Crop load management of fruit trees is a challenge for producers. For this experiment apple, peach, and sweet cherry trees were thinned using mechanical blossom thinning (MBT), and hand blossom thinning (HBT) to mimic MBT. Apple bloom was reduced by MBT, but only one treatment consistently reduced fruit set. Marketable yield, fruit weight, and quality were unaffected by thinning treatments. An apple spur leaf study found that damage from MBT was negligible. Mechanical blossom thinning of peach significantly reduced fruit set and hand thinning requirements at ‘June drop’. Marketable yield, fruit firmness, and soluble solids concentration were largely unaffected by thinning treatments, but fruit weight and size increased in one year. The two highest rates of sweet cherry MBT and HBT reduced fruit set but total yield, fruit weight, and quality were unaffected. Overall, MBT may be a viable option for tree fruit producers, especially peach growers. / The University of Guelph/OMAFRA Sustainable Production Systems Research Programme, the Niagara Peninsula Fruit and Vegetable Growers' Association, NSERC.

To achieve a high level of reliability, efficiency, and robustness in electric systems, the concept of smart grid has been proposed. It is an update of the traditional electric grid designed to meet current and future customers' requirements. With the smart grid, demand management has been adopted in order to shape the load pattern of the consumers, maintain supply-demand balance, and reduce the total energy cost. In this thesis, we focus mainly on energy savings by critically investigating the problem of load management in the smart grid. We first propose a user aware demand management approach that manages residential loads while taking into consideration users' comfort. This latter is modeled in a simple yet effective way that considers waiting time, type of appliance, as well as a weight factor to prioritize comfort or savings. The proposed approach is based on game theory using a modified regret matching procedure. It provides users with high incentives to participate actively in load management and borrows advantages of both centralized and decentralized schemes. Then, we investigate the issue of fairness within demand response programs. The fair division of the system bill stemming from the use of shared microgrid resources with different costs is examined. The Shapley value provides one of the core solutions to fairness problems; however, it has been known to be computationally expensive for systems such as microgrids. Therefore, we incorporate an approximation of the Shapley value into a demand response algorithm to propose a fair billing mechanism based on the contribution of each user towards attaining the aggregated system cost. Finally, we study energy trading in the smart grid as an alternative way to reduce the load on the grid by efficiently using renewable energy resources. We propose a solution that takes into account the smart grid physical infrastructure, in addition to the distribution of its users. Different constraints stemming from the nature of the smart grid have been considered towards a realistic solution. We show through simulation results that all of the proposed schemes reduce the load on the grid, the energy bills, and the total system energy cost while maintaining the users' comfort as well as fairness.

With the growing concerns about energy shortage and demand supply imbalance, demand side management (DSM) activities has found its way into the mining industry. This study analyzes the potential to save energy and energy-costs in underground mine ventilation networks, by application of DSM techniques. Energy saving is achieved by optimally adjusting the speed of the main fan to match the time-varying flow demand in the network, which is known as ventilation on demand (VOD). Further cost saving is achieved by shifting load to off-peak or standard times according to a time of use (TOU) tariff, i.e. finding the optimal mining schedule. The network is modelled using graph theory and Kirchhoff’s laws; which is used to form a non-linear, constrained, optimization problem. The objective of this problem is formulated to minimize the energy cost; and hence it is directly given as a function of the fan speed, which is the control variable. As such, the operating point is found for every change in the fan speed, by incorporating the fan laws and the system curve. The problem is solved using the fmincon solver in Matlab’s optimization toolbox. The model is analyzed for different scenarios, including varying the flow rate requirements and tariff structure. Although the results are preliminary and very case specific, the study suggests that significant energy and energy-cost saving can be achieved in a financially viable manner. / Dissertation (MEng)--University of Pretoria, 2014. / tm2015 / Electrical, Electronic and Computer Engineering / MEng / Unrestricted

Water Treatment Plants (WTPs) supply potable water which is transferred by pumps to various end users. WTPs and other sub-systems are energy intensive with pump installed capacities varying between 75 kW – 6 000 kW. It has therefore become important to optimise the utilisation of WTPs. Cost savings can be achieved and the load on the national grid can be reduced. The aim of this study is to develop and implement load management strategies on a municipal WTP. In this investigation the high lift pumps are deemed to be the largest consumers of electricity. Strategies to safely implement load management on a WTP were researched. By optimising the operations of the pumps, significant cost savings can be achieved. Comparisons between different electricity tariff structures were done. It was found plausible to save R 990 000 annually, on a pumping station with four 1 000 kW pumps installed, when switching to a time-of-use dependent tariff structure. Strategies to optimise plant utilisation while attempting a load management study include the optimisation of filter washing methods and raw water operations. An increase of 34% in efficiency for a filter backwash cycle was achieved. To accommodate the effects of the load management on the WTP, the operation of valves that allow water to distribute within the plant was also optimised. The implemented control strategies aimed to accomplish the full utilisation of the WTP and sub-systems to achieve savings. An average evening peak period load shift impact of 2.21 MW was achieved. Due to filter modifications the plant is able to supply 5% more water daily. A conclusion is drawn regarding the success of the strategies implemented. Recommendations are made for further research. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2015

