181 research outputs found

    Mobile Power Network for Ultimate Mobility without Battery Life Anxiety

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    Similar to the evolution from the wired Internet to mobile Internet (MI), the growing demand for power delivery anywhere and anytime appeals for power grid transformation from wired to mobile domain. We propose here the next generation of power delivery network -- mobile power network (MPN) for wireless power transfer within a mobile range from several meters to tens of meters. At first, we present the MPN's concept evolution and application scenarios. Then, we introduce the MPN's supporting technology, namely resonant beam charging (RBC). As a long-range wireless power transfer (WPT) method, RBC can safely deliver multi-Watt power to multiple devices concurrently. Meanwhile, the recent progress in RBC research has been summarized. Next, we specify the MPN's architecture to provide the wide-area WPT coverage. Finally, we discuss the MPN's features and challenges. MPN can enable the ultimate mobility by cutting the final cord of mobile devices, realizing the "last-mile" mobile power delivery.Comment: 10 pages, 5 figure

    Hierarchical and Distributed Architecture for Large-Scale Residential Demand Response Management

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    The implementation of smart grid brings several challenges to the power system. The ‘prosumer’ concept, proposed by the smart grid, allows small-scale ‘nano-grids’ to buy or sell electric power at their own discretion. One major problem in integrating prosumers is that they tend to follow the same pattern of generation and consumption, which is un-optimal for grid operations. One tool to optimize grid operations is demand response (DR). DR attempts to optimize by altering the power consumption patterns. DR is an integrated tool of the smart grid. FERC Order No. 2222 caters for distributed energy resources, including demand response resources, in participating in energy markets. However, DR contribution of an average residential energy consumer is insignificant. Most residential energy consumers pay a flat price for their energy usage and the established market for residential DR is quite small. In this dissertation, a survey is carried out on the current state-of-the-art in DR research and generalizations of the mathematical models are made. Additionally, a service provider model is developed along with an incentive program and user interfaces (UI). These UIs and incentive program are designed to be attractive and easily comprehended by a large customer base. Furthermore, customer behavior models are developed that characterize the potential customer base, allowing a demand response aggregator to understand and quantify the quality of the customer. Optimization methods for DR management with various characteristics are also explored in this dissertation. Moreover, A scalable demand response management framework that can incorporate millions of participants in the program is introduced. The framework is based on a hierarchical architecture. To improve DR management, hierarchical load forecasting method is studied. Specifically, optimal combination method for hierarchical forecast reconciliation is applied to the DR program. It is shown that the optimal combination for reconciliation of hierarchical predictions could reduce the stress levels of the consumer close to the ideal values for all scenarios

    A Game-theoretic Model for Regulating Freeriding in Subsidy-Based Pervasive Spectrum Sharing Markets

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    Cellular spectrum is a limited natural resource becoming scarcer at a worrisome rate. To satisfy users\u27 expectation from wireless data services, researchers and practitioners recognized the necessity of more utilization and pervasive sharing of the spectrum. Though scarce, spectrum is underutilized in some areas or within certain operating hours due to the lack of appropriate regulatory policies, static allocation and emerging business challenges. Thus, finding ways to improve the utilization of this resource to make sharing more pervasive is of great importance. There already exists a number of solutions to increase spectrum utilization via increased sharing. Dynamic Spectrum Access (DSA) enables a cellular operator to participate in spectrum sharing in many ways, such as geological database and cognitive radios, but these systems perform spectrum sharing at the secondary level (i.e., the bands are shared if and only if the primary/licensed user is idle) and it is questionable if they will be sufficient to meet the future expectations of the spectral efficiency. Along with the secondary sharing, spectrum sharing among primary users is emerging as a new domain of future mode of pervasive sharing. We call this type of spectrum sharing among primary users as pervasive spectrum sharing (PSS) . However, such spectrum sharing among primary users requires strong incentives to share and ensuring a freeriding-free cellular market. Freeriding in pervasively shared spectrum markets (be it via government subsidies/regulations or self-motivated coalitions among cellular operators) is a real techno-economic challenge to be addressed. In a PSS market, operators will share their resources with primary users of other operators and may sometimes have to block their own primary users in order to attain sharing goals. Small operators with lower quality service may freeride on large operators\u27 infrastructure in such pervasively shared markets. Even worse, since small operators\u27 users may perceive higher-than-expected service quality for a lower fee, this can cause customer loss to the large operators and motivate small operators to continue freeriding with additional earnings from the stolen customers. Thus, freeriding can drive a shared spectrum market to an unhealthy and unstable equilibrium. In this work, we model the freeriding by small operators in shared spectrum markets via a game-theoretic framework. We focus on a performance-based government incentivize scheme and aim to minimize the freeriding issue emerging in such PSS markets. We present insights from the model and discuss policy and regulatory challenges

