2020 Intermountain Engineering, Technology and Computing (IETC), 2020
EV placement and sizing are the subject of ever increasing studies in the last decade mostly rely... more 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.
Abstract Leveraging on graph automorphic properties of complex networks (CNs), this study investi... more Abstract 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.
In this work we present three Intrinsic Conducting Polymers (ICP) for Wi-Fi Electromagnetic Inter... more In this work we present three Intrinsic Conducting Polymers (ICP) for Wi-Fi Electromagnetic Interference (EMI) shielding; Polyaniline (PAni), Polypyrrole (PPy) and PEDOT:PSS (Poly(3,4-ethylenedioxythiophene: poly(styrenesulfonate)). The ICP materials will be used to minimize the problems with Electromagnetic Shielding (EMS), and provide protection from Electromagnetic Radiation (EMR) and Electromagnetic Interference (EMI). There is a great need to shield Wi-Fi and mobile phones from various unwanted communication systems signals, concurrently preserving the amount of radiated Electromagnetic Interference that is absorbed from the device/system. This is a balance which is called Electromagnetic Compatibility (EMC). With the increased development inWi-Fi and telecommunications equipment, EMI sources will increase and a simple method is required to test for transmission losses. The research in this paper focuses on the Wi-Fi microwave frequency of 2.45 GHz and the testing of the Intrin...
Abstract Establishing reliable, clean, and inexpensive solar PV systems is a complex interplay be... more Abstract Establishing reliable, clean, and inexpensive solar PV systems is a complex interplay between the level of reliability (LPSP), financial constraints, and CO2 emissions. This paper investigates the impact of these factors on stand-alone (SA) and grid-supplemented (GS) solar PV systems over multiple seasons. The research uses established hardware models, detailed power management strategies as well as realistic Australian grid tariffs and Genetic Algorithms to find the minimum Cost of Energy (COE) subject to LPSP and financial constraints. The developed power management strategies are also tested experimentally on a real solar PV system. The results indicate that the grid-supplemented system yields 30% lower COE compared to the stand-alone at baseline (LPSP
Abstract This paper presents an intelligent mechanism for Short Term Load Forecasting (STLF) mode... more Abstract This paper presents an intelligent mechanism for Short Term Load Forecasting (STLF) models, which allows self-adaptation with respect to the load operational conditions. Specifically, a knowledge-based FeedBack Tunning Fuzzy System (FBTFS) is proposed to instantaneously correlate the information about the demand profile and its operational conditions to make decisions for controlling the model’s forecasting error rate. To maintain minimum forecasting error under various operational scenarios, the FBTFS adaptation was optimised using a Multi-Layer Perceptron Artificial Neural Network (MLPANN), which was trained using Backpropagation algorithm, based on the information about the amount of error and the operational conditions at time of forecasting. For the sake of comparison and performance testing, this mechanism was added to the conventional forecasting methods, i.e. Nonlinear AutoRegressive eXogenous-Artificial Neural Network (NARXANN), Fuzzy Subtractive Clustering Method-based Adaptive Neuro Fuzzy Inference System (FSCMANFIS) and Gaussian-kernel Support Vector Machine (GSVM), and the measured forecasting error reduction average in a 12 month simulation period was 7.83%, 8.5% and 8.32% respectively. The 3.5 MW variable load profile of Edith Cowan University (ECU) in Joondalup, Australia, was used in the modelling and simulations of this model, and the data was provided by Western Power, the transmission and distribution company of the state of Western Australia.
International Journal of Electrical Power & Energy Systems, 2013
ABSTRACT This paper presents an optimal power flow controller for a utility connected microgrid b... more ABSTRACT This paper presents an optimal power flow controller for a utility connected microgrid based on a real-time self-tuning method. The purpose is to control the flow of the active and reactive power between the main grid and the microgrid composed of Distributed Generation (DG) units. Sharing power at the desired ratio by the DG units is the main performance parameter which is considered during the load change. This paper also shows the response of the controller in situations, where the load is either higher or greatly lower than the rated power of the DG unit. In this work, the controller scheme is composed of an inner current control loop and an outer power control loop based on a synchronous reference frame and the conventional PI regulators. The power controller is designed for active–reactive power (PQ) control strategy. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the power control parameters. In this paper, the proposed strategy is that the required load power is shared equally between the microgrid and the utility based on the PSO algorithm during the load change. The utility supplies the difference power when the load is more than the power generated by the microgrid, while it injects the extra power to the grid when the load is less than the power generated by the microgrid. The results show that the proposed controller offers an excellent response and proves the validity of the proposed strategy.
Abstract—This paper presents an optimal power control strat-egy for an autonomous microgrid opera... more Abstract—This paper presents an optimal power control strat-egy for an autonomous microgrid operation based on a real-time self-tuning method. The purpose of this work is to improve the quality of power supply where Distributed Generation (DG) units are connected to the grid. Dynamic response and harmonics distortion are the two main performance parameters which are considered in this work, particularly when the microgrid is islanded. The controller scheme is composed of an inner current control loop and an outer power control loop based on a synchronous reference frame and the conventional PI regulators. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the system. The results show that the proposed controller provides an excellent dynamic response with acceptable harmonics level. Index Terms—Microgrid, power controller, current controller, Particle Swarm Optimization (PSO). I.
