No description available.

Abstract As the result of the free economic booming in the past years, th international trade relations have became more closed and intense. Especially, the globlization and WTO make most of the industries become more competitive. Each government takes reformation at the industry movement¡Bprivatization or free economy policy to achieve the cost down and efficiency in order to obtain international marketing advantage .for example,the British government was the first one todeploy privatizatiopn of electricity market Since 1980 .Its successful is the pattern of American¡AAustrian¡Anorth Europe and Asia countries. The electricity market is monopolized by the governent-own Taiwan Power Company for more than 50 years.It has the traditional bussinesss including the power generation¡Bthe transmission ¡Bthe distribution and the sales ,which made excellent contribution to this country. After 1980s¡Awith global economic booming¡A the electricity power demanding is gradually impeded by green party and public that corncern the impact to the environment verywhere on this island. Consequently ,without the sufficient power supply ,the electricity power shortage was quite often since then.In order to facilitate the efficient management and increase the capacity of the power the government ordered the Department of Economy of ROC to accomplish the de-regulation and privatization of the electricity market.By induced the capital with management skill from local private company¡Athe goal has been achieved with significant progresses.and more competitors.Three stages bid increased 9000 mw of power at final¡Ait nearly 25¢Mof total market, four privates power company was synconization already since 1998. Generally speaking ,the power deregulation policy is successful and has been gradually move to its target. The beginning of this paper is to probe the difficulties that the private-owned company ,though the planning, to the final achievement. By collecting and investigating all the related materials, this paper discusses and reviews the drawback and results of the power deregulation policy. And the main topics are to provide the advise and create new vision for the undergoing deregultion plan ,including the analysis and review of the privatization policy ,the location decision of new power plans the planning and design for the power distribution ,ande marketing of the electricity. The private power companies could use the final conclusionas the advice or references in their future plans

Yes / The classical generation scheduling problem defines on/off decisions (commitment) and dispatch level of all available generators in a power system for each scheduling period. In recent years researchers have focused on developing new approaches to solve nonclassical generation scheduling problems in the newly deregulated and decentralized electricity market place. In this paper a GA-based approach has been developed for a system operator to schedule generation in a market akin to that operating in England and Wales. A generation scheduling problem has been formulated and solved using available trading information at the time of dispatch. The solution is updated after information is obtained in a rolling fashion. The approach is tested for two IEEE network-based problems, and achieves comparable results with a branch and bound technique in reasonable CPU time.

Following the privatisation programme of public utilities implemented by the UK government in the 1980s and early 1990s, an interesting debate on the impact of regulation on the cost of equity capital has emerged. While the effects of regulatory announcements have been studied extensively in the USA, there is very little systematic evidence in the UK. This thesis partly redresses this imbalance by analysing the impact of regulatory announcements on the ex-post returns of equity capital and systematic risk of three utility industries in the UK, namely the electricity, telecommunications and water industries. The main objective of this thesis is to test the impact of regulatory announcements that relate to competition, pricing and the quality of services on the return and risk of equity capital. By using an event-study type methodology, the thesis attempts to isolate the effects of regulation from technical and market uncertainties. The methodology normally used in this type of studies is extended to adjust for the well-documented problem in financial time series of volatility clustering and to allow for changes in the systematic risk through time. Overall, the results in the empirical chapters reveal some important issues. While it is clear from the debate in the literature that the cost of capital influences the choice of regulatory parameters, this thesis provides evidence to support the view that regulation in turn alters the cost of equity capital by affecting the ex-post returns and systematic risk of both individual regulated companies and industries. Although the direction and size of these effects of regulation are not always easy to predict, there is evidence to suggest that they may depend crucially on the structure and competitive posture of the industry, as well as technological and market conditions and the parameters of the regulatory system.

Diss. (sammanfattning) Uppsala : Uppsala universitet, 2005. / Härtill 5 uppsatser.

The aim of this study is to examine how the EU ETS price has affected the price of electricity in the Nordic electricity market, and how future changes in the carbon price may affect the wholesale electricity prices. The Nordic countries included are Sweden, Norway, Denmark and Finland. The analysis builds on a reduced econometric model where the Nordic electricity price constitutes the dependent variable. Problem with autocorrelation implied that quarterly data rather than monthly data were used. This model is estimated using ordinary least square (OLS) regression technique. Four variables were found to be statistically significant. These include the EU ETS price, the hydro reservoir level, the coal price and the temperature. The estimated coefficients were used to conduct a simulation on what could happen if the EU ETS price increased to € 30 per ton. The results showed that the electricity price would than increase by about € 16 per MWh from its current level at about € 37 per MWh.

Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.

Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.

No description available.

An electricity market is very complex and different in its nature, when compared to other commodity markets. The introduction of competition and restructuring in global electricity markets brought more complexity and major changes in terms of governance, ownership and technical and market operations. In a liberalized electricity market, all market participants are responsible for their own decisions; therefore, all the participants are trying to make profit by participating in electricity trading. There are different types of electricity market, and in this research a bilateral electricity market has been specifically considered. This thesis not only contributes with regard to the reviewing UK electricity market as an example of a bilateral electricity market with more than 97% of long-term bilateral trading, but also proposes a dual aspect point of view with regard to the bilateral electricity market by splitting the generation and supply sides of the wholesale market. This research aims at maximizing the market participants’ profits and finds the equilibrium point of the bilateral market; hence, various methods such as equilibrium models have been reviewed with regard to management of the risks (e.g. technical and financial risks) of participating in the electricity market. This research proposes a novel Conjectural Variation Equilibrium (CVE) model for bilateral electricity markets, to reduce the market participants’ exposure to risks and maximize the profits. Hence, generation companies’ behaviors and strategies in an imperfect bilateral market environment, oligopoly, have been investigated by applying the CVE method. By looking at the bilateral market from an alternative aspect, the supply companies’ behaviors in an oligopsony environment have also been taken into consideration. At the final stage of this research, the ‘matching’ of both quantity and price between oligopolistic and oligopsonistic markets has been obtained through a novel-coordinating algorithm that includes CVE model iterations of both markets. Such matching can be achieved by adopting a hierarchical optimization approach, using the Matlab Patternsearch optimization algorithm, which acts as a virtual broker to find the equilibrium point of both markets. Index Terms-- Bilateral electricity market, Oligopolistic market, Oligopsonistic market, Conjectural Variation Equilibrium method, Patternsearch optimization, Game theory, Hierarchical optimization method