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 graph automorphic approach for placement and sizing of charging stations in EV network considering traffic

This paper proposes a novel graph-based approach with automorphic grouping for the modelling, synthesis, and analysis of electric vehicle (EV) networks with charging stations (CSs) that considers the impacts of traffic. The EV charge demands are modeled by a graph where nodes are positioned at potential locations for CSs, and edges represent traffic flow between the nodes. A synchronization protocol is assumed for the network where the system states correspond to the waiting time at each node. These models are then utilized for the placement and sizing of CSs in order to limit vehicle waiting times at all stations below a desirable threshold level. The main idea is to reformulate the CS placement and sizing problems in a control framework. Moreover, a strategy for the deployment of portable charging stations (PCSs) in selected areas is introduced to further improve the quality of solutions by reducing the overshooting of waiting times during peak traffic hours. Further, the inherent symmetry of the graph, described by graph automorphisms, are leveraged to investigate the number and positions of CSs. Detailed simulations are performed for the EV network of Perth Metropolitan in Western Australia to verify the effectiveness of the proposed approach

Comparative and performative investigation of various data-based and conventional theoretical methods for modelling heat pipe solar collectors

Solar collector, as the key component of any solar system, has always been the focal point of research in the field of solar energy. Based on the literature, data-based methods, which have been proven to be promising in accurate modelling of solar collectors, have not been used for modelling heat pipe solar collectors (HPSCs). At the same time, accurate equations relating the thermal efficiency of solar collectors to the operational and climatic conditions have not been obtained for HPSCs. Therefore, in this study, various data-based and energy balance-based modelling methods were proposed, and based on different accuracy criteria, their precisions were compared in predicting the performance of HPSCs. First, an experimental rig was manufactured and the operational data of the system was recorded throughout a year. The recorded experimental data was used to train and validate various modelling approaches. Then, the accuracies of the proposed models were analysed and assessed. The evaluated models included Artificial Neural Network (ANN), Thermal Resistance Network (TRN), Artificial Neuro Fuzzy Inference System (ANFIS), and Fuzzy methods. Among different modelling approaches, ANN had the best performance which was followed by the ANFIS and TRN methods. The Fuzzy method was not recommended due to its poor accuracy. In addition, the optimum equations relating the outlet temperature of HPSCs to the operational conditions of the solar water heating systems as well as the climatic conditions were obtained and verified

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

Position Control of Motor Drive Systems: A Data Driven Approach

International audienceA new model-free approach for designing robust PID controllers for the position control of electrical machines (such as induction, synchronous or DC motors) with un-modeled dynamics is proposed. In this paper, it is illustrated that frequency response data is sufficient to calculate a family of robust PID controllers that satisfy an-norm on the complementary sensitivity function. The approach is illustrated on an induction motor drive system through simulation

Position Control of Motor Drive Systems: A Data Driven Approach

This paper presents a new model free approach to the design of robust PID controller for the position control of electrical machines, such as induction motor, synchronous motor and DC motor faced to un-modeled dynamics. It is illustrated that knowing the frequency response data is sufficient to calculate the family of robust PID controllers that satisfy -norm on the complementary sensitivity function. The usefulness of the proposed approach is demonstrated through simulation on an induction motor drive system

Graph automorphic approaches to the robustness of complex networks

© 2020 Elsevier Ltd Leveraging on graph automorphic properties of complex networks (CNs), this study investigates three robustness aspects of CNs including the robustness of controllability, disturbance decoupling, and fault tolerance against failure in a network element. All these aspects are investigated using a quantified notion of graph symmetry, namely the automorphism group, which has been found implications for the network controllability during the last few years. The typical size of automorphism group is very big. The study raises a computational issue related to determining the whole set of automorphism group and proposes an alternative approach which can attain the emergent symmetry characteristics from the significantly smaller groups called generators of automorphisms. Novel necessary conditions for network robust controllability following a failure in a network element are attributed to the properties of the underlying graph symmetry. Using a symmetry related concept called determining set and a geometric control property called controlled invariant, the new necessary and sufficient conditions for disturbance decoupling are proposed. In addition, the critical nodes/edges of the network are identified by determining their role in automorphism groups. We verify that nodes with more repetition in symmetry groups of the network are more critical in characterizing the network robustness. Further, the impact of elimination of critical network elements on its robustness is analyzed by calculating a new improved index of symmetry which considers the orbital impacts of automorphisms. The importance of all symmetry inspired findings of this paper is highlighted via simulation on various networks

Placement and sizing of EV charging stations according to centrality of the underlying network

EV placement and sizing are the subject of ever increasing studies in the last decade mostly relying on optimization approaches. This study looks at the EV network as a complex network where the nodes are the potential locations of charging stations (CSs) and edges (links) represent the traffic flow. It then investigates the impacts of some graph properties on the solutions of the CS placement problem. In fact, the graph centrality and its variants are used to find the locations of CSs to reduce the average waiting times at the stations. It is shown that the centrality based analysis can lead to promising results for small and medium EV networks leaving the large networks to be addressed by more complicated approaches. Simulations are performed on the central (downtown) part of Perth City EV network, Western Australia scaled down by the real traffic information