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1 
Direct nonlinear interior point methods for optimal power flowsWu, YuChi 08 1900 (has links)
No description available.

2 
Online energy generation scheduling for microgrids with intermittent energy sources and cogeneration. / CUHK electronic theses & dissertations collectionJanuary 2013 (has links)
Lu, Lian. / Thesis (M.Phil.)Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 9195). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.

3 
A new evolutionary optimisation method for the operation of power systems with multiple storage resourcesThai, Cau Doan Hoang, Electrical Engineering & Telecommunications, Faculty of Engineering, UNSW January 2000 (has links)
Advanced technologies, a worldwide trend to deregulation of power systems and environmental constraints have attracted increasing interest in the operation of electric power systems with multiple storage resources. Under the competitive pressure of the deregulation, new efficient solution techniques to adapt quickly to the changing marketplace are in demand. This thesis presents a new evolutionary method, Constructive Evolutionary Programming (CEP), for minimising the system operational cost of scheduling electric power systems with multiple storage resources. The method combines the advantages of Constructive Dynamic Programming and Evolutionary Programming. Instead of evolving the "primal" variables such as storage content releases and thermal generator outputs, CEP evolves the piecewise linear convex costtogo functions (i.e. the storage content value curves). The multistage problem of multistorage power system scheduling is thus decomposed into many smaller onestage subproblems with evolved costtogo functions. For each evolutionary individual, linear programming is used in the forward pass process to solve the dispatch subproblems and the total system operational cost over the scheduling period is assigned to its fitness. Case studies demonstrate that the proposed method is robust and efficient for multistorage power systems, particularly large complex hydrothermal system with cascaded and pumped storages. Although the proposed method is in the early stage of development, relying on assumptions of piecewise linear convexity in a deterministic environment, methods for the incorporation of stochastic models, electrical network and nonlinear, nonconvex and nonsmooth models are discussed. In addition, a number of possible improvements are also outlined. Due to its simplicity but robustness and efficiency, there are potential research directions for the further development of this evolutionary optimisation method.

4 
A new evolutionary optimisation method for the operation of power systems with multiple storage resourcesThai, Cau Doan Hoang, Electrical Engineering & Telecommunications, Faculty of Engineering, UNSW January 2000 (has links)
Advanced technologies, a worldwide trend to deregulation of power systems and environmental constraints have attracted increasing interest in the operation of electric power systems with multiple storage resources. Under the competitive pressure of the deregulation, new efficient solution techniques to adapt quickly to the changing marketplace are in demand. This thesis presents a new evolutionary method, Constructive Evolutionary Programming (CEP), for minimising the system operational cost of scheduling electric power systems with multiple storage resources. The method combines the advantages of Constructive Dynamic Programming and Evolutionary Programming. Instead of evolving the "primal" variables such as storage content releases and thermal generator outputs, CEP evolves the piecewise linear convex costtogo functions (i.e. the storage content value curves). The multistage problem of multistorage power system scheduling is thus decomposed into many smaller onestage subproblems with evolved costtogo functions. For each evolutionary individual, linear programming is used in the forward pass process to solve the dispatch subproblems and the total system operational cost over the scheduling period is assigned to its fitness. Case studies demonstrate that the proposed method is robust and efficient for multistorage power systems, particularly large complex hydrothermal system with cascaded and pumped storages. Although the proposed method is in the early stage of development, relying on assumptions of piecewise linear convexity in a deterministic environment, methods for the incorporation of stochastic models, electrical network and nonlinear, nonconvex and nonsmooth models are discussed. In addition, a number of possible improvements are also outlined. Due to its simplicity but robustness and efficiency, there are potential research directions for the further development of this evolutionary optimisation method.

5 
A new evolutionary optimisation method for the operation of power systems with multiple storage resourcesThai, Cau Doan Hoang, Electrical Engineering & Telecommunications, Faculty of Engineering, UNSW January 2000 (has links)
Advanced technologies, a worldwide trend to deregulation of power systems and environmental constraints have attracted increasing interest in the operation of electric power systems with multiple storage resources. Under the competitive pressure of the deregulation, new efficient solution techniques to adapt quickly to the changing marketplace are in demand. This thesis presents a new evolutionary method, Constructive Evolutionary Programming (CEP), for minimising the system operational cost of scheduling electric power systems with multiple storage resources. The method combines the advantages of Constructive Dynamic Programming and Evolutionary Programming. Instead of evolving the "primal" variables such as storage content releases and thermal generator outputs, CEP evolves the piecewise linear convex costtogo functions (i.e. the storage content value curves). The multistage problem of multistorage power system scheduling is thus decomposed into many smaller onestage subproblems with evolved costtogo functions. For each evolutionary individual, linear programming is used in the forward pass process to solve the dispatch subproblems and the total system operational cost over the scheduling period is assigned to its fitness. Case studies demonstrate that the proposed method is robust and efficient for multistorage power systems, particularly large complex hydrothermal system with cascaded and pumped storages. Although the proposed method is in the early stage of development, relying on assumptions of piecewise linear convexity in a deterministic environment, methods for the incorporation of stochastic models, electrical network and nonlinear, nonconvex and nonsmooth models are discussed. In addition, a number of possible improvements are also outlined. Due to its simplicity but robustness and efficiency, there are potential research directions for the further development of this evolutionary optimisation method.

