A hybrid metaheuritic technique developed for hourly load forecasting

Electricity load forecasting has become one of the most functioning tools in energy efficiency and load management and utility companies which has been made very complex due to deregulation. Due to the importance of providing a secure and economic electricty for the consumers, having a reliable and robust enough forecast engine in short-term load management is very needful. Fuzzy inference system is one of primal branches of Artificial Intelligence techniques which has been widely used for different applications of decision making in complex systems. This paper aims to develop a Fuzzy inference system as a main forecast engine for Short term Load Forecasting (STLF) of a city in Iran. However, the optimization of this platform for this special case remains a basic problem. Hence, to address this issue, the Radial Movement Optimization (RMO) technique is proposed to optimize the whole Fuzzy platform. To support this idea, the accuracy of the proposed model is analyzed using MAPE index and an average error of 1.38% is obtained for the forecast load demand which represents the reliability of the proposed method. Finally, results achieved by this method, demonstrate that an adaptive two-stage hybrid system consisting of Fuzzy & RMO can be an accurate and robust enough choice for STLF problems.

A novel operation and control strategy for a standalone hybrid renewable power system

This paper proposes a novel operation and control strategy for a renewable hybrid power system for a standalone operation. The proposed hybrid system consists of a wind turbine, a fuel cell, an electrolyzer, a battery storage unit, and a set of loads. The overall control strategy is based on a two-level structure. The top level is the energy management and power regulation system. Depending on wind and load conditions, this system generates reference dynamic operating points to low level individual subsystems. The energy management and power regulation system also controls the load scheduling operation during unfavorable wind conditions under inadequate energy storage in order to avoid a system blackout. Based on the reference dynamic operating points of the individual subsystems, the local controllers control the wind turbine, fuel cell, electrolyzer, and battery storage units. The proposed control system is implemented in MATLAB Simpower software and tested for various wind and load conditions. Results are presented and discussed.

Multi-temporal land use mapping using remotely sensed techniques and the integration of a pollutant load model in a GIS

Estimation of nutrient load production based on multi-temporal remotely sensed land-use data for the Glenelg-Hopkins region in southwest Victoria, Australia, is discussed. Changes in land use were mapped using archived Landsat data and computerized classification techniques. Land-use
change is unparalleled in recent history, with 13% of the region transformed in the last decade. Total nitrogen and phosphorus loading were estimated using an export coefficient model. The analysis demonstrated a disturbing increase in nitrogen and phosphorus loadings from 1995 to 2002. Whilst such increases were suspected from past anecdotal and ad-hoc evidence, our modelling quantitatively estimated such increases and thus demonstrated the enormous potential of using remote sensing and GIS for monitoring land-use change and hence improve land-use management.

RFID-based real-time smart waste management system

In an environmental context, the use of RFID (radio frequency identification) and load cell sensor technology can be employed for not only bringing down waste management costs, but also to facilitate automating and streamlining waste (e.g., garbage, recycling, and green) identification and weight measurement processes for designing smart waste management systems. In this paper, we outline a RFID and sensor model for designing a system in real-time waste management. An application of the architecture is described in the area of RFID and sensor based automatic waste identity, weight, and stolen bins identification system (WIWSBIS).

A pilot study of the eccentric decline squat in the management of painful chronic patellar tendinopathy

Objectives: This non-randomised pilot study investigated the effect of eccentric quadriceps training on 17 patients (22 tendons) with painful chronic patellar tendinopathy.

Methods: Two different eccentric exercise regimens were used by subjects with a long duration of pain with activity (more than six months). (a) Nine consecutive patients (10 tendons; eight men, one woman; mean age 22 years) performed eccentric exercise with the ankle joint in a standard (foot flat) position. (b) Eight patients (12 tendons; five men, three women; mean age 28 years) performed eccentric training standing on a 25° decline board, designed to increase load on the knee extensor mechanism. The eccentric training was performed twice daily, with three sets of 15 repetitions, for 12 weeks. Primary outcome measures were (a) 100 mm visual analogue scale (VAS), where the subject recorded the amount of pain during activity, and (b) return to previous activity. Follow up was at 12 weeks, with a further limited follow up at 15 months.

Results: Good clinical results were obtained in the group who trained on the decline board, with six patients (nine tendons) returning to sport and showing a significantly reduced amount of pain over the 12 week period. Mean VAS scores fell from 74.2 to 28.5 (p = 0.004). At 15 months, four patients (five tendons) reported satisfactory results (mean VAS 26.2). In the standard squat group the results were poor, with only one athlete returning to previous activity. Mean VAS scores in this group were 79.0 at baseline and 72.3 at 12 weeks (p = 0.144).

