Real-time load-side control of electric power systems

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems.

(1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control.

(2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

Enhanced 3-Dimensional Carbon Nanotube Based Anodes for Li-ion Battery Applications

A prototype 3-dimensional (3D) anode, based on multiwall carbon nanotubes (MWCNTs), for Li-ion batteries (LIBs), with potential use in Electric Vehicles (EVs) was investigated. The unique 3D design of the anode allowed much higher areal mass density of MWCNTs as active materials, resulting in more amount of Li+ ion intake, compared to that of a conventional 2D counterpart. Furthermore, 3D amorphous Si/MWCNTs hybrid structure offered enhancement in electrochemical response (specific capacity 549 mAhg-1). Also, an anode stack was fabricated to further increase the areal or volumetric mass density of MWCNTs. An areal mass density of the anode stack 34.9 mg/cm2 was attained, which is 1,342% higher than the value for a single layer 2.6 mg/cm2. Furthermore, the binder-assisted and hot-pressed anode stack yielded the average reversible, stable gravimetric and volumetric specific capacities of 213 mAhg-1 and 265 mAh/cm3, respectively (at 0.5C). Moreover, a large-scale patterned novel flexible 3D MWCNTs-graphene-polyethylene terephthalate (PET) anode structure was prepared. It generated a reversible specific capacity of 153 mAhg-1 at 0.17C and cycling stability of 130 mAhg-1 up to 50 cycles at 1.7C.

Optimal bidding strategies of an electric vehicle aggregator in an electricity market

In recent years Electric Vehicles (EVs) are getting more importance as future transport systems, due to the increase of the concerns relevant to the greenhouse gases emission and the use fossil fuel. The management of the charging and discharging process of EVs could provide new business model for participating in the electricity markets. Moreover, vehicle to grid systems have the potential of increasing utility system flexibility. This thesis develops some models for the optimal integration of the EVs in the electricity market. In particular, the thesis focuses on the optimal bidding strategy of an EV aggregator participating to both the day ahead market and the secondary reserve market. The aggregator profit is maximized taking into account the energy balance equation, as well as the technical constraints of energy settlement, power supply and state of charge of the EVs. The results obtained by using the GAMS (General Algebraic Modelling System) environment are presented and discussed.

Virtual Calibration of CO2 and Pollutant Emissions of a High-Performance PHEV using Model-in-the-Loop Methodology

The study analyses the calibration process of a newly developed high-performance plug-in hybrid electric passenger car powertrain. The complexity of modern powertrains and the more and more restrictive regulations regarding pollutant emissions are the primary challenges for the calibration of a vehicle’s powertrain. In addition, the managers of OEM need to know as earlier as possible if the vehicle under development will meet the target technical features (emission included). This leads to the necessity for advanced calibration methodologies, in order to keep the development of the powertrain robust, time and cost effective. The suggested solution is the virtual calibration, that allows the tuning of control functions of a powertrain before having it built. The aim of this study is to calibrate virtually the hybrid control unit functions in order to optimize the pollutant emissions and the fuel consumption. Starting from the model of the conventional vehicle, the powertrain is then hybridized and integrated with emissions and aftertreatments models. After its validation, the hybrid control unit strategies are optimized using the Model-in-the-Loop testing methodology. The calibration activities will proceed thanks to the implementation of a Hardware-in-the-Loop environment, that will allow to test and calibrate the Engine and Transmission control units effectively, besides in a time and cost saving manner.

