Multi-objective operation optimization of an electrical distribution network with soft open point

With the increasing amount of distributed generation (DG) integrated into electrical distribution networks, various operational problems, such as excessive power losses, over-voltage and thermal overloading issues become gradually remarkable. Innovative approaches for power flow and voltage controls are required to ensure the power quality, as well as to accommodate large DG penetrations. Using power electronic devices is one of the approaches. In this paper, a multi-objective optimization framework was proposed to improve the operation of a distribution network with distributed generation and a soft open point (SOP). An SOP is a distribution-level power electronic device with the capability of real-time and accurate active and reactive power flow control. A novel optimization method that integrates a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm and a local search technique – the Taxi-cab method, was proposed to determine the optimal set-points of the SOP, where power loss reduction, feeder load balancing and voltage profile improvement were taken as objectives. The local search technique is integrated to fine tune the non-dominated solutions obtained by the global search technique, overcoming the drawback of MOPSO in local optima trapping. Therefore, the search capability of the integrated method is enhanced compared to the conventional MOPSO algorithm. The proposed methodology was applied to a 69-bus distribution network. Results demonstrated that the integrated method effectively solves the multi-objective optimization problem, and obtains better and more diverse solutions than the conventional MOPSO method. With the DG penetration increasing from 0 to 200%, on average, an SOP reduces power losses by 58.4%, reduces the load balance index by 68.3% and reduces the voltage profile index by 62.1%, all compared to the case without an SOP. Comparisons between SOP and network reconfiguration showed the outperformance of SOP in operation optimization

Multi-objective optimization of electrical distribution network operation considering reconfiguration and soft open points

High penetration levels of Distributed Generations (DG) significantly affect the operations of electrical distribution networks. In this paper, Distribution Network Reconfiguration (DNR), and the implementation of Soft Open Point (SOP) – a distribution-level power electronic device are investigated as effective solutions to facilitate large DG penetrations while meeting network operational constraints. DNR is developed based on the ant colony optimization, and the optimal SOP outputs are determined using the Taxi-cab algorithm after determining the network configuration. Both optimization problems are formulated within a multi-objective framework using the Pareto optimality. The performances of DNR and SOP to improve network operations are demonstrated on a modified 33-bus distribution system with various DG penetrations

Reverse Nearest Neighbor Heat Maps: A Tool for Influence Exploration

We study the problem of constructing a reverse nearest neighbor (RNN) heat map by finding the RNN set of every point in a two-dimensional space. Based on the RNN set of a point, we obtain a quantitative influence (i.e., heat) for the point. The heat map provides a global view on the influence distribution in the space, and hence supports exploratory analyses in many applications such as marketing and resource management. To construct such a heat map, we first reduce it to a problem called Region Coloring (RC), which divides the space into disjoint regions within which all the points have the same RNN set. We then propose a novel algorithm named CREST that efficiently solves the RC problem by labeling each region with the heat value of its containing points. In CREST, we propose innovative techniques to avoid processing expensive RNN queries and greatly reduce the number of region labeling operations. We perform detailed analyses on the complexity of CREST and lower bounds of the RC problem, and prove that CREST is asymptotically optimal in the worst case. Extensive experiments with both real and synthetic data sets demonstrate that CREST outperforms alternative algorithms by several orders of magnitude.Comment: Accepted to appear in ICDE 201

Impacts of a medium voltage direct current link on the performance of electrical distribution networks

With an increasing number of distributed generators (DGs) integrated into distribution networks, operational problems such as excessive power losses, voltage violations and thermal overloads have occurred. Medium Voltage Direct Current (MVDC) technology represents a candidate solution to address these problems as well as to unlock the capacity of existing electrical network assets. In this paper, the capability of using an MVDC link to improve the performance of a distribution network, i.e. reducing power losses and increasing the hosting capacity for DG connections was investigated. A grid transformer (GT)-based control method was developed, in which the real-time data of the active power flow at GTs was used to specify the set-points of an MVDC link. The control strategies considered multiple objectives, i.e. power loss reduction, feeder load balancing, voltage profile improvement, and trade-off options among them. The response curves of these control strategies were developed through offline studies, where a multi-objective Particle Swarm Optimization (MOPSO) method was used. Case studies on a real distribution network were conducted to analyze the impacts of the MVDC link. The performances of the network were evaluated and compared between the proposed control strategies, using real demand and generation profiles. Results revealed that, for an MV distribution network, it might be beneficial to switch between different control strategies with the variations in demand and generation conditions. Results also showed that, regardless of the control strategy used, the MVDC link can significantly increase the network hosting capacity (up to 15%) for DGs, and reduce about 50% of power losses compared to a conventional alternative current (AC) line for the test network