Practice and Innovations in Sustainable Transport

The book continues with an experimental analysis conducted to obtain accurate and complete information about electric vehicles in different traffic situations and road conditions. For the experimental analysis in this study, three different electric vehicles from the Edinburgh College leasing program were equipped and tracked to obtain over 50 GPS and energy consumption data for short distance journeys in the Edinburgh area and long-range tests between Edinburgh and Bristol. In the following section, an adaptive and robust square root cubature Kalman filter based on variational Bayesian approximation and Huber’s M-estimation is proposed to accurately estimate state of charge (SOC), which is vital for safe operation and efficient management of lithium-ion batteries. A coupled-inductor DC-DC converter with a high voltage gain is proposed in the following section to match the voltage of a fuel cell stack to a DC link bus. Finally, the book presents a review of the different approaches that have been proposed by various authors to mitigate the impact of electric buses and electric taxis on the future smart grid

Advanced Battery Technologies: New Applications and Management Systems

In recent years, lithium-ion batteries (LIBs) have been increasingly contributing to the development of novel engineering systems with energy storage requirements. LIBs are playing an essential role in our society, as they are being used in a wide variety of applications, ranging from consumer electronics, electric mobility, renewable energy storage, biomedical applications, or aerospace systems. Despite the remarkable achievements and applicability of LIBs, there are several features within this technology that require further research and improvements. In this book, a collection of 10 original research papers addresses some of those key features, including: battery testing methodologies, state of charge and state of health monitoring, and system-level power electronics applications. One key aspect to emphasize when it comes to this book is the multidisciplinary nature of the selected papers. The presented research was developed at university departments, institutes and organizations of different disciplines, including Electrical Engineering, Control Engineering, Computer Science or Material Science, to name a few examples. The overall result is a book that represents a coherent collection of multidisciplinary works within the prominent field of LIBs

Advances and Technologies in High Voltage Power Systems Operation, Control, Protection and Security

The electrical demands in several countries around the world are increasing due to the huge energy requirements of prosperous economies and the human activities of modern life. In order to economically transfer electrical powers from the generation side to the demand side, these powers need to be transferred at high-voltage levels through suitable transmission systems and power substations. To this end, high-voltage transmission systems and power substations are in demand. Actually, they are at the heart of interconnected power systems, in which any faults might lead to unsuitable consequences, abnormal operation situations, security issues, and even power cuts and blackouts. In order to cope with the ever-increasing operation and control complexity and security in interconnected high-voltage power systems, new architectures, concepts, algorithms, and procedures are essential. This book aims to encourage researchers to address the technical issues and research gaps in high-voltage transmission systems and power substations in modern energy systems

Enhanced power system resiliency to high-impact, low-frequency events with emphasis on geomagnetic disturbances

Various reliability procedures have been developed to protect the power systems against common reliability issues that threaten the grid frequently. However, these procedures are unlikely to be sufficient for high-impact low-frequency (HILF) events. This thesis proposes several techniques to enhance resiliency with respect to HILF events. In particular, we focus on cyber-physical attacks and geomagnetic disturbances (GMDs). Corrective control through generation redispatch is proposed to protect the system from cyber-physical attacks. A modification of the optimal power flow (OPF) is proposed which optimizes the system resiliency instead of the generation cost. For larger systems, the burden of solving the resilience-oriented OPF is reduced through a fast greedy algorithm which utilizes proper heuristics to narrow the search space. Moreover, an effective line switching algorithm is developed to minimize the GMD impact for large-scale power systems. The algorithm uses linear sensitivity analysis to find the best switching strategy and minimizes the GIC-saturated reactive power loss. The resiliency may be improved through power system monitoring and situational awareness. Power system data is growing rapidly with the everyday installation of different types of sensors throughout the network. In this thesis, various data analytics tools are proposed to effectively employ the sensor data for enhancing resiliency. In particular, we focus on the application of real data analysis to improve the GMD models. We identify common challenges in dealing with real data and develop effective tools to tackle them. A frequent issue with model validation is that for a real system, the parameters of the model to be validated may be inaccurate or even unavailable. To handle this, two approaches are proposed. The first approach is to develop a validation framework which is independent of the model parameters and completely relies on the measurements. Although this technique successfully handles the system uncertainties and offers a robust validation tool, it does not provide the ability to utilize the available network parameters. Sometimes, the network parameters are partially available with some degree of accuracy and it is desired to take advantage of this additional information. The second validation framework provides this capability by first modifying the model to account for the missing or inaccurate parameters. Then a suitable validation framework is built upon that model. Another common issue that is widely encountered in data analysis techniques is incomplete data when part of the required data is missing or is invalid. Examples of missing data are provided through real case studies, and advanced imputation tools are developed to handle them

Open circuit voltage and state of charge relationship functional optimization for the working state monitoring of the aerial lithium-ion battery pack.

