Autonomous underwater vehicles: development and implementation of time and energy efficient trajectories

Autonomous underwater vehicles (AUVs) are increasingly used, both in military and civilian applications. These vehicles are limited mainly by the intelligence we give them and the life of their batteries. Research is active to extend vehicle autonomy in both aspects. Our intent is to give the vehicle the ability to adapt its behavior under different mission scenarios (emergency maneuvers versus long duration monitoring). This involves a search for optimal trajectories minimizing time, energy or a combination of both. Despite some success stories in AUV control, optimal control is still a very underdeveloped area. Adaptive control research has contributed to cost minimization problems, but vehicle design has been the driving force for advancement in optimal control research. We look to advance the development of optimal control theory by expanding the motions along which AUVs travel. Traditionally, AUVs have taken the role of performing the long data gathering mission in the open ocean with little to no interaction with their surroundings, MacIver et al. (2004). The AUV is used to find the shipwreck, and the remotely operated vehicle (ROV) handles the exploration up close. AUV mission profiles of this sort are best suited through the use of a torpedo shaped AUV, Bertram and Alvarez (2006), since straight lines and minimal (0 deg - 30 deg) angular displacements are all that are necessary to perform the transects and grid lines for these applications. However, the torpedo shape AUV lacks the ability to perform low-speed maneuvers in cluttered environments, such as autonomous exploration close to the seabed and around obstacles, MacIver et al. (2004). Thus, we consider an agile vehicle capable of movement in six degrees of freedom without any preference of direction.

Changes in resting and walking energy expenditure and walking speed during pregnancy in obese women

Background Energy conserving processes reported in undernourished women during pregnancy are a recognised strategy to provide energy required to support fetal development. Women who are obese before conceiving arguably have sufficient fat stores to support the energy demands of pregnancy without the need to provoke energy conserving mechanisms. Objective We tested the hypothesis that obese women would demonstrate behavioural adaptation (i.e. decrease in self-selected walking (SSW) speed) but not metabolic compensation (i.e. decrease in resting metabolic rate (RMR) or metabolic cost of walking) during gestation. Design RMR, SSW speed, metabolic cost of walking, and anthropometry were measured in 23 women (BMI: 33.6 ± 2.5 kg/m2; 31 ± 4 years) at approximately weeks 15 (wk 15) and 30 (wk 30) of gestation. RMR was also measured in two cohorts of non-pregnant controls matched for age, weight and height of the pregnant cohort at wk 15 (N=23) and wk 30 (N=23). Results GWG varied widely (11.3 ± 5.4 kg) and 52% of women gained more weight than is recommended. RMR increased significantly by an average 177 ± 176 kcal/d (11±12%; P<0.0001); however the within-group variability was large. Both the metabolic cost of walking and SSW speed decreased significantly (P<0.01). While RMR increased in >80% of the cohort, the net oxygen cost of walking decreased in the same proportion of women. Conclusions While the increase in RMR was greater than was explained by weight gain, there was evidence of both behavioural and biological compensation in the metabolic cost of walking in obese women during gestation.

Implementable efficient time and energy consumption trajectories design for an autonomous underwater vehicle

In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.

Innovative damage assessment of steel truss bridges using modal strain energy correlation