6 
On power scheduling and strategic behavior in electricity marketsNuchprayoon, Somboon 05 1900 (has links)
No description available.

7 
EnergyEfficient Power Management Architectures for Emerging Needs from the Internet of Things Devices to Data CentersKim, Dongkwun January 2022 (has links)
The Internet of Things (IoT) is now permeating our daily lives, providing critical data for every decision. IoT architecture consists of multiple layers with unique functions and independent components. Each layer of IoT architecture requires different power sources and power delivery schemes. Therefore, different types of power management architectures are required for individual IoT components. Fortunately, advances in metal oxide semiconductor (MOS) technology have made it possible to implement a variety of highperformance power management architectures.
These power management architectures should not only create the power rails required for IoT components but also serve additional functions depending on the application. The power management architecture of IoT devices needs to support submW or mWscale power consumption. In addition, the power management architecture should be either fully integrated on a chip or miniaturized with few passive components to minimize the size of IoT devices. Buildingscale data centers, on the other hand, need various power conversion stages. In this scenario, power conversion from an intermediate DC bus to many point of loads (PoL) requires a high conversion ratio DCDC converter. Because each PoL draws enormous amounts of power, the power management architecture should withstand high currents and include protection circuitry to prevent damage.
This thesis presents research on the design of power management architectures required by IoT devices and data centers. Chapter 2 presents the design and circuit techniques of power management architectures for IoT devices. Chapter 2 outlines a new methodology for codesigning an integrated switchedcapacitor (SC) DCDC converter and a load circuit in ultralowpower IoT devices. This methodology enables the implementation of an areaefficient fully integrated IoT systemonchip (SoC) while maintaining high power conversion efficiency (PCE). Chapter 3 presents a 10output ultralowpower singleinductormultipleoutput (SIMO) DCDC buck converter with integrated output capacitors for submW IoT SoCs. Featuring a continuous comparatorbased output switch controller and a digital pulsewidth modulation (PWM) controller for ultralow feedback latency, this SIMO converter produces ten independent output voltages with high PCE.
Lastly, in Chapter 4, an integrated programmable gate timing control and gate driver chip for an activeclamp forward converter (ACFC) Power Block for data center applications is developed. While the ACFC Power Block converts 1248 V intermediate DC bus voltage to a digital PoL voltage, the gate timing control and driver chip can optimize PCE and reduce the system form factor.

8 
Potential benefits of a transformer load management systemMiller, Kenneth Aubrey January 1970 (has links)
A method of calculating the yearly owning and operating cost of a distribution transformer is developed taking into consideration the loss of life due to overload. Using the developed methods, the potential benefits of managing an overloaded distribution transformer was calculated for a transformer on the Virginia Electric and Power Company (Vepco) System.
By loading the transformer according to a saturation type load growth curve considered typical for Vepco System, its life was approximated. The fixed carrying charges were then applied at a rate sufficient to recover all invested capital during the life of the transformer.
The potential savings were calculated when cutting the secondary and adding a transformer of equal one size smaller and two sizes smaller than the original. The study indicated no savings would be obtained when cutting the secondary.
The only savings indicated were obtained by taking down an overloaded transformer and replacing it with the next larger size.
The potential savings of managing these transformers presently installed, as well as those to be installed in the next years, as well as those to be installed in the next ten years, was calculated using a critical rate of return of 6, 7, 8, 9, and 10 percent. The calculated savings were $3,251,500 at 6 Percent, $2,674,400 at 7 Percent, $2,075,400 at 8 Percent, $1,602,200 at 9 Percent, $1,257,300 at 10 Percent. / Master of Science

9 
Generalized Differential Calculus and Applications to OptimizationRector, R. Blake 01 June 2017 (has links)
This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of setvalued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations research, including nonconvex problems. Finally, an optimization framework is applied to solve a problem in electric power systems involving a smart solar inverter and battery storage system providing energy and ancillary services to the grid.

10 
A method of generation scheduling in electric utility systems with nuclear unitsRahman, Saifur 07 April 2010 (has links)
The problem of unit commitment in an electric utility system is analyzed. The types of generating units considered include nuclearsteam, fossilsteam, thermalpeaking, conventional and pumpedstorage hydro. The large problem of generating unit commitment, due to the inclusion of the nuclear unit, is decomposed into two stages. In the first stage, the relatively stable nuclear generation is optimized with respect to the generation from the large fossilsteam unit. Hourly generation levels for all the units in the system are determined in the second stage.
AS a result of considering the startupshutdown cost, the objective function has a fixed charge component in addition to first and second degree polynomials. Representation of the minimum turndown level and minimum Shutdown duration of the generator necessitates the use of O1 variables along with continuous variables. The solution methodology presented here, applying an extension of the LambdaSeparable Programming, can handle these requirements efficiently.
Application of the algorithm results in a minimumcost generation schedule for all units in the system. Optimum generation levels of energy limited units are determined without using a preselected unit commitment order. The effect of startupshutdown costs on the number of hours a Plant should operate is established. The cost and benefit of spent nuclear fuel reprocessing is analyzed and the effect of uranium prices on it (reprocessing) is shown.
The model is tested using a sample system of six generating units. Hourly generation schedules, includig purchase and sale, are determined for two oneweek periods while the nuclear generation is optimized for an entire year. / Ph. D.

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