37 research outputs found

    Hybridizing Lead-Acid Batteries with Supercapacitors: A Methodology

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    Hybridizing a lead–acid battery energy storage system (ESS) with supercapacitors is a promising solution to cope with the increased battery degradation in standalone microgrids that suffer from irregular electricity profiles. There are many studies in the literature on such hybrid energy storage systems (HESS), usually examining the various hybridization aspects separately. This paper provides a holistic look at the design of an HESS. A new control scheme is proposed that applies power filtering to smooth out the battery profile, while strictly adhering to the supercapacitors’ voltage limits. A new lead–acid battery model is introduced, which accounts for the combined effects of a microcycle’s depth of discharge (DoD) and battery temperature, usually considered separately in the literature. Furthermore, a sensitivity analysis on the thermal parameters and an economic analysis were performed using a 90-day electricity profile from an actual DC microgrid in India to infer the hybridization benefit. The results show that the hybridization is beneficial mainly at poor thermal conditions and highlight the need for a battery degradation model that considers both the DoD effect with microcycle resolution and temperate impact to accurately assess the gain from such a hybridization

    Batteries and Supercapacitors Aging

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    Electrochemical energy storage is a key element of systems in a wide range of sectors, such as electro-mobility, portable devices, and renewable energy. The energy storage systems (ESSs) considered here are batteries, supercapacitors, and hybrid components such as lithium-ion capacitors. The durability of ESSs determines the total cost of ownership, the global impacts (lifecycle) on a large portion of these applications and, thus, their viability. Understanding ESS aging is a key to optimizing their design and usability in terms of their intended applications. Knowledge of ESS aging is also essential to improve their dependability (reliability, availability, maintainability, and safety). This Special Issue includes 12 research papers and 1 review article focusing on battery, supercapacitor, and hybrid capacitor aging

    Hibernus++: a self-calibrating and adaptive system for transiently-powered embedded devices

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    Energy harvesters are being used to power autonomous systems, but their output power is variable and intermittent. To sustain computation, these systems integrate batteries or supercapacitors to smooth out rapid changes in harvester output. Energy storage devices require time for charging and increase the size, mass and cost of systems. The field of transient computing moves away from this approach, by powering the system directly from the harvester output. To prevent an application from having to restart computation after a power outage, approaches such as Hibernus allow these systems to hibernate when supply failure is imminent. When the supply reaches the operating threshold, the last saved state is restored and the operation is continued from the point it was interrupted. This work proposes Hibernus++ to intelligently adapt the hibernate and restore thresholds in response to source dynamics and system load properties. Specifically, capabilities are built into the system to autonomously characterize the hardware platform and its performance during hibernation in order to set the hibernation threshold at a point which minimizes wasted energy and maximizes computation time. Similarly, the system auto-calibrates the restore threshold depending on the balance of energy supply and consumption in order to maximize computation time. Hibernus++ is validated both theoretically and experimentally on microcontroller hardware using both synthesized and real energy harvesters. Results show that Hibernus++ provides an average 16% reduction in energy consumption and an improvement of 17% in application execution time over stateof- the-art approaches

    Alternative Sources of Energy Modeling, Automation, Optimal Planning and Operation

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    An economic development model analyzes the adoption of alternative strategy capable of leveraging the economy, based essentially on RES. The combination of wind turbine, PV installation with new technology battery energy storage, DSM network and RES forecasting algorithms maximizes RES integration in isolated islands. An innovative model of power system (PS) imbalances is presented, which aims to capture various features of the stochastic behavior of imbalances and to reduce in average reserve requirements and PS risk. Deep learning techniques for medium-term wind speed and solar irradiance forecasting are presented, using for first time a specific cloud index. Scalability-replicability of the FLEXITRANSTORE technology innovations integrates hardware-software solutions in all areas of the transmission system and the wholesale markets, promoting increased RES. A deep learning and GIS approach are combined for the optimal positioning of wave energy converters. An innovative methodology to hybridize battery-based energy storage using supercapacitors for smoother power profile, a new control scheme and battery degradation mechanism and their economic viability are presented. An innovative module-level photovoltaic (PV) architecture in parallel configuration is introduced maximizing power extraction under partial shading. A new method for detecting demagnetization faults in axial flux permanent magnet synchronous wind generators is presented. The stochastic operating temperature (OT) optimization integrated with Markov Chain simulation ascertains a more accurate OT for guiding the coal gasification practice