Conclusion: In a small group of patients with patellar tendinopathy, eccentric squats on a decline board produced encouraging results in terms of pain reduction and return to function in the short term. Eccentric exercise using standard single leg squats in a similar sized group appeared to be a less effective form of rehabilitation in reducing pain and returning subjects to previous levels of activity.

An intelligent energy management model for a parallel hybrid vehicle under combined loads

To exploit the benefits offered by parallel HEVs, an intelligent energy management model is developed and evaluated in this paper. Despite most existing works, the developed model incorporates combined wind/drag, slope, rolling, and accessories loads to minimise the fuel consumption under varying driving conditions. A slope prediction unit is also employed. The engine and the electric motor can output power simultaneously under a heavy-load or a slopped road condition. Two simulation were conducted namely slopped-windy-prediction and slopped-windy-prediction-hybrid. The results indicate that the vehicle speed and acceleration is smoother where the hybrid component was included. The average fuel consumption for the first and second simulations were 7.94 and 7.46 liter/100 km, respectively.

Management of SPMD based parallel processing on clusters of workstations

Current attempts to manage parallel applications on Clusters of Workstations (COWs) have either generally followed the parallel execution environment approach or been extensions to existing network operating systems, both of which do not provide complete or satisfactory solutions. The efficient and transparent management of parallelism within the COW environment requires enhanced methods of process instantiation, mapping of parallel process to workstations, maintenance of process relationships, process communication facilities, and process coordination mechanisms. The aim of this research is to synthesise, design, develop and experimentally study a system capable of efficiently and transparently managing SPMD parallelism on a COW. This system should both improve the performance of SPMD based parallel programs and relieve the programmer from the involvement into parallelism management in order to allow them to concentrate on application programming. It is also the aim of this research to show that such a system, to achieve these objectives, is best achieved by adding new special services and exploiting the existing services of a client/server and microkernel based distributed operating system. To achieve these goals the research methods of the experimental computer science should be employed. In order to specify the scope of this project, this work investigated the issues related to parallel processing on COWs and surveyed a number of relevant systems including PVM, NOW and MOSIX. It was shown that although the MOSIX system provide a number of good services related to parallelism management, none of the system forms a complete solution. The problems identified with these systems include: instantiation services that are not suited to parallel processing; duplication of services between the parallelism management environment and the operating system; and poor levels of transparency. A high performance and transparent system capable of managing the execution of SPMD parallel applications was synthesised and the specific services of process instantiation, process mapping and process interaction detailed. The process instantiation service designed here provides the capability to instantiate parallel processes using either creation or duplication methods and also supports multiple and group based instantiation which is specifically design for SPMD parallel processing. The process mapping service provides the combination of process allocation and dynamic load balancing to ensure the load of a COW remains balanced not only at the time a parallel program is initialised but also during the execution of the program. The process interaction service guarantees to maintain transparently process relationships, communications and coordination services between parallel processes regardless of their location within the COW. The combination of these services provides an original architecture and organisation of a system that is capable of fully managing the execution of SPMD parallel applications on a COW. A logical design of a parallelism management system was developed derived from the synthesised system and was shown that it should ideally be based on a distributed operating system employing the client server model. The client/server based distributed operating system provides the level of transparency, modularity and flexibility necessary for a complete parallelism management system. The services identified in the synthesised system have been mapped to a set of server processes including: Process Instantiation Server providing advanced multiple and group based process creation and duplication; Process Mapping Server combining load collection, process allocation and dynamic load balancing services; and Process Interaction Server providing transparent interprocess communication and coordination. A Process Migration Server was also identified as vital to support both the instantiation and mapping servers. The RHODOS client/server and microkernel based distributed operating system was selected to carry out research into the detailed design and to be used for the implementation this parallelism management system. RHODOS was enhanced to provide the required servers and resulted in the development of the REX Manager, Global Scheduler and Process Migration Manager to provide the services of process instantiation, mapping and migration, respectively. The process interaction services were already provided within RHODOS and only required some extensions to the existing Process Manager and IPC Managers. Through a variety of experiments it was shown that when this system was used to support the execution of SPMD parallel applications the overall execution times were improved, especially when multiple and group based instantiation services are employed. The RHODOS PMS was also shown to greatly reduce the programming burden experienced by users when writing SPMD parallel applications by providing a small set of powerful primitives specially designed to support parallel processing. The system was also shown to be applicable and has been used in a variety of other research areas such as Distributed Shared Memory, Parallelising Compilers and assisting the port of PVM to the RHODOS system. The RHODOS Parallelism Management System (PMS) provides a unique and creative solution to the problem of transparently and efficiently controlling the execution of SPMD parallel applications on COWs. Combining advanced services such as multiple and group based process creation and duplication; combined process allocation and dynamic load balancing; and complete COW wide transparency produces a totally new system that addresses many of the problems not addressed in other systems.

