Search

This paper presents a novel method to determine the optimal routing of medium voltage distribution networks in sparse rural areas. The objective is evaluated through minimizing the net present cost of the network over a selected time period. A problem specific genetic algorithm is proposed to address the optimal network routing problem and compute the optimized topology throughout a geographically constrained region. The proposed method simultaneously considers nonfixed candidate lines to overcome search space restrictions through a variable length encoding structure and the use of Steiner points, and a shortest path algorithm to traverse between point-to-point connections in the constrained region. Geographical restrictions on network routing are considered through the formation of a rasterized map. The network is modeled at the branch level and considers both greenfield and expansion planning to highlight the effects of accessibility restrictions. The optimization model is applied to a real rural distribution network in the South–West of Western Australia. Alternative network topologies are found to provide significant improvements over the existing network and traditional reconfiguration based methods for evaluating the minimum cost sparse rural distribution network. [ABSTRACT FROM AUTHOR]

Over the last decade, many power systems have significantly changed with the proliferation of renewable generation sources, such as wind and solar photovoltaic. Due to their variability and nonsynchronous nature, new challenges and complexities have emerged regarding operational security of modern power systems. The 2016 South Australia (SA) blackout was the first known blackout due to such a high renewable situation. An official report has recently been published to review the causes and provide the corresponding recommendations for improvement of network operation, control, and security. However, there are still a number of critical issues and debates which remain unsolved, such as network bottleneck identification, overvoltage explanation, pole slip concern, frequency dip mystery, and frequency/voltage instability debate. In this paper, based on the reconstruction of the event, these unsettled issues are prudently analyzed to unveil their root causes. In addition, an innovative scheme is proposed to prevent the blackout by identifying the network separation at an early stage. This research will not only further advance the understanding of the 2016 SA blackout, but also will provide valuable guidelines for the management of future renewable-rich networks. [ABSTRACT FROM AUTHOR]

The increasing uptake of electric vehicles suggests that vehicle charging will have a significant impact on the electricity grid. Finding ways to shift this charging to off-peak periods has been recognized as a key challenge for integration of electric vehicles into the electricity grid on a large scale. In this paper, electric vehicle charging is formulated as a receding horizon optimization problem that takes into account the present and anticipated constraints of the distribution network over a finite charging horizon. The constraint set includes transformer and line limitations, phase unbalance, and voltage stability within the network. By using a linear approximation of voltage drop within the network, the problem solution may be computed repeatedly in near real time, and thereby take into account the dynamic nature of changing demand and vehicle arrival and departure. It is shown that this linear approximation of the network constraints is quick to compute, while still ensuring that network constraints are respected. The approach is demonstrated on a validated model of a real network via simulations that use real vehicle travel profiles and real demand data. Using the optimal charging method, high percentages of vehicle uptake can be sustained in existing networks without requiring any further network upgrades, leading to more efficient use of existing assets and savings for the consumer. [ABSTRACT FROM PUBLISHER]