    Energy Management

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    Forecasts point to a huge increase in energy demand over the next 25 years, with a direct and immediate impact on the exhaustion of fossil fuels, the increase in pollution levels and the global warming that will have significant consequences for all sectors of society. Irrespective of the likelihood of these predictions or what researchers in different scientific disciplines may believe or publicly say about how critical the energy situation may be on a world level, it is without doubt one of the great debates that has stirred up public interest in modern times. We should probably already be thinking about the design of a worldwide strategic plan for energy management across the planet. It would include measures to raise awareness, educate the different actors involved, develop policies, provide resources, prioritise actions and establish contingency plans. This process is complex and depends on political, social, economic and technological factors that are hard to take into account simultaneously. Then, before such a plan is formulated, studies such as those described in this book can serve to illustrate what Information and Communication Technologies have to offer in this sphere and, with luck, to create a reference to encourage investigators in the pursuit of new and better solutions

    Hybrid Energy Harvesting for Self Powered Human Applications

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    Continuing progress in reduction of size and power consumption of semiconductors, and significant improvement in their capability to compute sense and communicate data, have enabled a new area of wearable electronics and smart garments. Mobile electronics devices such as smart phones, tablets, laptops, e-readers and GPS devices have shaped and defined the world of consumer electronics. As such those devices interact with us on every day level, keeping us connected with environment through the use of sensors, imagers, location based services and data networks. Looking beyond typical consumer applications, there is an increasing demand for a wearable and energy efficient electronics capable of operating from human harvested energy. This study will present a solution that is capable of providing basic human bio-parametric data such as: body temperature, pressure, man down indication, impact occurrence indication as well as data on orientation and inclination. All those functions will be embedded as wearable electronics and be able to operate from the energy that was harvested from human body. The need to have this kind of data collected on the human subject in especially demanding environments and situations is greatly appreciative in applications related to search and rescue agencies, paramedics, firefighters and security and police. The solution presented in this thesis is focusing on energy harvesting from human body and the environment, together with utilization of such energy for wearable electronic

    Student Research Abstract Writings, Spring 2018

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    Control Analysis for Grid Tied Battery Energy Storage System for SOC and SOH Management

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    Frequency regulation is an important part of grid ancillary services in the UK power system to mitigate the impacts of variable energy resources and uncertainty of load on system frequency. The National Grid Electricity Transmission (NGET), the primary electricity transmission network operator in the UK, is introduced various frequency response services such as firm frequency response (FFR) and the new fast enhanced frequency response (EFR), which are designed to provide real-time response to deviations in the grid frequency. Flexible and fast response capabilities of battery energy storage systems (BESSs) make them an ideal choice to provide grid frequency regulation. This thesis presents control algorithms for a BESS to deliver a charge/discharge power output in response to deviations in the grid frequency with respect to the requisite service specifications, while managing the state-of-charge (SOC) of the BESS to optimize the availability of the system. Furthermore, this thesis investigates using the BESS in order to maximize triad avoidance benefit revenues while layering UK grid frequency response services. Using historical UK electricity prices, a balancing service scheduling approach is introduced to maximize energy arbitrage revenue by layering different types of grid balancing services, including EFR and FFR, throughout the day. Simulation results demonstrate that the proposed algorithm delivers both dynamic and non-dynamic FFR and also EFR to NGET required service specifications while generating arbitrage revenue as well as service availability payments in the balancing market. In this thesis, a new fast cycle counting method (CCM) considering the effect of current rate (C-rate), SOC and depth-of-discharge (DOD) on battery lifetime for grid-tied BESS is presented. The methodology provides an approximation for the number of battery charge-discharge cycles based on historical microcyling SOC data typical of BESS frequency regulation operation. The EFR and FFR algorithms are used for analysis. The obtained historical SOC data from the analysis are then considered as an input for evaluating the proposed CCM. Utilizing the Miner Rule’s degradation analysis method, lifetime analysis based on battery cycling is also provided for a lithium-titanate (LTO) and lithium-nickel-manganese-cobalt-oxide (NMC) battery. The work in this thesis is supported by experimental results from the 2MW/1MWh Willenhall Energy Storage System (WESS) to validate the models and assess the accuracy of the simulation results
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