Effect of noise factors in energy management of series plug-in hybrid electric vehicles

It has been demonstrated that charge depletion (CD) energy management strategies are more efficient choices for energy management of plug-in hybrid electric vehicles (PHEVs). The knowledge of drive cycle as a priori can improve the performance of CD energy management in PHEVs. However, there are many noise factors which affect both drivetrain power demand and vehicle performance even in identical drive cycles. In this research, the effect of each noise factor is investigated by introducing the concept of power cycle instead of drive cycle for a journey. Based on the nature of the noise factors, a practical solution for developing a power-cycle library is introduced. Investigating the predicted power cycle, an energy management strategy is developed which considers the influence of temperature noise factor on engine performance. The effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered. Simulation results for a modelled series PHEV similar to GM Volt show that the suggested energy management strategy based on the driver power cycle library improves both vehicle fuel economy and battery health by reducing battery load and temperature.

Quantification of physical load in elite junior Australian football players

Results from this thesis provide insights into the physical loads experienced by the elite junior Australian footballer. The information presented can assist in the facilitation of best practice advice for player management and training prescription through the use of training diaries and GPS TMA and HR device technologies.

Evidence-based chronic heart-failure management programs : myth or reality?

Background Chronic heart-failure management programmes (CHF-MPs) have become part of standard care for patients with chronic heart failure (CHF). Objective To investigate whether programmes had applied evidence-based expert clinical guidelines to optimise patient outcomes. Design A prospective cross-sectional survey was used to conduct a national audit. Setting Community setting of CHF-MPs for patients postdischarge. Sample All CHF-MPs operating during 2005–2006 (n=55). Also 10–50 consecutive patients from 48 programmes were recruited (n=1157). Main outcome measures (1) Characteristics and interventions used within each CHF-MP; and (2) characteristics of patients enrolled into these programmes. Results Overall, there was a disproportionate distribution of CHF-MPs across Australia. Only 6.3% of hospitals nationally provided a CHF-MP. A total of 8000 postdischarge CHF patients (median: 126; IQR: 26–260) were managed via CHF-MPs, representing only 20% of the potential national case load. Significantly, 16% of the caseload comprised patients in functional New York Heart Association Class I with no evidence of these patients having had previous echocardiography to confirm a diagnosis of CHF. Heterogeneity of CHF-MPs in applied models of care was evident, with 70% of CHF-MPs offering a hybrid model (a combination of heart-failure outpatient clinics and home visits), 20% conducting home visits and 16% conducting an extended rehabilitation model of care. Less than half (44%) allowed heart-failure nurses to titrate medications. The main medications that were titrated in these programmes were diuretics (n=23, 96%), β-blockers (n=17, 71%), ACE inhibitors (ACEIs) (n=14, 58%) and spironolactone (n=9, 38%). Conclusion CHF-MPs are being implemented rapidly throughout Australia. However, many of these programmes do not adhere to expert clinical guidelines for the management of patients with CHF. This poor translation of evidence into practice highlights the inconsistency and questions the quality of health-related outcomes for these patients.

Short-term load and wind power forecasting using neural network-based prediction intervals

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

An investigation for improved home energy management

 Increasing household energy consumption and increasing primary energy cost urged to improve home energy efficiency. Improved energy management can suggest the ways to improve home energy efficiency. Various home appliances are the prime cause to the increased power demand. Appliance's energy rating information helps to develop awareness and reduce energy consumption. Load shifting can help to reduce overall cost of used energy bill by shifting peak time load to off-peak time. However most of the present appliances remains in standby mode (active or passive) for a significant part of the day, and load shifting cannot reduce the total energy consumption. Therefore investigation is required to identify any possible scopes to improve energy management at home. This paper investigated several home appliances and monitored daily time of use power consumption. It was found that by controlling standby power from a daily home load of 4.482 kWh, power demand can be reduced 12.56% moreover energy related greenhouse gas (GHG) emission can be reduced 133.08kg/year.