This study investigates on a strong correlation between complex network (CN) controllability (cha... more This study investigates on a strong correlation between complex network (CN) controllability (characterized by the number of required driver nodes) and graph symmetry (described by automorphism groups) in undirected and unweighted networks. Based on the properties of permutation products of elementary automorphisms, novel necessary conditions for CN controllability are presented which are computationally more effective than previous method. In addition, a novel index of symmetry is proposed upon which a more meaningful understanding of symmetry impact on CN controllability can be comprehended. Based on this new index, a modification strategy is suggested aiming to satisfy CN controllability with a lower number of driver nodes. The study shows that the proposed modification approach can result in a minimal set of driver nodes with a reasonable computational complexity. Further, the critical components of complex networks, in terms of their impact on the number of required driver node...
Fuzzy Inference Systems (FIS) have been widely used in many applications including image processi... more Fuzzy Inference Systems (FIS) have been widely used in many applications including image processing, optimization, control and system identification. Among these applications, we would like to investigate energy demand modelling. Generally, developing an energy demand model is the challenge of interpreting the historical use of energy in an electric power network into equations which approximate the future use of energy. The developed model’s equations are coded and embedded into a processor based system, which predicts the output when a certain type of input occurs. However, the range and quality of prediction is still limited within the knowledge supplied to the model. The major concern about the energy demand modelling is to categorize the type of prediction in short or longterm prediction. In addition, it is crucial to categorize the type of the power network to be modelled. Since identifying the useful historical operation data for setting the model parameters is crucial in mod...
Abstract—Efficient generation and distribution are crucial for economic power production. In this... more Abstract—Efficient generation and distribution are crucial for economic power production. In this paper we discuss the planning and design of upgrading a medium size enterprise power system by installing Distributed Energy Resources (DERs), with partic-ular emphasis on economic viability and environmental benefits. The planning for this project considers both conventional grid and SmartGrid connections. Project planning, installation chal-lenges and governmental support of renewable energy projects in Australia are discussed. It is found that upgrading a medium size enterprise power system with DERs can yield reasonable levels of energy cost savings and greenhouse gas mitigation with both conventional grid and SmartGrid connections, but that SmartGrid connection can deliver better outcomes. Index Terms—medium size enterprise power systems, solar and wind energies integration with smartgrid, economic and environmental analyses of energy projects I.
2020 Intermountain Engineering, Technology and Computing (IETC), 2020
EV placement and sizing are the subject of ever increasing studies in the last decade mostly rely... more 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.
Abstract Leveraging on graph automorphic properties of complex networks (CNs), this study investi... more Abstract 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.
In this work we present three Intrinsic Conducting Polymers (ICP) for Wi-Fi Electromagnetic Inter... more In this work we present three Intrinsic Conducting Polymers (ICP) for Wi-Fi Electromagnetic Interference (EMI) shielding; Polyaniline (PAni), Polypyrrole (PPy) and PEDOT:PSS (Poly(3,4-ethylenedioxythiophene: poly(styrenesulfonate)). The ICP materials will be used to minimize the problems with Electromagnetic Shielding (EMS), and provide protection from Electromagnetic Radiation (EMR) and Electromagnetic Interference (EMI). There is a great need to shield Wi-Fi and mobile phones from various unwanted communication systems signals, concurrently preserving the amount of radiated Electromagnetic Interference that is absorbed from the device/system. This is a balance which is called Electromagnetic Compatibility (EMC). With the increased development inWi-Fi and telecommunications equipment, EMI sources will increase and a simple method is required to test for transmission losses. The research in this paper focuses on the Wi-Fi microwave frequency of 2.45 GHz and the testing of the Intrin...
Abstract Establishing reliable, clean, and inexpensive solar PV systems is a complex interplay be... more Abstract Establishing reliable, clean, and inexpensive solar PV systems is a complex interplay between the level of reliability (LPSP), financial constraints, and CO2 emissions. This paper investigates the impact of these factors on stand-alone (SA) and grid-supplemented (GS) solar PV systems over multiple seasons. The research uses established hardware models, detailed power management strategies as well as realistic Australian grid tariffs and Genetic Algorithms to find the minimum Cost of Energy (COE) subject to LPSP and financial constraints. The developed power management strategies are also tested experimentally on a real solar PV system. The results indicate that the grid-supplemented system yields 30% lower COE compared to the stand-alone at baseline (LPSP
Abstract This paper presents an intelligent mechanism for Short Term Load Forecasting (STLF) mode... more Abstract This paper presents an intelligent mechanism for Short Term Load Forecasting (STLF) models, which allows self-adaptation with respect to the load operational conditions. Specifically, a knowledge-based FeedBack Tunning Fuzzy System (FBTFS) is proposed to instantaneously correlate the information about the demand profile and its operational conditions to make decisions for controlling the model’s forecasting error rate. To maintain minimum forecasting error under various operational scenarios, the FBTFS adaptation was optimised using a Multi-Layer Perceptron Artificial Neural Network (MLPANN), which was trained using Backpropagation algorithm, based on the information about the amount of error and the operational conditions at time of forecasting. For the sake of comparison and performance testing, this mechanism was added to the conventional forecasting methods, i.e. Nonlinear AutoRegressive eXogenous-Artificial Neural Network (NARXANN), Fuzzy Subtractive Clustering Method-based Adaptive Neuro Fuzzy Inference System (FSCMANFIS) and Gaussian-kernel Support Vector Machine (GSVM), and the measured forecasting error reduction average in a 12 month simulation period was 7.83%, 8.5% and 8.32% respectively. The 3.5 MW variable load profile of Edith Cowan University (ECU) in Joondalup, Australia, was used in the modelling and simulations of this model, and the data was provided by Western Power, the transmission and distribution company of the state of Western Australia.
