The world is facing many problems, including limited natural resources as well as environmental and energy problems. Climate change is a fact and has a negative impact on several areas. The development of society has created the need for secure and reliable energy systems. Therefore, energy production must keep up with recent developments while limiting negative environmental impact. Although the sharp increase of renewable energy sources connecting to electrical networks creates stress on energy systems. Maintaining the standard of living and achieving sustainable energy production requires a significant increase in the efficiency of energy use. In addition, the fact that there are presently an abundance of effective ways to store electricity means, and requires, that the production, as well as consumption, of power are kept in balance at all times. One of the basic operating forces regarding the Smart Grid is to balance energy consumption in the best way possible. The intelligent networks method is also advantageous for the environment as well as the consumers and producers of electricity. Although the broad sense of the Smart Grid includes the whole power system, ranging from power generation, transmission and distribution infrastructure to all categories of consumers (domestic, commercial and industrial). Smart Grids are also techniques that enable improved business continuity, increased connectivity and also helps to improve the efficiency of the corporate network, and indirectly reduce costs for consumers. Further measures in this area include power supply and system maintenance as well as information and communication technology. This study will provide knowledge and understanding in addition to contributing ideas on how to improve the wind power plants and the electricity grid through the use of Smart Grids. The analysis is also a way to convey an overall impression of how the Smart Grid works as well as summarizing the general requirements in order to achieve the best possible performance.

The concept of the smart grid has been proposed to modernize the power grid with efficient and comprehensive monitoring systems as well as autonomous and self-healing technologies. Demand response (DR) and demand side management (DSM) are two aspects of the smart grid. The first is used to control the demand and supply, and the peak-to-average ratio (PAR) of a distribution network, and the second is used to manage a site's energy consumption efficiently. This thesis focuses on reducing the need for importing extra electricity from resources outside the local distribution network using DR, DSM. First, a demand management model is described to optimize customer energy usage and consider their comfort within a sequential optimization model. A multi-layer and multi-objective optimization system is proposed at the energy consumption level to consider customer comfort and experience. The cluster-based sequential management approach is presented to improve customer comfort via appliance scheduling. To quantify thermal comfort, a thermodynamic solution is used for the heating ventilation, and air conditioning (HVAC) system to schedule thermal load and eliminate customer inconvenience on room temperature. Customer inconvenience refers to a condition that the use of an appliance does not meet the preferences of the customer. Moreover, the satisfaction of electric vehicle charging, constrained by minimum cost, and the preferred usage time for the non-interruptible deferrable loads are considered in this model. Due to the uncertain demand profile of users, stochastic solutions for demand response problems enable utility companies to address the uncertainties in the customers' energy consumption. A stochastic DR approach is presented between an aggregator and residential customers during peak load periods, and the optimal outputs of customers and aggregator are determined. This probabilistic demand response management model uses a mixed-strategy Stackelberg game to maximize the profit of total energy reduction for the aggregator and to maximize the reward of demand reduction for customers. The proposed solution reduces the demand, PAR, and the overall energy costs for both customers and the grid while maintaining customer comfort. To perform a secure and robust energy trading model with high scalable decentralized supervision, a mixed-strategy stochastic game model is integrated with energy blockchain to address uncertainties in DR contributions. This model utilizes the processing hardware of customers for block mining, stores customer DR agreements as distributed ledgers, and offers a smart contract and consensus algorithm for energy transaction validation. A novel consensus algorithm compatible with a DR problem is presented to incentivize customers to contribute to DR events and collaborate in block mining to gain monetary profits. The results demonstrate the security and robustness of the consensus algorithm for detecting malicious activities. In summary, this thesis proposes schemes that control grid demand and minimize energy usage while preserving user comfort, security, and economic fairness.

There is an international effort to develop smart grids to overcome the problems caused by aging power grids. However, to immigrate to the new grid, the IT infrastructure has to be integrated with the current power grid. There is currently an ongoing debate surrounding what would be the best choice for smart grid communication technology. One of the promising communication technologies for smart grid realization is powerline communication (PLC). PLC provides utilities the opportunity of managing their own network infrastructure. Power cables are everywhere; even rural areas are covered with power cables. However, because of its noisy environment and the low capacity of narrowband powerline communication (NBPLC), its viability for smart grid realization is being questioned. To investigate this issue, smart grid communication network requirements and powerline communication technologies and channel models are studied. Then, using MATLAB and Network Simulator-2, powerline communication and a smart grid communication network (SGCN) are simulated. The performance of different powerline channels for smart grid realization is investigated and a viable PLC infrastructure for smart grid communication network is proposed. Furthermore, to have a better understanding of the viability of powerline communication for the smart grid, some future smart grid advanced applications are investigated and integrated to the system. It is shown that although two types of powerline channels do not perform well, the proposed powerline communication infrastructure, even under advanced traffic, is capable of providing the smart grid with its communication prerequisites. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2012-04-30 15:31:43.471