    Implementation of second-life batteries as energy storage systems enhancing the interoperability and flexibility of the energy infrastructure in tertiary buildings

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    The main focus of this project is to evaluate the implementation of second-life batteries for a building stock enabling the energy flexibility schemes like Demand Response (DR). This project will focus particularly on how the building stock and its energy infrastructure (energy storage systems, legacy-assets, communication devices and grid architecture, among others) can participate as innovative energy solutions of the next generation of smart-grids, acting as virtual power plants (VPP) in order to deploy the distributed generation (DG) concept in the actual energy field and paving the way to unlock the demand response (DR) market in the distribution energy network. In addition, the implementation of these technologies will led to plan different business models and the scalability of them in the tertiary building sector. Battery energy storage systems (BESSs) are already being deployed for several stationary applications in a techno-economical feasible way. This project focuses in the study to obtain potential revenues from BESSs built from EVs lithium-ion batteries with varying states of health (SoH). For this analysis, a stationary BESS sizing model is done, using the parameters of a 14 kWh new battery, but also doing a comparison with parameters if the same battery would be 11.2 kWh second-life battery. The comprehensive sizing model consists of several detailed sub-models, considering battery specifications, aging and an operational strategy plan, which allow a technical assessment through a determined time frame. Therefore, battery depreciation and energy losses are considered in this techno-economic analysis. Potential economical feasible applications of new and second-life batteries, such the integration of a Building Integrated Photovoltaics (BIPV), self-consumption schemes, feed-in-tariff schemes and frequency regulation as well as their combined operation are compared. The research includes different electricity price scenarios mostly from the current Spanish energy market. The operation and integration of ICT-IoT technology upgrades is found to have the highest economic viability for this specific case study. A detailed study for this project will enhance the relevant importance of these topics in the energy field and how it will be a disruptive solution for the initial problem statement. A general context is given in order to introduce the main and specific objectives thus to trace an adequate way to follow and achieve them. The development of this master thesis will be coupled with the Demand Response Integration technologies (DRIvE) [10] H2020 EU funded project, currently on-going, considering some of the energy consumption data and initial parameters from the selected case study at COMSA Corporación office building in Barcelona, Spain

    Bidding strategy for a virtual power plant for trading energy in the wholesale electricity market

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    Virtual power plants (VPPs) are an effective way to increase renewable integration. In this PhD research, the concept design and the detailed costs and benefits of implementing a realistic VPP in Western Australia (WA), comprising 67 dwellings, are developed. The VPP is designed to integrate and coordinate an 810kW rooftop solar PV farm, 350kW/700kWh vanadium redox flow batteries (VRFB), heat pump hot water systems (HWSs), and smart appliances through demand management mechanisms. This research develops a robust bidding strategy for the VPP to participate in both load following ancillary service (LFAS) and energy market in the wholesale electricity market in WA considering the uncertainties associated with PV generation and electricity market prices. Using this strategy, the payback period can be improved by 3 years (to a payback period of 6 years) and the internal rate of return (IRR) by 7.5% (to an IRR of 18%) by participating in both markets. The daily average error of the proposed robust method is 2.7% over one year when compared with a robust mathematical method. The computational effort is 0.66 sec for 365 runs for the proposed method compared to 947.10 sec for the robust mathematical method. To engage customers in the demand management schemes by the VPP owner, the gamified approach is adopted to make the exercise enjoyable while not compromising their comfort levels. Seven gamified applications are examined using a developed methodology based on Kim’s model and Fogg’s model, and the most suitable one is determined. The simulation results show that gamification can improve the payback period by 1 to 2 months for the VPP owner. Furthermore, an efficient and fog-based monitoring and control platform is proposed for the VPP to be flexible, scalable, secure, and cost-effective to realise the full capabilities and profitability of the VPP
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