As a part of vital infrastructure and transportation network, bridge structures must function safely at all times. Bridges are designed to have a long life span. At any point in time, however, some bridges are aged. The ageing of bridge structures, given the rapidly growing demand of heavy and fast inter-city passages and continuous increase of freight transportation, would require diligence on bridge owners to ensure that the infrastructure is healthy at reasonable cost. In recent decades, a new technique, structural health monitoring (SHM), has emerged to meet this challenge. In this new engineering discipline, structural modal identification and damage detection have formed a vital component. Witnessed by an increasing number of publications is that the change in vibration characteristics is widely and deeply investigated to assess structural damage. Although a number of publications have addressed the feasibility of various methods through experimental verifications, few of them have focused on steel truss bridges. Finding a feasible vibration-based damage indicator for steel truss bridges and solving the difficulties in practical modal identification to support damage detection motivated this research project. This research was to derive an innovative method to assess structural damage in steel truss bridges. First, it proposed a new damage indicator that relies on optimising the correlation between theoretical and measured modal strain energy. The optimisation is powered by a newly proposed multilayer genetic algorithm. In addition, a selection criterion for damage-sensitive modes has been studied to achieve more efficient and accurate damage detection results. Second, in order to support the proposed damage indicator, the research studied the applications of two state-of-the-art modal identification techniques by considering some practical difficulties: the limited instrumentation, the influence of environmental noise, the difficulties in finite element model updating, and the data selection problem in the output-only modal identification methods. The numerical (by a planer truss model) and experimental (by a laboratory through truss bridge) verifications have proved the effectiveness and feasibility of the proposed damage detection scheme. The modal strain energy-based indicator was found to be sensitive to the damage in steel truss bridges with incomplete measurement. It has shown the damage indicator's potential in practical applications of steel truss bridges. Lastly, the achievement and limitation of this study, and lessons learnt from the modal analysis have been summarised.

Planning for the impact of distributed solar energy on the grid

The behaviour of single installations of solar energy systems is well understood; however, what happens at an aggregated location, such as a distribution substation, when output of groups of installations cumulate is not so well understood. This paper considers groups of installations attached to distributions substations on which the load is primarily commercial and industrial. Agent-based modelling has been used to model the physical electrical distribution system and the behaviour of equipment outputs towards the consumer end of the network. The paper reports the approach used to simulate both the electricity consumption of groups of consumers and the output of solar systems subject to weather variability with the inclusion of cloud data from the Bureau of Meteorology (BOM). The data sets currently used are for Townsville, North Queensland. The initial characteristics that indicate whether solar installations are cost effective from an electricity distribution perspective are discussed.

An assessment for cost effective maintenance and operation of the Callide Power Station electrical system, using reliability evaluation

The reliable operation of the electrical system at Callide Power Station is of extreme importance to the normal everyday running of the Station. This study applied the principles of reliability to do an analysis on the electrical system at Callide Power Station. It was found that the level of expected outage cost increased exponentially with a declining level of maintenance. Concluding that even in a harsh economic electricity market where CS Energy tries and push their plants to the limit, maintenance must not be neglected. A number of system configurations were found to increase the reliability of the system and reduce the expected outage costs. A number of other advantages were identified as a result of using reliability principles to do this study on the Callide electrical system configuration.

The effectiveness of energy feedback for conservation and peak demand : a literature review

This paper reviews electricity consumption feedback literature to explore the potential of electricity feedback to affect residential consumers’ electricity usage patterns. The review highlights a substantial amount of literature covering the debate over the effectiveness of different feedback criteria to residential customer acceptance and overall conservation and peak demand reduction. Researchers studying the effects of feedback on everyday energy use have observed substantial variation in effect size, both within and between studies. Although researchers still continue to question the types of feedback that are most effective in encouraging conservation and peak load reduction, some trends have emerged. These include that feedback be received as quickly as possible to the time of consumption; be related to a standard; be clear and meaningful and where possible both direct and indirect feedback be customised to the customer. In general, the literature finds that feedback can reduce electricity consumption in homes by 5 to 20 per cent, but that significant gaps remain in our knowledge of the effectiveness and cost benefit of feedback.

Transmission system expansion planning considering combined operation of wind farms and energy storage systems

An energy storage system (ESS) can provide ancillary services such as frequency regulation and reserves, as well as smooth the fluctuations of wind power outputs, and hence improve the security and economics of the power system concerned. The combined operation of a wind farm and an ESS has become a widely accepted operating mode. Hence, it appears necessary to consider this operating mode in transmission system expansion planning, and this is an issue to be systematically addressed in this work. Firstly, the relationship between the cost of the NaS based ESS and its discharging cycle life is analyzed. A strategy for the combined operation of a wind farm and an ESS is next presented, so as to have a good compromise between the operating cost of the ESS and the smoothing effect of the fluctuation of wind power outputs. Then, a transmission system expansion planning model is developed with the sum of the transmission investment costs, the investment and operating costs of ESSs and the punishment cost of lost wind energy as the objective function to be minimized. An improved particle swarm optimization algorithm is employed to solve the developed planning model. Finally, the essential features of the developed model and adopted algorithm are demonstrated by 18-bus and 46-bus test systems.