El desarrollo de la presente investigación, tiene como objetivo en determinar de qué manera influye el Smart Grid en la reducción de costos de energía eléctrica, particularmente en el sistema de distribución, de la Unidad Minera Julcani, Huancavelica 2017, cabe mencionar que dicho estudio fue de tipo descriptivo, explicativo, bajo el diseño no experimental, de corte transversal, lo cual se realizó procedimiento de recolección de información contando con una población y a la vez el mismo tamaño de muestra de 24 oficinas administrativas de la Unidad Minera Julcani, por estar en constante actividad en cuanto a su consumo de energía eléctrica,

A Smart Grid is a digitally enabled electric power grid that integrates the computation and communication technologies from cyber world with the sensors and actuators from physical world. Due to the system complexity, typically the high cohesion of communication and power system, the Smart Grid innovation introduces new and fundamentally different security vulnerabilities and risks. In this work, two important research aspects about cyber-physical security of Smart Grid are addressed: (i) The construction, impact and countermeasure of data integrity attacks; and (ii) The design and implementation of general cyber-physical security experiment platform. For data integrity attacks: based on the system model of state estimation process in Smart Grid, firstly, a data integrity attack model is formulated, such that the attackers can generate financial benefits from the real-time electrical market operations. Then, to reduce the required knowledge about the targeted power system when launching attacks, an online attack approach is proposed, such that the attacker is able to construct the desired attacks without the network information of power system. Furthermore, a network information attacking strategy is proposed, in which the most vulnerable meters can be directly identified and the desired measurement perturbations can be achieved by strategically manipulating the network information. Besides the attacking strategies, corresponding countermeasures based on the sparsity of attack vectors and robust state estimator are provided respectively. For the experiment platform: ScorePlus, a software-hardware hybrid and federated experiment environment for Smart Grid is presented. ScorePlus incorporates both software emulator and hardware testbed, such that they all follow the same architecture, and the same Smart Grid application program can be tested on either of them without any modification; ScorePlus provides a federated environment such that multiple software emulators and hardware testbeds at different locations are able to connect and form a unified Smart Grid system; ScorePlus software is encapsulated as a resource plugin in OpenStack cloud computing platform, such that it supports massive deployments with large scale test cases in cloud infrastructure.

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Due to recent concerns regarding energy conservation and dependence on fossil fuels, the efficient integration of electric vehicle populations’ in the future smart grid has become a significant area of research. Despite the heavy penetration of smart meters throughout North America and Europe a lack of research exists utilizing real consumption data. Making use of smart meter data, a model of a prototypical residential feeder was created to observe the effects of increased electric vehicle penetration on the selected feeder. Simulations of the current operation of the feeder were performed along with modeled uncoordinated, coordinated, and coordinated vehicle to grid charging of electric vehicles. As expected, it was found that the normal operation of the feeder is subject to several inefficiencies which are made worse by uncoordinated charging of electric vehicles. Significant improvements in the considered operational parameters were found as a result of the coordinated charging of vehicles using a quadratic programming based control algorithm. Further it was found, that the use of coordinated vehicle to grid connections only produces marginal benefits over standard connections. Leading to the conclusion that development of charging controls is more significant to the mitigation of electric vehicle charging effects than the integration of vehicle to grid connections. / Thesis (Master, Physics, Engineering Physics and Astronomy) -- Queen's University, 2014-01-31 16:02:37.201

