Selection of energy storage system for a regenerative dynamic dynamometer

This paper presents a design technique of a fully regenerative dynamic dynamometer. It incorporates an energy storage system to absorb the energy variation due to dynamometer transients. This allows the minimum power electronics requirement at the grid to supply the losses. The simulation results of the full system over a driving cycle show the amount of energy required to complete a driving cycle, therefore the size of the energy storage system can be determined.

Migrating to a sustainable energy system : distributed generation and storage, fuel cells and hypercars

This paper examines a number of issues in sustainable energy generation and distribution, and explores avenues that are available for integration of our society’s energy supplies. In particular, the paper presents a way in which transport vehicle energy supplies could be integrated with distributed generation schemes to achieve synergistic and beneficial outcomes. The worldwide energy system contains fundamental problems that result directly from the use of unsustainable fuels and a lack of energy system integration. There is a need to adopt an integrated, sustainable energy system for our society. The adoption of distributed generation could result in beneficial restructuring of the energy trade, and a change in the role of energy providers. Inherent benefits in distributed generation schemes would directly combat barriers to installation of renewable generation facilities, which might prove distributed renewable energy sources to be more feasible. The presence of fuel cells, batteries, power electronic inverters and intelligent controls in vehicles of the future provides many opportunities for the integration of vehicle energy supplies into a distributed generation scheme. In such a system, vehicles could play a major role in power generation and storage.

Migrating to a sustainable energy system : distributed generation and storage, fuel cells and hypercars

This paper examines a number of issues in sustainable energy generation and distribution, and explores avenues that are available for integration of our society’s energy supplies. In particular, the paper presents a way in which transport vehicle energy supplies could be integrated with distributed generation schemes to achieve synergistic and beneficial outcomes. The worldwide energy system contains fundamental problems that result directly from the use of unsustainable fuels and a lack of energy system integration. There is a need to adopt an integrated, sustainable energy system for our society. The adoption of distributed generation could result in beneficial restructuring of the energy trade, and a change in the role of energy providers. Inherent benefits in distributed generation schemes would directly combat barriers to installation of renewable generation facilities, which might prove distributed renewable energy sources to be more feasible. The presence of fuel cells, batteries, power electronic inverters and intelligent controls in vehicles of the future provides many opportunities for the integration of vehicle energy supplies into a distributed generation scheme. In such a system, vehicles could play a major role in power generation and storage.

Virtual world cultural probe

We have developed a virtual world environment for eliciting expert information from stakeholders. The intention is that the virtual world prompts the user to remember more about their work processes. Our example shows a sparse visualisation of the University of Vienna Department of Computer Science, our collaborators in this project.

Crowd monitoring using computer vision

Novel computer vision techniques have been developed for automatic monitoring of crowed environments such as airports, railway stations and shopping malls. Using video feeds from multiple cameras, the techniques enable crowd counting, crowd flow monitoring, queue monitoring and abnormal event detection. The outcome of the research is useful for surveillance applications and for obtaining operational metrics to improve business efficiency.

The operating schedule for battery energy storage companies in electricity market

This paper presents a series of operating schedules for Battery Energy Storage Companies (BESC) to provide peak shaving and spinning reserve services in the electricity markets under increasing wind penetration. As individual market participants, BESC can bid in ancillary services markets in an Independent System Operator (ISO) and contribute towards frequency and voltage support in the grid. Recent development in batteries technologies and availability of the day-ahead spot market prices would make BESC economically feasible. Profit maximization of BESC is achieved by determining the optimum capacity of Energy Storage Systems (ESS) required for meeting spinning reserve requirements as well as peak shaving. Historic spot market prices and frequency deviations from Australia Energy Market Operator (AEMO) are used for numerical simulations and the economic benefits of BESC is considered reflecting various aspects in Australia’s National Electricity Markets (NEM).

Coordinated control of grid connected photovoltaic reactive power and battery energy storage systems to improve the voltage profile of a residential distribution feeder

Increasing penetration of photovoltaic (PV) as well as increasing peak load demand has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and Battery Energy Storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop based BES system is evaluated for rural and urban scenarios (having different R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low resistance feeder), whereas, coordinated PV and BES support is required for the rural scenario (high resistance feeder). Constant as well as variable droop based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes is presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data is used to verify the efficacy of the proposed method.

Estimating benefits of energy storage for aggregate storage applications in electricity distribution networks in Queensland

Electric Energy Storage (EES) is considered as one of the promising options for reducing the need for costly upgrades in distribution networks in Queensland (QLD). However, It is expected, the full potential for storage for distribution upgrade deferral cannot be fully realized due to high cost of EES. On the other hand, EES used for distribution deferral application can support a variety of complementary storage applications such as energy price arbitrage, time of use (TOU) energy cost reduction, wholesale electricity market ancillary services, and transmission upgrade deferral. Aggregation of benefits of these complementary storage applications would have the potential for increasing the amount of EES that may be financially attractive to defer distribution network augmentation in QLD. In this context, this paper analyzes distribution upgrade deferral, energy price arbitrage, TOU energy cost reduction, and integrated solar PV-storage benefits of EES devices in QLD.

Performance-driven live migration of multiple virtual machines in datacenters

Live migration of multiple Virtual Machines (VMs) has become an indispensible management activity in datacenters for application performance, load balancing, server consolidation. While state-of-the-art live VM migration strategies focus on the improvement of the migration performance of a single VM, little attention has been given to the case of multiple VMs migration. Moreover, existing works on live VM migration ignore the inter-VM dependencies, and underlying network topology and its bandwidth. Different sequences of migration and different allocations of bandwidth result in different total migration times and total migration downtimes. This paper concentrates on developing a multiple VMs migration scheduling algorithm such that the performance of migration is maximized. We evaluate our proposed algorithm through simulation. The simulation results show that our proposed algorithm can migrate multiple VMs on any datacenter with minimum total migration time and total migration downtime.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.

Load leveling in LV network using coordianted Energy Storage Units

This paper proposes a new distributed coordination approach to make load leveling, using Energy Storage Units (ESUs) in LV network. The proposed distributed control strategy is based on consensus algorithm which shares the required active power equally among the ESUs with respect to their rating. To show the effectiveness of the proposed approach, a typical radial LV network is simulated as a case study.

Voltage regulation, power balancing and battery storage discharge control by smart demand side management and multi-objective decision making

A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.

Optimal sizing of combined PV-energy storage for a grid-connected residential building

In this paper, load profile and operational goal are used to find optimal sizing of combined PV-energy storage for a future grid-connected residential building. As part of this approach, five operational goals are introduced and the annual cost for each operation goal has been assessed. Finally, the optimal sizing for combined PV-energy storage has been determined, using direct search method. In addition, sensitivity of the annual cost to different parameters has been analyzed.

Design of a least-cost battery-supercapacitor energy storage system for realizing dispatchable wind power

A statistical approach is used in the design of a battery-supercapacitor energy storage system for a wind farm. The design exploits the technical merits of the two energy storage mediums, in terms of the differences in their specific power and energy densities, and their ability to accommodate different rates of change in the charging/discharging powers. By treating the input wind power as random and using a proposed coordinated power flows control strategy for the battery and the supercapacitor, the approach evaluates the energy storage capacities, the corresponding expected life cycle cost/year of the storage mediums, and the expected cost/year of unmet power dispatch. A computational procedure is then developed for the design of a least-cost/year hybrid energy storage system to realize wind power dispatch at a specified confidence level.

Modeling and position-sensorless control of a dual-airgap axial flux permanent magnet machine for flywheel energy storage systems

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.