International Journal of Electrical Power & Energy Systems, 2013
ABSTRACT This paper presents an optimal power flow controller for a utility connected microgrid b... more ABSTRACT This paper presents an optimal power flow controller for a utility connected microgrid based on a real-time self-tuning method. The purpose is to control the flow of the active and reactive power between the main grid and the microgrid composed of Distributed Generation (DG) units. Sharing power at the desired ratio by the DG units is the main performance parameter which is considered during the load change. This paper also shows the response of the controller in situations, where the load is either higher or greatly lower than the rated power of the DG unit. In this work, the controller scheme is composed of an inner current control loop and an outer power control loop based on a synchronous reference frame and the conventional PI regulators. The power controller is designed for active–reactive power (PQ) control strategy. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the power control parameters. In this paper, the proposed strategy is that the required load power is shared equally between the microgrid and the utility based on the PSO algorithm during the load change. The utility supplies the difference power when the load is more than the power generated by the microgrid, while it injects the extra power to the grid when the load is less than the power generated by the microgrid. The results show that the proposed controller offers an excellent response and proves the validity of the proposed strategy.
Abstract—This paper presents an optimal power control strat-egy for an autonomous microgrid opera... more Abstract—This paper presents an optimal power control strat-egy for an autonomous microgrid operation based on a real-time self-tuning method. The purpose of this work is to improve the quality of power supply where Distributed Generation (DG) units are connected to the grid. Dynamic response and harmonics distortion are the two main performance parameters which are considered in this work, particularly when the microgrid is islanded. The controller scheme is composed of an inner current control loop and an outer power control loop based on a synchronous reference frame and the conventional PI regulators. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the system. The results show that the proposed controller provides an excellent dynamic response with acceptable harmonics level. Index Terms—Microgrid, power controller, current controller, Particle Swarm Optimization (PSO). I.
This study investigates on a strong correlation between complex network (CN) controllability (cha... more This study investigates on a strong correlation between complex network (CN) controllability (characterized by the number of required driver nodes) and graph symmetry (described by automorphism groups) in undirected and unweighted networks. Based on the properties of permutation products of elementary automorphisms, novel necessary conditions for CN controllability are presented which are computationally more effective than previous method. In addition, a novel index of symmetry is proposed upon which a more meaningful understanding of symmetry impact on CN controllability can be comprehended. Based on this new index, a modification strategy is suggested aiming to satisfy CN controllability with a lower number of driver nodes. The study shows that the proposed modification approach can result in a minimal set of driver nodes with a reasonable computational complexity. Further, the critical components of complex networks, in terms of their impact on the number of required driver node...
Fuzzy Inference Systems (FIS) have been widely used in many applications including image processi... more Fuzzy Inference Systems (FIS) have been widely used in many applications including image processing, optimization, control and system identification. Among these applications, we would like to investigate energy demand modelling. Generally, developing an energy demand model is the challenge of interpreting the historical use of energy in an electric power network into equations which approximate the future use of energy. The developed model’s equations are coded and embedded into a processor based system, which predicts the output when a certain type of input occurs. However, the range and quality of prediction is still limited within the knowledge supplied to the model. The major concern about the energy demand modelling is to categorize the type of prediction in short or longterm prediction. In addition, it is crucial to categorize the type of the power network to be modelled. Since identifying the useful historical operation data for setting the model parameters is crucial in mod...
Abstract—Efficient generation and distribution are crucial for economic power production. In this... more Abstract—Efficient generation and distribution are crucial for economic power production. In this paper we discuss the planning and design of upgrading a medium size enterprise power system by installing Distributed Energy Resources (DERs), with partic-ular emphasis on economic viability and environmental benefits. The planning for this project considers both conventional grid and SmartGrid connections. Project planning, installation chal-lenges and governmental support of renewable energy projects in Australia are discussed. It is found that upgrading a medium size enterprise power system with DERs can yield reasonable levels of energy cost savings and greenhouse gas mitigation with both conventional grid and SmartGrid connections, but that SmartGrid connection can deliver better outcomes. Index Terms—medium size enterprise power systems, solar and wind energies integration with smartgrid, economic and environmental analyses of energy projects I.
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Papers by Octavian Bass