Spelling suggestions: "subject:"power productionsection"" "subject:"power productionisation""
1 |
Analysis of variances in electric power system simulation for production costSmith, William Corbett. January 1991 (has links)
Thesis (Ph. D.)--Ohio University, November, 1991. / Title from PDF t.p.
|
2 |
Three phase analysis of unbalanced power system networksShlash, M. A. January 1974 (has links)
No description available.
|
3 |
On the optimization of homeostatic utility controls as applied to small power producing facilitiesGhoudjehbaklou, Hassan 08 1900 (has links)
No description available.
|
4 |
A variance reduction technique for production cost simulationWise, Michael Anthony. January 1989 (has links)
Thesis (M.S.)--Ohio University, November, 1989. / Title from PDF t.p.
|
5 |
System operating voltages for best economy based on reactive power requirements and lossesRao, B. Sreenivasa. January 1962 (has links)
Thesis (M.S.)--University of Wisconsin--Madison, 1962. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaf 102)
|
6 |
The assessment, prediction and measurement of flicker for arc furnaces.Petersen, Hugh Malcolm 17 February 2014 (has links)
M.Ing. (Electrical and Electronic Engineering) / Please refer to full text to view abstract.
|
7 |
Path-dependent valuation of generators in the capacity, energy and carbon marketsSun, Yi, 孙毅 January 2011 (has links)
published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy
|
8 |
Analytical models for wind power investmentCheng, Mang-kong., 鄭孟剛. January 2011 (has links)
Wind power generation has experienced an explosive growth worldwide. It is a
promising renewable energy source to countries that are short of fossil fuels, e.g. China.
While wind power is a distinctive direction to go for, it is still necessary to examine the
rationale behind such investing mania, and this thesis analyzes the issue by collectively
investment modeling.
For investment analysis, it is necessary to first identify the relevant market
background before inferring to any analytical model. Chapter 2 identifies a number of
wind power investment scenarios in accordance to modern electricity market regime,
primarily American and European structures. Among them, two main scenarios are
investigated and modeled subsequently: fixed tariff wind power project invested by
independent power producer and wind power project undertaken by utility. It has to be
emphasized that different market scenarios would lead to different modeling
methodologies for best representing the reality.
Wind power is intermittent and uncertain. One way to describe the probabilistic
energy production is by statistical characterization of wind power in a period of time.
Chapter 3 presents a standalone analytical model of the wind power probability
distribution and its higher order statistics. Large-scale deployment of wind power would
influence power system in unprecedented ways. High penetration wind power poses a
need of refinement to existing methodologies on production costing and reliability
evaluation. The applications of the probabilistic wind power model to these topics are
outlined in this chapter.
In Chapter 4, investment of fixed tariff wind power project is analyzed. Operation
of wind farm is very passive and as long as wind keeps blowing, such wind power
investment has minimal risk in annual revenue. The low-risk profile facilitates debt
financing. This leads to the attempt to manipulate the project capital structure to
maximize the project levered value. Yet the default probability is raised and associated
with a subjective value of default probability there is a value-at-risk debt level. I therefore
propose an optimization formulation to maximize the wind power project valuation with
debt as decision variable subject to the value-at-risk debt constraint.
Apart from independent wind power producers, many policy and market factors
driving wind power development are actually put on the utility side, e.g. Renewable
Portfolio Standard (Renewable Energy Target) in U.S. (Europe) and Green Power
Programs. It implies that utility has to have wind power (or other renewable) capacity
ready by a certain date. In practice, utility may take action earlier if conditions are
favorable or optimal. The conditions considered here are fossil fuel prices or in more
general setting, electricity contract prices. Define the total fuel cost saving from
conventional units as the benefit of wind power. If fuel prices are high enough,
substituting load demand by wind energy is profitable, vice versa. The investment
decision is analogous to premature exercising of an American option, in which the wind
power project is modeled as real option. Chapter 5 offers detailed formulation of this idea. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy
|
9 |
Market segmentation and domestic electricity supply in VictoriaSharam, Andrea. January 2005 (has links)
Thesis (PhD) - Institute for Social Research, Swinburne University of Technology, 2005. / Thesis submitted in fulfillment of the requirements of the degree of Doctor of Philosophy, Institute for Social Research, Swinburne University of Technology, 2005. Typescript. Bibliography: p. 188-207.
|
10 |
An extensional mode resonator for vibration harvestingYoungsman, John M'Kay. January 2009 (has links) (PDF)
Thesis (Ph. D.)--Washington State University, May 2009. / Title from PDF title page (viewed on Apr. 19, 2010). "College of Engineering and Architecture." Includes bibliographical references (p. 113-116).
|
Page generated in 0.0676 seconds