Smart grid is about integration of distributed energy resources (DERs) into the energy systems, especially electricity grid. DERs include renewable energy resources such as wind and solar, energy storages such as electrical and thermal energy storage, demand response programs, smart homes, and electric vehicles with their charging stations. DERs have significant advantages such as reduction of operation costs, emission, and peak as well as the increase of reliability, resiliency, stability, and voltage profile in smart grids. They also prevent establishment of fossil fuel power plants and expansion of transmission lines by locating in electricity distribution grid and transmission lines. The advantages approve the financial, technical, and environmental effects of the DERs in smart grids. An operation/planning approach such as EHs/IEHs is required to utilization of DERs in the Smart Grid. EH is a super node in electricity power system which connects different energy networks such as gas, electricity, heating, or cooling. The EH can be developed by DERs for operation and planning purposes. The EHs can be located in different parts of the energy networks to form IEHs. Despite the significant advantages of utilization of DERs in EHs of Smart Grids, they should be utilized by information and communication technologies (ICTs), which results in Cyber-Physical Power Systems (CPPSs) vulnerable to different cyberattacks. The vulnerability of DERs in EHs of Smart Grid leads to jeopardizing the reliability, stability, and resiliency of power systems since integrity, confidentiality, or availability cyberattacks might bypass the detection systems to take control of DERs for malicious purposes such as congestion, cascading failure, blackout, undervoltage/overvoltage, or costs. In this research, some cyberattacks are modeled on DERs in EHs and IEHs of Smart Grid, and the vulnerabilities of DERs to the cyberattacks in the developed EHs/IEs are approved: First, an integrity cyberattack is modeled and applied to the DR program (time/incentive-based) in the developed EH in electricity distribution grid in order to control the performance of the EH and its negative effects on the grid. The attacker aims to manipulate the system by both raising peak demand and lowering customers' energy bills simultaneously. This strategy is designed to deceive customers into participating in falsified Demand Response (DR) programs, ultimately leading to an increase in the overall peak demands of the system which jeopardizes the reliability of the system. Second, an integrity FDI cyberattack is modeled and applied on the developed IEHs in transmission lines in order to control the performance of the IEH and its negative effects on the transmission lines. This cyberattack is modeled to manipulate the transmission lines energy demands in order to threaten reliability and stability of the system by bypassing detection systems. Finally, the attacker targets the developed EHs integrated by DERs by maximizing the costs associated with operation, emission, and energy not supplied costs. The attacker objective is to adversely affect the financial, technical, and environmental advantages of integration of DERs to the system. Hence, powerful remedial actions are required to alleviate the adverse effects of DERs, manipulated by attackers, in the developed EHs. Therefore, a remedial action is designed by min-max formulation in order to mitigate the adverse effects of DERs on financial, technical, and environmental terms. The remedial action reduces the imposed costs by changing the status of EH devices. The results highlight the role of DERs in reducing costs and emphasize the need for their proactive security measures in cyber-physical power systems.

Buildings account for approximately 40% of the energy demand and 33% of the total greenhouse gas emissions in the European Union. Accordingly, there are several efforts that target energy efficiency in buildings both at the European and Swedish levels. The role of buildings in climate change mitigation, however, is not limited to energy savings. Buildings are expected to become key elements of the future smart energy systems by supplying and using energy in a more flexible way. Reducing the energy demand in buildings effectively and shifting the role of buildings in energy systems from ‘passive’ consumers to ‘active’ prosumers, however, require close interaction and cooperation between the energy and buildings sectors. Based on the data collected from interviews and a web survey, this doctoral thesis investigates the relationship between the energy and buildings sectors in Sweden at the inter-company level, presents key stakeholder views on smart energy features in buildings and investigates the opportunities and barriers for their adoption in Sweden and Hong Kong. The results of this thesis suggest a potential for improving the cooperation between the Swedish energy and buildings sectors, which was identified to be influenced by the following factors: district heating monopolies; energy efficiency efforts in the buildings sector; unsuccessful technology-neutrality of the building regulations; self-generation systems in buildings; and energy use patterns. Shifting the focus from self-gains to mutual gains appears crucial to strengthen the inter-sectoral cooperation, as there are several opportunities for achieving mutually beneficial solutions for the two sectors. This would, however, require significant changes in current practices and business models as well as the introduction of new technologies, which would allow for a more flexible energy supply and use. Accordingly, technologies that target flexible energy use in buildings are considered the most important smart energy features in buildings. The current high costs of technologies, such as home automation and smart electrical appliances, however, create the strongest barrier to adoption. Therefore, the introduction of new business and ownership models and the elimination of the institutional and regulatory barriers are crucial to achieve a wide-scale development of smart energy features in buildings. The results from Hong Kong suggest that institutional and regulatory barriers can particularly create strong hinders to the adoption of technologies. It is possible to achieve more sustainable energy systems, where buildings are active elements of networks that supply and use energy in a more flexible and ‘smarter’ way. Cooperation between the energy and buildings sectors can play a key role in the adoption of smart energy features in buildings and pave the way for the smart built environment of the future.

Master of Science / Department of Electrical and Computer Engineering / Anil Pahwa / This research project builds upon previous work related to intelligent and energy efficient lighting in modern street and outdoor lighting systems. The concept of implementing modern smart grid technologies such as the proposed Street & Outdoor Lighting Intelligent Monitoring System (SOLIMS) is developed. A random sample of photocells from two municipal electric power systems is used to collect data of the actual on/off times of random photocells versus Civil Twilight (sunrise/sunset) times. A business case was developed using the data collected from the observations to support an electric utility company’s implementation of SOLIMS as an alternative to current operations. The goal of the business case is to demonstrate energy and capacity savings, reduced maintenance and operating costs, and lower carbon emissions.