PSO based multi-objective optimization of unbalanced lv distribution network by PV inverter control

The rapid expansion of consumer-driven installations of residential photovoltaic (PV) systems causes serious power quality issues, e.g. notable voltage variations and unbalance, which not only detrimentally affects security and stability of distribution network operation, but also limits the number and capacity of further PV connections. Based on both reactive power management and real power curtailment of inverters, this study proposes a comprehensive PV control strategy to improve the performance of unbalanced three-phase four-wire low voltage (LV) distribution networks with high PV penetrations. The optimal combination of PV set points is determined by solving a multi-objective optimal power flow (OPF) problem that can simultaneously improve voltage magnitude and balance profiles while minimizing network loss, inverter loss associated with reactive power generation and the cost of real power generation curtailment. To reflect preferences on control objectives, the multi-objective problem is reformulated into an aggregated single-objective problem using weighted sum method and then solved by the global particle swarm optimization (PSO) in MATLAB. Detailed simulations are performed and analysed for a typical scenario of high PV penetration on a real three-phase four-wire unbalanced distribution network in Perth Solar City trial, Australia. © 2014 IEEE

Cyber-Security Constrained Placement of FACTS Devices in Power Networks from a Novel Topological Perspective

Optimal placement of flexible AC transmission systems (FACTS) devices and the cyber-security of associated data exchange are crucial for the controllability of wide area power networks. The placement of FACTS devices is studied in this paper from a novel graph theoretic perspective, which unlike the existing approaches, purely relies on topological characteristics of the underlying physical graphs of power networks. To this end, the maximum matching principle (MMP) is used to find the set of required FACTS devices for the grid controllability. In addition, the cyber-security of the most critical data related to the FACTS controllers is guaranteed by introducing the concept of moderated- $k$ -security where $k$ is a measure of data obscurity from the adversary perspective. The idea of moderated- $k$ -symmetry is proposed to facilitate the arrangement of the published cyber graph based on a permutation of nodes within the symmetry group of the grid, called generator of automorphism. It is then verified that the published cyber-graph can significantly obscure the data exchange over the cyber graph for adversaries. Finally, a similarity is observed and demonstrated between the set of critical nodes attained from the symmetry analysis and the solution of the FACTS devices placement that further highlights the importance of symmetry for the analysis and design of complex power networks. Detailed simulations are applied to three power networks and analyzed to demonstrate the performance and eligibility of the proposed methods and results

Robust Placement and Sizing of Charging Stations from a Novel Graph Theoretic Perspective

This paper proposes analytical approaches to extend the capacity of existing networks of electric vehicles (EVs) by placement of additional charging stations (CSs) as well as determining the sizes of existing and new CSs in order to handle future expansions of EVs. The EV flow at CSs is modeled by a graph where nodes are potential locations for CSs and edges are uncertain parameters representing the variable EV flow at CSs. The required extra CS locations are explored by transforming the CS placement problem into a controllability framework addressed by maximum matching principle (MMP). To find the sizes of each CS, the graph of CS network is partitioned featuring only one CS in each subgraph. The size of CS in each subgraph is then determined by transforming the problem into the problem of robust stability of a system with uncertain parameters where each parameter is associated with an edge of subgraph. The zero exclusion principle is then tested for the related Kharitonov rectangles and polygonal polynomials of closed loop system with selected feedback gain as CS capacity. The proposed analytical approach is tested on the existing Tesla CS Network of Sydney. The locations of extra required CSs as well as the sizes of existing and new CSs are determined to maintain the waiting times at all stations below the threshold level

A comprehensive three-phase load flow method for integrated MV and LV distribution networks

In the smart grid era, significant penetrations of distributed renewables not only directly impact the secondary low-voltage (LV) distribution network where they are connected, but also indirectly affect the primary medium-voltage (MV) distribution network. Therefore, load flow algorithms are expected to cover both MV and LV levels within a distribution network for more accurate and reasonable analyses. In this study, based on the Direct Load Flow approach and detailed modeling of common Dyn11 distribution transformers, a comprehensive three-phase load flow method which can effectively and efficiently solve the integrated MV and LV distribution networks is proposed. The feasibility and effectiveness as well as superior computational performance in terms of accuracy, efficiency and robustness are verified by simulations on the typical IEEE 4-bus test feeder and a real Australian distribution network over 24 hours