Energy-efficient localization : GPS duty cycling with radio ranging

GPS is a commonly used and convenient technology for determining absolute position in outdoor environments, but its high power consumption leads to rapid battery depletion in mobile devices. An obvious solution is to duty cycle the GPS module, which prolongs the device lifetime at the cost of increased position uncertainty while the GPS is off. This article addresses the trade-off between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty while GPS is off. Empirical GPS and radio contact data from a large-scale animal tracking deployment is used to model node mobility, radio performance, and GPS. Because GPS takes a considerable, and variable, time after powering up before it delivers a good position measurement, we model the GPS behaviour through empirical measurements of two GPS modules. These models are then used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose strategies that use RSSI ranging and GPS back-offs to further reduce energy consumption. Results show that our combined strategies can cut node energy consumption by one third while still meeting application-specific positioning criteria.

Energy efficient virtual machine placement in data centers

Electricity cost has become a major expense for running data centers and server consolidation using virtualization technology has been used as an important technology to improve the energy efficiency of data centers. In this research, a genetic algorithm and a simulation-annealing algorithm are proposed for the static virtual machine placement problem that considers the energy consumption in both the servers and the communication network, and a trading algorithm is proposed for dynamic virtual machine placement. Experimental results have shown that the proposed methods are more energy efficient than existing solutions.

The impact of the clean development mechanism (CDM) on the cost price of wind power electricity : a China study

As a renewable energy source, wind power is playing an increasingly important role in China’s electricity supply. Meanwhile, China is also the world’s largest market for Clean Development Mechanism (CDM) wind power projects. Based on the data of 27 wind power projects of Inner Mongolia registered with the Executive Board of the United Nations (EB) in 2010, this paper constructs a financial model of Net Present Value (NPV) to analyze the cost of wind power electricity. A sensitivity analysis is then conducted to examine the impact of different variables with and without Certified Emission Reduction (CER) income brought about by the CDM. It is concluded that the CDM, along with static investment and annual wind electricity production, is one of the most significant factors in promoting the development of wind power in China. Additionally, wind power is envisaged as a practical proposition for competing with thermal power if the appropriate actions identified in the paper are made.

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.

HeatWave : a handheld 3D thermography system for energy auditing

Energy auditing is an effective but costly approach for reducing the long-term energy consumption of buildings. When well-executed, energy loss can be quickly identified in the building structure and its subsystems. This then presents opportunities for improving energy efficiency. We present a low-cost, portable technology called "HeatWave" which allows non-experts to generate detailed 3D surface temperature models for energy auditing. This handheld 3D thermography system consists of two commercially available imaging sensors and a set of software algorithms which can be run on a laptop. The 3D model can be visualized in real-time by the operator so that they can monitor their degree of coverage as the sensors are used to capture data. In addition, results can be analyzed offline using the proposed "Spectra" multispectral visualization toolbox. The presence of surface temperature data in the generated 3D model enables the operator to easily identify and measure thermal irregularities such as thermal bridges, insulation leaks, moisture build-up and HVAC faults. Moreover, 3D models generated from subsequent audits of the same environment can be automatically compared to detect temporal changes in conditions and energy use over time.

Defining expected cost for the air conditioning to avoid a price spike of electricity market under DSR model

This work presents a demand side response model (DSR) which assists small electricity consumers, through an aggregator, exposed to the market price to proactively mitigate price and peak impact on the electrical system. The proposed model allows consumers to manage air-conditioning when as a function of possible price spikes. The main contribution of this research is to demonstrate how consumers can minimise the total expected cost by optimising air-conditioning to account for occurrences of a price spike in the electricity market. This model investigates how pre-cooling method can be used to minimise energy costs when there is a substantial risk of an electricity price spike. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics during hot days on weekdays in the period 2011 to 2012.

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.