Design of mobility infrastructures to promote sustainability and accessibility of urban areas

This doctoral dissertation represents a cluster of research activities carried out at the DICAM Department of the University of Bologna during a three-year Ph.D. course. The goal of this research is to show how the development of an interconnected infrastructure network, aimed at promoting accessibility and sustainability of places, is fundamental in a framework of deep urban regeneration. Sustainable urban mobility plays an important role in improving the quality of life of citizens. From an environmental point of view, a sustainable mobility system means reducing fuel discharges and energy waste and, in general, aims to promote low carbon emissions. At the same time, a socially and economically sustainable mobility system should be accessible to everybody and create more job opportunities through better connectivity and mobility. Environmentally friendly means of transport such as non-motorized transport, electric vehicles, and hybrid vehicles play an important role in achieving sustainability but require a planned approach at the local policy level. The aim of this study is to demonstrate that, through a targeted reconnection of road and cycle-pedestrian routes, the quality of life of an urban area subject to degradation can be significantly improved just by increasing its accessibility and sustainability. Starting from a detailed study of the European policies and from the comparison with real similar cases, the case study of the Canal Port of Rimini (Italy) has been analysed within the European project FRAMESPORT. The analysis allowed the elaboration of a multicriterial methodology to get to the definition of a project proposal and of a priority scale of interventions. The applied methodology is a valuable tool that may be used in the future in similar urban contexts. Finally, the whole project was represented by using virtual reality to visually show the difference between the before and after the regeneration intervention.

Power flow forecasting and smart charging for electric vehicle charging systems with photovoltaic integration

An essential role in the global energy transition is attributed to Electric Vehicles (EVs) the energy for EV traction can be generated by renewable energy sources (RES), also at a local level through distributed power plants, such as photovoltaic (PV) systems. However, EV integration with electrical systems might not be straightforward. The intermittent RES, combined with the high and uncontrolled aggregate EV charging, require an evolution toward new planning and paradigms of energy systems. In this context, this work aims to provide a practical solution for EV charging integration in electrical systems with RES. A method for predicting the power required by an EV fleet at the charging hub (CH) is developed in this thesis. The proposed forecasting method considers the main parameters on which charging demand depends. The results of the EV charging forecasting method are deeply analyzed under different scenarios. To reduce the EV load intermittency, methods for managing the charging power of EVs are proposed. The main target was to provide Charging Management Systems (CMS) that modulate EV charging to optimize specific performance indicators such as system self-consumption, peak load reduction, and PV exploitation. Controlling the EV charging power to achieve specific optimization goals is also known as Smart Charging (SC). The proposed techniques are applied to real-world scenarios demonstrating performance improvements in using SC strategies. A viable alternative to maximize integration with intermittent RES generation is the integration of energy storage. Battery Energy Storage Systems (BESS) may be a buffer between peak load and RES production. A sizing algorithm for PV+BESS integration in EV charging hubs is provided. The sizing optimization aims to optimize the system's energy and economic performance. The results provide an overview of the optimal size that the PV+BESS plant should have to improve whole system performance in different scenarios.

Enhancing the reliability of electric transportation motors through insulation coordination and improved qualification

The ambitious goals of increasing the efficiency, performance and power densities of transportation drives cannot be met with compromises in the motor reliability. For the insulation specialists the challenge will be critical as the use of wide-bandgap converters (WBG, based on SiC and GaN switches) and the higher operating voltages expected for the next generation drives will enhance the electrical stresses to unprecedented levels. It is expected for the DC bus in aircrafts to reach 800 V (split +/-400 V) and beyond, driven by the urban air mobility sector and the need for electrification of electro-mechanical/electro-hydraulic actuators (an essential part of the "More Electric Aircraft" concept). Simultaneously the DC bus in electric vehicles (EV) traction motors is anticipated to increase up to 1200 V very soon. The electrical insulation system is one of the most delicate part of the machine in terms of failure probability. In particular, the appearance of partial discharges (PD) is disruptive on the reliability of the drive, especially under fast repetitive transients. Extensive experimental activity has been performed to extend the body of knowledge on PD inception, endurance under PD activity, and explore and identify new phenomena undermining the reliability. The focus has been concentrated on the impact of the WGB-converter produced waveforms and the environmental conditions typical of the aeronautical sector on insulation models. Particular effort was put in the analysis at the reduced pressures typical of aircraft cruise altitude operation. The results obtained, after a critical discussion, have been used to suggest a coordination between the insulation PD inception voltage with the converter stresses and to propose an improved qualification procedure based on the existing IEC 60034-18-41 standard.