Water Treatment Plants (WTPs) supply potable water which is transferred by pumps to various end users. WTPs and other sub-systems are energy intensive with pump installed capacities varying between 75 kW – 6 000 kW. It has therefore become important to optimise the utilisation of WTPs. Cost savings can be achieved and the load on the national grid can be reduced. The aim of this study is to develop and implement load management strategies on a municipal WTP. In this investigation the high lift pumps are deemed to be the largest consumers of electricity. Strategies to safely implement load management on a WTP were researched. By optimising the operations of the pumps, significant cost savings can be achieved. Comparisons between different electricity tariff structures were done. It was found plausible to save R 990 000 annually, on a pumping station with four 1 000 kW pumps installed, when switching to a time-of-use dependent tariff structure. Strategies to optimise plant utilisation while attempting a load management study include the optimisation of filter washing methods and raw water operations. An increase of 34% in efficiency for a filter backwash cycle was achieved. To accommodate the effects of the load management on the WTP, the operation of valves that allow water to distribute within the plant was also optimised. The implemented control strategies aimed to accomplish the full utilisation of the WTP and sub-systems to achieve savings. An average evening peak period load shift impact of 2.21 MW was achieved. Due to filter modifications the plant is able to supply 5% more water daily. A conclusion is drawn regarding the success of the strategies implemented. Recommendations are made for further research. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2015

Unmanned Air Vehicles (UAVs) are becoming more widely used in both military and civilian applications. Some of the largest UAVs have power systems equivalent to that of a military strike jet making power management an important aspect of their design. As they have developed, the amount of power needed for loads has increased. This has placed increase strain on the on-board generators and a need for higher reliability. In normal operation these generators are sized to be able to power all on-board systems with out overheating. Under abnormal operating conditions these generators may start to overheat, causing the loss of the generator's power output. The research presented here aims to answer two main questions: 1) Is it possible to predict when an overheat fault will occur based on the expected power usage defined by mission profiles? 2) Can an overheat fault be prevented while still allowing power to be distributed to necessary loads to allow mission completion? This is achieved by a load management algorithm, which adjusts the load profile for a mission, by either displacing the load to spare generators, or resting the generator to cool it down. The result is that for non-catastrophic faults the faulty generator does not need to be fully shut down and missions can continue rather than having to be aborted. This thesis presents the development of the load management system including the algorithm, prediction method and the models used for prediction. Ultimately, the algorithms developed are tested on a generator test rig. The main contribution of this work is the design of a prognostic load management algorithm. Secondary contributions are the use of a lumped parameter thermal model within a condition monitoring application, and the creation of a system identification model to describe the thermal dynamics of a generator.

All-electric ship power systems have limited generation capacity and finite rotating inertia compared with large power systems. Moreover, all-electric ship power systems include large portions of nonlinear loads and dynamic loads relative to the total power capacity, which may significantly reduce the stability margin. Pulse loads and other high-energy weapon loads in the system draw a large amount of power intermittently, which may cause significant frequency and voltage oscillations in the system. Thus, an effective real-time load management technique is needed to dynamically balance the load and generation to operate the system normally. Multi-agent systems, inspired by biological phenomena, aim to cooperatively achieve system objectives that are difficult to reach by a single agent or centralized controller. Since power systems include various electrical components with different dynamical systems, conventional homogeneous multi-agent system cooperative controllers have difficulties solving the real-time load management problem with heterogeneous agents. In this dissertation, a novel heterogeneous multi-agent system cooperative control methodology is presented based on artificial potential functions and reduced-order agent models to cooperatively achieve real-time load management for all-electric ship power systems. The technique integrates high-order system dynamics and various kinds of operational constraints into the multi-agent system, which improves the accuracy of the cooperative controller. The multi-agent system includes a MVAC multiagent system and a DC zone multi-agent, which are coordinated by an AC-DC communication agent. The developed multi-agent system framework and the notional all-electric ship power system model were simulated in PSCAD software. Case studies and performance analysis of the MVAC multi-agent system and the DC zone multi-agent system were performed. The simulation results indicated that propulsion loads and pulse loads can be successfully coordinated to reduce the impact of pulse loads on the power quality of all-electric ship power systems. Further, the switch status or power set-point of loads in DC zones can be optimally determined to dynamically balance the generation and load while satisfying the operational constraints of the system and considering load priorities. The method has great potential to be extended to other isolated power systems, such as microgrids.

