Competitive Electricity Markets are based on a set of hypotheses which sustain a vertical and horizontal segmentation of the generation, transmission and distribution sectors in different functions In Argentina, this theoretical model was implemented in a Wholesale Electricity Market (WEM) and its operation for more than a decade produced a great amount of data which are analyzed by Public Authorities to make further decisions Proposals regarding reforms in the design of the Argentinean WEM should be based on a deep knowledge of the influence exerted by different factors connected with the main technological and economic WEM parameters Consequently, it is important to have methodologies and statistical techniques to help Public Authorities make decisions This paper presents the application of the methodology of analysis of variance of multivariate data (MANOVA) to detect the influence that days and months exert on the spot price (or market price) in the Argentinean WEM A fixed-effect with two factors model (seven-level factor for days and a twelve-level factor for months) is used

Using MANOVA Methodology in a Competitive Electric Market under Uncertainties

electricity market has been restructuring throughout the world for maximum utilisation of resources and the system is expended to maximise social welfare. Economic gains based on regional cooperation in the energy sector have become a firmly established practice across the world. In this paper we have proposed a JAVA based power trading simulator that will estimate market clearing price. A careful study of the existing models is to be carried out to evolve a model in JAVA, which is easy to adopt, sustain and to take care of existing participants. The demand is fixed and supply side bidding scenarios with case studies are presented in the paper. This simulator having 5 generators will bid for 24 hrs in single sided auction market. This paper presents a successful JAVA base MCP simulator which can be used in Power Exchange to find out MCP and MCV without any problem. Users get familiar with all the steps that a power producer must perform to generate successful bids in an electricity pool. Suppliers and consumers bid in a pool: their interactions and communications are simulated on the JAVA platform. The market clearing algorithm is implemented in JAVA. Section II discusses the concept of MCP and power exchange proposed algorithm of the simulator. Section III discusses the existence methodology and Pseudo codes of simulator. Section IV discusses the simulation and numerical results for calculation of MCP and quantity of power allotted to each customer. Finally Section V concludes the paper.

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JAVA based Power Trading Simulator in Electricity Market

Experimental design technique is a powerful tool that is used in uncertainty cases, when a great amount of data is available. In this paper, the effects of different factors on the determination of electricity consumption are analyzed. This analysis is based on experimental design technique. The implementation of the proposed technique is shown applying electricity consumption in Iran.

Analyzing the Electricity Consumption Using Experimental Design Technique

Competitive electricity markets are based on a set of hypotheses which sustains a vertical and horizontal segmentation of the generation, transmission and distribution sectors in different functions. This theoretical model was implemented in several countries and its operation for more than a decade produced a great amount of data which are analyzed by the public authorities to take further decisions. Proposals regarding reforms for this type of markets must be based on a deep knowledge of different factors influence on the market parameters. Consequently, it is important to have methodologies and statistical techniques to help Public Authorities take decisions. In this paper, the application of the methodology of analysis of variance of multivariate data (MANOVA) to detect the impact of the fuel consumption on the market price is presented. A two factors fixed effect model is used; two-level factors for fuel-oil and two-level factors for natural gas. The random variable observed is a vector of twenty-four components which correspond to the 2005 market price in the Argentinean Electricity Market.

Multivariate Analysis of Variance Applied to Competitive Electricity Markets: The Fixed Effects Model

Competitive electricity markets are based on a set of hypotheses which sustains a vertical and horizontal segmentation of the generation, transmission and distribution sectors in different functions. In Argentina, this theoretical model was implemented in a wholesale electricity market (MEM in Spanish) and its operation for more than a decade produced a great amount of data which are analyzed by the Public Authorities to take further decisions. Proposals regarding reforms in the design of the Argentinean MEM must be based on a deep knowledge of the influence exerted by different factors connected with the main technological and economic MEM parameters. Consequently, it is important to have methodologies and statistical techniques which help Public Authorities to take decisions. In this paper, we present the application of the methodology of analysis of variance of data (ANOVA) to detect the influence that Large Users (GUMA in Spanish) has on the Contract (Forward) Market in the Argentinean MEM. A random-effect model of two factors is used: a ten-level factor for Large Users and a four-factor for months. The random variable observed correspond to the Contract Market price in Argentinean MEM during 2.003, 2.004, 2005 and 2.006.

Maximum Likelihood Estimation of Variance Components in a Competitive Electricity Market

Application of an experimental design methodology for economic parameter analysis in an open market environment

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Application of an experimental design methodology for economic parameter analysis in an open market environment