O impacto energético e as emissões de CO2 dos veículos eléctricos em Portugal

Para a diminuição da dependência energética de Portugal face às importações de energia, a Estratégia Nacional para a Energia 2020 (ENE 2020) define uma aposta na produção de energia a partir de fontes renováveis, na promoção da eficiência energética tanto nos edifícios como nos transportes com vista a reduzir as emissões de gases com efeito de estufa. No campo da eficiência energética, o ENE 2020 pretende obter uma poupança energética de 9,8% face a valores de 2008, traduzindo-se em perto de 1800 milhões de tep já em 2015. Uma das medidas passa pela aposta na mobilidade eléctrica, onde se prevê que os veículos eléctricos possam contribuir significativamente para a redução do consumo de combustível e por conseguinte, para a redução das emissões de CO2 para a atmosfera. No entanto, esta redução está condicionada pelas fontes de energia utilizadas para o abastecimento das baterias. Neste estudo foram determinados os consumos de combustível e as emissões de CO2 de um veículo de combustão interna adimensional representativo do parque automóvel. É também estimada a previsão de crescimento do parque automóvel num cenário "Business-as-Usual", através dos métodos de previsão tecnológica para o horizonte 2010-2030, bem como cenários de penetração de veículos eléctricos para o mesmo período com base no método de Fisher- Pry. É ainda analisado o impacto que a introdução dos veículos eléctricos tem ao nível dos consumos de combustível, das emissões de dióxido de carbono e qual o impacto que tal medida terá na rede eléctrica, nomeadamente no diagrama de carga e no nível de emissões de CO2 do Sistema Electroprodutor Nacional. Por fim, é avaliado o impacto dos veículos eléctricos no diagrama de carga diário português, com base em vários perfis de carga das baterias. A introdução de veículos eléctricos em Portugal terá pouca expressão dado que, no melhor dos cenários haverão somente cerca de 85 mil unidades em circulação, no ano de 2030. Ao nível do consumo de combustíveis rodoviários, os veículos eléctricos poderão vir a reduzir o consumo de gasolina até 0,52% e até 0,27% no consumo de diesel, entre 2010 e 2030, contribuindo ligeiramente uma menor dependência energética externa. Ao nível do consumo eléctrico, o abastecimento das baterias dos veículos eléctricos representará até 0,5% do consumo eléctrico total, sendo que parte desse abastecimento será garantido através de centrais de ciclo combinado a gás natural. Apesar da maior utilização deste tipo de centrais térmicas para produção de energia, tanto para abastecimento das viaturas eléctricas, como para o consumo em geral, verifica-se que em 2030, o nível de emissões do sistema electroprodutor será cerca de 46% inferior aos níveis registados em 2010, prevendo-se que atinja as 0,163gCO2/kWh produzido pelo Sistema Electroprodutor Nacional devido à maior quota de produção das fontes de energia renovável, como o vento, a hídrica ou a solar.

Impacto da integração dos veículos eléctricos nos edifícios multi-habitacionais, nas redes de distribuição de baixa tensão e no diagrama de carga nacional