The aerial lithium-ion battery pack works differently from the usual battery packs, the working characteristic of which is intermittent supplement charge and instantaneous large current discharge. An adaptive state of charge estimation method combined with the output voltage tracking strategy is proposed by using the reduced particle - unscented Kalman filter, which is based on the reaction mechanism and experimental characteristic analysis. The improved splice equivalent circuit model is constructed together with its state-space description, in which the operating characteristics can be obtained. The relationship function between the open circuit voltage and the state of charge is analyzed and especially optimized. The feasibility and accuracy characteristics are tested by using the aerial lithium-ion battery pack experimental samples with seven series-connected battery cells. Experimental results show that the state of charge estimation error is less than 2.00%. The proposed method achieves the state of charge estimation accurately for the aerial lithium-ion battery pack, which provides a core avenue for its high-power supply security

PREDICTIVE CONTROL OF POWER GRID-CONNECTED ENERGY SYSTEMS BASED ON ENERGY AND EXERGY METRICS

Building and transportation sectors account for 41% and 27% of total energy consumption in the US, respectively. Designing smart controllers for Heating, Ventilation and Air-Conditioning (HVAC) systems and Internal Combustion Engines (ICEs) can play a key role in reducing energy consumption. Exergy or availability is based on the First and Second Laws of Thermodynamics and is a more precise metric to evaluate energy systems including HVAC and ICE systems. This dissertation centers on development of exergy models and design of model-based controllers based on exergy and energy metrics for grid-connected energy systems including HVAC and ICEs. In this PhD dissertation, effectiveness of smart controllers such as Model Predictive Controller (MPC) for HVAC system in reducing energy consumption in buildings has been shown. Given the unknown and varying behavior of buildings parameters, this dissertation proposes a modeling framework for online estimation of states and unknown parameters. This method leads to a Parameter Adaptive Building (PAB) model which is used for MPC. Exergy destruction/loss in a system or process indicates the loss of work potential. In this dissertation, exergy destruction is formulated as the cost function for MPC problem. Compared to RBC, exergy-based MPC achieve 22% reduction in exergy destruction and 36% reduction in electrical energy consumption by HVAC system. In addition, the results show that exergy-based MPC outperforms energy-based MPC by 12% less energy consumption. Furthermore, the similar exergy-based approach for building is developed to control ICE operation. A detailed ICE exergy model is developed for a single cylinder engine. Then, an optimal control method based on the exergy model of the ICE is introduced for transient and steady state operations of the ICE. The proposed exergy-based controller can be applied for two applications including (i) automotive (ii) Combined Heat and Power (CHP) systems to produce electric power and thermal energy for heating purposes in buildings. The results show that using the exergy-based optimal control strategy leads to an average of 6.7% fuel saving and 8.3% exergy saving compared to commonly used FLT based combustion control. After developing thermal and exergy models for building and ICE testbeds, a framework is proposed for bilevel optimization in a system of commercial buildings integrated to smart distribution grid. The proposed framework optimizes the operation of both entities involved in the building-to-grid (B2G) integration. The framework achieves two objectives: (i) increases load penetration by maximizing the distribution system load factor and (ii) reduces energy cost for the buildings. The results show that this framework reduces commercial buildings electricity cost by 25% compared to the unoptimized case, while improving the system load factor up to 17%

A Comprehensive Survey on Different Control Strategies and Applications of Active Power Filters for Power Quality Improvement

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Power quality (PQ) has become an important topic in today’s power system scenario. PQ issues are raised not only in normal three-phase systems but also with the incorporation of different distributed generations (DGs), including renewable energy sources, storage systems, and other systems like diesel generators, fuel cells, etc. The prevalence of these issues comes from the non-linear features and rapid changing of power electronics devices, such as switch-mode converters for adjustable speed drives and diode or thyristor rectifiers. The wide use of these fast switching devices in the utility system leads to an increase in disturbances associated with harmonics and reactive power. The occurrence of PQ disturbances in turn creates several unwanted effects on the utility system. Therefore, many researchers are working on the enhancement of PQ using different custom power devices (CPDs). In this work, the authors highlight the significance of the PQ in the utility network, its effect, and its solution, using different CPDs, such as passive, active, and hybrid filters. Further, the authors point out several compensation strategies, including reference signal generation and gating signal strategies. In addition, this paper also presents the role of the active power filter (APF) in different DG systems. Some technical and economic considerations and future developments are also discussed in this literature. For easy reference, a volume of journals of more than 140 publications on this particular subject is reported. The effectiveness of this research work will boost researchers’ ability to select proper control methodology and compensation strategy for various applications of APFs for improving PQ.publishedVersio

ESSE 2017. Proceedings of the International Conference on Environmental Science and Sustainable Energy

Environmental science is an interdisciplinary academic field that integrates physical-, biological-, and information sciences to study and solve environmental problems. ESSE - The International Conference on Environmental Science and Sustainable Energy provides a platform for experts, professionals, and researchers to share updated information and stimulate the communication with each other. In 2017 it was held in Suzhou, China June 23-25, 2017