In recent years, with the rapid development of electric and electronic technology, the All-Electric Aircraft (AEA) concept has attracted more and more attention, which only utilizes the electric power instead of conventional hydraulic and pneumatic power to supply all the airframe systems. To meet the power requirements under various flight stages and operating conditions, the AEA approach has resulted in the current aircraft electrical power generation capacity up to 1.6 MW. To satisfy the power quality and stability requirements, the advanced power electronic interfaces and more efficient power distribution systems must be investigated. Moreover, with the purpose of taking the full advantages of available electrical power, novel dynamic power distribution management research and design for an AEA must be carried out. The main objective of this thesis is to investigate and develop a methodology of more efficient power distribution management with the purpose of minimizing the rated power generating capacity and the mass of the electrical power system (EPS) including the power generation system and the power distribution system in an AEA. It is important to analyse and compare the subsistent electrical power distribution management approaches in current aircraft. Therefore the electrical power systems of A320 and B777, especially the power management system, will be discussed in this thesis. Most importantly the baseline aircraft, the Flying Crane is the outcome of the group design project. The whole project began in March 2008, and ended in September 2010, including three stages: conceptual design, preliminary design and detailed design. The dynamic power distribution management research is based on the power distribution system of the Flying Crane. The main task of the investigation is to analyse and manage the power usage among and inside typical airframe systems by using dynamic power distribution management method. The characteristics and operation process of these systems will be investigated in detail and thoroughly. By using the method of dynamic power distribution management, all the electrical consumers and sub-systems powered by electricity are managed effectively. The performance of an aircraft can be improved by reducing the peak load requirement on board. Furthermore, the electrical system architecture, distributed power distribution system and the dynamic power distribution management system for AEA are presented. Finally, the mass of the whole electrical power system is estimated and analysed carefully.

To address the overload conditions caused by the increasing network traffic volume, recent literature in the network intrusion detection and prevention field has proposed the use of clusters of network intrusion detection and prevention systems (NIDPSs). We observe that simple traffic distribution schemes are usually used for NIDPS clusters. These schemes have two major drawbacks: (1) the loss of correlation information caused by the traffic distribution because correlated flows are not sent to the same NIDPS and (2) the unbalanced loads of the NIDPSs. The first drawback severely affects the ability to detect intrusions that require analysis of correlated flows. The second drawback greatly increases the chance of overloading an NIDPS even when loads of the others are low. In this thesis, we address these two drawbacks. In particular, we propose two novel traffic distribution systems: the Correlation-Based Load Balancer and the Correlation-Based Load Manager as two different solutions to the NIDPS traffic distribution problem. On the one hand, the Load Balancer and the Load Manager both consider the current loads of the NIDPSs while distributing traffic to provide fine-grained load balancing and dynamic load distribution, respectively. On the other hand, both systems take into account traffic correlation in their distributions, thereby significantly reducing the loss of correlation information during their distribution of traffic. We have implemented prototypes of both systems and evaluated them using extensive simulations and real traffic traces. Overall, the evaluation results show that both systems have low overhead in terms of the delays introduced to the packets. More importantly, compared to the naive hash-based distribution, the Load Balancer significantly improves the anomaly-based detection accuracy of DDoS attacks and port scans -- the two major attacks that require the analysis of correlated flows -- meanwhile, the Load Manager successfully maintains the anomaly-based detection accuracy of these two major attacks of the NIDPSs.

In the new residential area, called Stockholm Royal Seaport (SRS), the customers will be living in Active Houses with Load Management. This implies that some balancing of the grid is shifted from the production to the consumption. To give the customer incentives to participate in the Load Management, new more dynamic pricing models needs to be implemented. At the same time, profits for the investors are needed to motivate an implementation of similar residential areas. To achieve this, an analysis of the electricity markets and an implementation of dynamic pricing models in a MATLAB simulation are done. A proposed trading profit for the investors and possible cost reductions for customers have been derived from the modelling. The results show that the difference in costs between utilized and unutilized Load Management are small, only considering the dynamic pricing models, therefore compliments to these are discussed. The conclusion is therefore that the energy for the manageable loads should be charged separately. Another important conclusion is that a change of the Spotmarket is needed in order to create a more beneficial market for retailers with flexible customers. / I den nya stadsdelen, Norra Djurgårdsstaden, ska kunderna bo i aktiva hus med laststyrda vitvaror. På så vis flyttas en del balanskraft från produktionen till konsumtionen. För att kunderna ska få incitament till att delta i laststyrningen krävs nya, mer dynamiska, pristariffer. Samtidigt behöver investerarna hitta möjliga förtjänster för att motivera ett införande av liknande stadsdelar. Detta har gjorts genom en analys av elmarknaden och en implementering av dynamiska prismodeller i en konsumtionssimulering i MATLAB. En föreslagen trading-förtjänst för investerarna samt möjliga kostnadsreduceringar för kunder har utvärderats utifrån modelleringen. Resultaten visar att med endast de dynamiska prismodellerna blir kostnadsskillnaden liten mellan de som utnyttjar laststyrningen och de som inte gör det, varför komplement till dessa diskuterats. Slutsatsen blir därför att den laststyrda elen bör debiteras enligt separat modell. En ytterligare slutsats är att spotmarknaden bör förändras för att skapa en gynnsam marknad för återförsäljare med flexibla kunder.