Associado à escassez dos combustíveis fósseis e ao desejado controlo de emissões nocivas para a atmosfera, assistimos no mundo ao desenvolvimento do um novo paradigma — a mobilidade eléctrica. Apesar das variações de maior ou menor arbítrio político dos governos, do excelente ou débil desenvolvimento tecnológico, relacionados com os veículos eléctricos, estamos perante um caminho, no que diz respeito à mobilidade eléctrica, que já não deve ser encarado como uma moda mas como uma orientação para o futuro da mobilidade. Portugal tendo dado mostras que pretende estar na dianteira deste desafio, necessita equacionar e compreender em que condições existirá uma infra-estrutura nacional capaz de fazer o veículo eléctrico vingar. Assim, neste trabalho, analisa-se o impacto da mobilidade eléctrica em algumas dessas infra-estruturas, nomeadamente nos edifícios multi-habitacionais e redes de distribuição em baixa tensão. São criados neste âmbito, quatro perfis de carregamento dos EVs nomeadamente: nas horas de chegada a casa; nas horas de vazio com início programado pelo condutor; nas horas de vazio controlado por operador de rede (“Smart Grid”); e um cenário que contempla a utilização do V2G. Com a obrigação legal de nos novos edifícios serem instaladas tomadas para veículos eléctricos, é estudado, com os cenários anteriores a possibilidade de continuar a conceber as instalações eléctricas, sem alterar algumas das disposições legais, ao abrigo dos regulamentos existentes. É também estudado, com os cenários criados e com a previsão da venda de veículos eléctricos até 2020, o impacto deste novo consumo no diagrama de carga do Sistema Eléctrico Nacional. Mostra-se assim que a introdução de sistemas inteligentes de distribuição de energia [Smartgrid e vehicle to grid” (V2G)] deverá ser encarada como a solução que por excelência contribuirá para um aproveitamento das infra-estruturas existentes e simultaneamente um uso acessível para os veículos eléctricos.

Desenvolvimento do sistema de tracção de um veículo eléctrico ecológico com travagem regenerativa

Nesta dissertação descreve-se uma metodologia de dimensionamento do sistema de tracção para equipar um veículo eléctrico ecológico (VEECO) com inclusão de um sistema de travagem regenerativa. Apresenta-se uma perspectiva geral de diversas topologias de sistemas de tracção utilizadas nos veículos eléctricos e realiza-se a sua comparação através do estudo e análise dos acionamentos electromecânicos que podem ser utilizados nesses sistemas de tracção eléctrica. Utilizando ferramentas de simulação numérica, estuda-se o modelo matemático de um veículo eléctrico com travagem regenerativa. A partir deste modelo matemático é adoptado uma possível configuração para o seu sistema de tracção eléctrica e são obtidas características teóricas de desempenho do veículo eléctrico, através da análise de testes padrão ao veículo. Em banco de ensaios, constrói-se um sistema de tracção eléctrica que permite a validação experimental do modelo matemático do veículo eléctrico. Para a construção deste banco de ensaios foram concebidos os sistemas de tracção eléctrica, de carga mecânica e de controlo e monitorização do banco de ensaios. A validação experimental realiza-se através dos mesmos testes padrão ao veículo eléctrico, como o teste NEDC (New European Driving Cycle), o teste de aceleração entre 0 e 100km/h e o teste de gradeabilidade. Desenvolve-se o dimensionamento do sistema de tracção eléctrica a equipar o VEECO, através da componente de modelação paramétrica do modelo matemático do veículo eléctrico. Com esta metodologia é adoptado um conjunto de variáveis paramétricas relacionadas com os elementos que constituem o sistema de tracção eléctrica do VEECO. Estuda-se a influência destas variáveis paramétricas nas características de desempenho pretendidas para o VEECO. Como resultado da análise de modelação paramétrica é apresentada uma solução para o sistema de tracção eléctrica do VEECO que cumpre a execução do NEDC, apresenta um tempo de aceleração entre 0 e 100km/h inferior a 10 segundos, supera uma gradeabilidade de 10% e uma autonomia de 200 km. O sistema de tracção do VEECO também permite realizar a travagem regenerativa com rendimento até 33%. Possui controlo de tracção e anti bloqueio da roda motora, através de uma unidade de controlo que permite reduzir a potência transmitida ao veio, quando a velocidade da roda de tracção difere do valor de referência da velocidade do veículo. Os conhecimentos adquiridos através do processo de investigação e desenvolvimento, para a realização da presente dissertação permitem apresentar perspectivas de desenvolvimento futuro com aplicação nos sistemas de tracção de veículos eléctricos rodoviários.

Real-time energy resources scheduling considering intensive wind penetration

The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.