networks. In this regard, developing a practical framework to deal with this kind of issue is essential. Hence, in this paper, a novel bi-level stochastic programming approach is presented for optimal energy and reserve scheduling of the active distribution system in the presence of different eco-efficient autonomous players. In the proposed model, the distribution system operator, as a leader, attempts to minimize its total operating costs. At the same time, the renewable-based microgrid owner, as an independent follower, tends to maximize its profit from exchanging energy and reserve with the distribution system operator. The suggested scheme is a non-linear bi-level problem which is transformed into a non-linear single-level problem through Karush–Kuhn–Tucker conditions. In order to find the global optima, the non-linear single-level problem is linearized by utilizing the Big-M method. Finally, to investigate the effectiveness of the provided model, it is tested on the modified IEEE 15-Bus active distribution system under different cases and scenarios. Obtained results indicate that the operation cost of the distribution system operator can be reduced up to 134.09$, from 10710.11$ to 10576.02$, and the profit of the microgrid owner can be increased significantly 906.93$, from 659.455$ to 1566.39$, by considering both environmentally friendly units, IPL and CAES. • Optimal operation of the Active Distribution System in the presence of a private renewable-based Microgrid is addressed. • A stochastic bi-level programming approach is proposed for joint energy and reserve scheduling of the considered system. • Impacts of Intelligent Parking Lot and Compressed Air Energy Storage are investigated on optimal operation of the system. • A new framework is provided for the participation of the system's independent players in separate electricity markets. [ABSTRACT FROM AUTHOR]