Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.

Optimal dispatch of spinning reserve in a competitive electricity market using genetic algorithms

Ancillary service plays a key role in maintaining operation security of the power system in a competitive electricity market. The spinning reserve is one of the most important ancillary services that should be provided effectively. This paper presents the design of an integrated market for energy and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the cost of service while maintaining system security. Genetic algorithms (GA) are used for finding the global optimal solutions for this dispatch problem. Case studies and corresponding analyses have been carried out to demonstrate and discuss the efficiency and usefulness of the proposed method.

Investement appraisal in a deregulated electricity market

This thesis analyses the impact of deregulation on the theory and practice of investment decision making in the electricity sector and appraises the likely effects on its long term future inefficiency. Part I describes the market and its shortcomings in promoting an optimal generation margin and plant mix and in reducing prices through competition. A full size operational model is developed to simulate hour by hour operation of the market and analyse its features. A relationship is established between the SMP and plant mix and between the LOLP and plant margin and it is shown bow a theoretical optimum can be derived when the combined LOLP payments and the capital costs of additional generation reach a minimum. A comparison of prices against an idealised bulk supply tariff is used to show how energy prices have risen some 12% in excess of what might have occurred under the CEGB regime. This part concludes with proposals to improve the marlmarket conditions and these are tested against the actual investment decisions since deregulation to demonstrate their appropriateness. It is shown that the current market mechanisms could lead to suboptimal investment. Part 3 discusses the essential role of transmission in enabling competition and reviews worldwide practices illustrating little consensus on charging for its use. Basic costing principles are described and a new model is developed to demonstrate bow a generator may strike supply agreements either side of an interconnector to influence prices so as to maximise his income. The optimal pricing strategy for the transmitter is also derived and consumer response is simulated .The concept of transmission uplift is developed and the operational model is extended to include transmission constraints and then used to establish monthly incremental transmission constraint cost functions. It is shown how these can be used to appraise investment options and optimally plan outages. Part 4 concludes by discussing the regulatory framework and its limitations in improving efficiency or encouraging the optimum levels of investment. The principal findings of the thesis are reviewed and potential market improvement are described. This part concludes with a discussion of alternative market structures and likely future developments.

Organizational change and development:a case study in the Indian electricity market

Five principles for accommodating cultural nuances

Essays on the effect of renewable energy production in the spanish electricity market.

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Short-Term Trading for a Wind-PV Power Producer in an Electricity Market

This paper deals with the problem of coordinated trading of wind and photovoltaic systems in order to find the optimal bid to submit in a pool-based electricity market. The coordination of wind and photovoltaic systems presents uncertainties not only due to electricity market prices, but also with wind and photovoltaic power forecast. Electricity markets are characterized by financial penalties in case of deficit or excess of generation. So, the aim o this work is to reduce these financial penalties and maximize the expected profit of the power producer. The problem is formulated as a stochastic linear programming problem. The proposed approach is validated with real data of pool-based electricity market of Iberian Peninsula.

Market Power in the Spanish Electricity Auction

Published as an article in: Journal of Regulatory Economics, 2010, vol. 37, issue 1, pages 42-69.