Mircea Scutariu

Customer characterization options for improving the tariff offer

This paper deals with the classification of electricity customers on the basis of their electrical behavior. Starting from an extensive field-measurementbased database of customer daily load diagrams, we searched for the most appropriate indices or sets of indices to be used for customer classification. We propose two original measures to quantify the degree of adequacy of each index. Using the indices as distinguishing features, we adopt an automatic clustering algorithm to form customer classes. Each customer class is then represented by its load profile. We use the load profiles to study the margins left to a distribution company for fixing dedicated tariffs to each customer class. We take into account new degrees of freedom available in the competitive electricity markets, which increase flexibility in the tariff definition under imposed revenue caps. Results of a case study performed on a set of customers of a large distribution company are presented.

Electric energy customer characterisation for developing dedicated market strategies

This paper deals with the classification of the electricity customers for building up dedicated tariff structures based on their electrical behaviour. Starting from the results of field measurements, the load patterns are characterised by a set of indices representing the shape of the load curves. An automatic clustering algorithm is used to form the customer classes. Each customer class is then represented by its load profile. The load profiles are used to study the margins left to the utility company for fixing dedicated tariffs to each customer class, according to new rules introduced in the liberalised electricity market, which increase the flexibility in the definition of the tariffs under imposed price caps. Results of a case study performed on a set of customers of a distribution company are presented.

Customer classification by means of harmonic representation of distinguishing features

This paper deals with grouping electricity customers on the basis of their electrical behavior. We refer to a set of daily load diagrams representing a macro-class of electricity customers defined on the basis of external classification criteria. We investigate on the selection of appropriate features to be used for grouping the customers by means of clustering techniques. We propose a novel characterization of the load diagrams by using a frequency-domain approach in which each customer is represented by a set of harmonics-based features. Assuming the day as fundamental period, we perform harmonic analysis of the representative load diagrams and define a set of shape factors by using magnitude and phase information of a relevant set of harmonics. We discuss some critical aspects of the feature selection, mainly linked to the treatment of the phase information. We show results of application of the proposed method to 232 customers of a real distribution system. Using the proposed harmonics-based features in a load diagram clustering procedure provides effective results, with a slight reduction in adequacy with respect to the use of 15-minute time-domain samples, well compensated by the significant reduction of the number of features used to represent the customer data and to run the clustering procedure.

Efficient iterative refinement clustering for electricity customer classification

Customer classification is aimed at providing to the electricity suppliers a sound information on the electricity consumption, to be used for formulating dedicated tariff structures. Different clustering methods can be adopted for assisting the process of electricity customer classification. Previous studies have identified two methods - hierarchical clustering and follow-the-leader - as most promising in terms of clustering validity for classifying the customers on the basis of the shape of their load patterns. However, the above methods exhibited some limitations in terms of the possibility of preassigning the number of clusters (for the follow-the-leader) or improving the cluster formation by reassigning the load patterns to the clusters already formed (for the hierarchical clustering). This paper presents the new iterative refinement clustering (IRC) method, originally developed in order to overcome these limitations. The performance of the IRC method has been compared to the one of other clustering methods by means of suitable clustering validity indicators. The results obtained on a set of over 200 non-residential customers are presented in the paper to show the effectiveness of the proposed IRC method.

Corrective Maintenance Timetable in Restructured Distribution Environment

Outsourcing of maintenance activities from the core distribution operator business prompted the reorganization of the operations sequence of activities and affects, to some extent, the reliability of the distribution network. Repair times, a major component in the reliability calculations, arrive to a new understanding from operations point of view and the adequacy of established probabilistic representations has to be assessed. This paper proposes a mechanism to identify the layout of the sequence of activities for distribution component repair, resulting from reorganization, and revises the adequate representation of the times associated with various stages of the derived repair process. Statistical-based techniques employing estimates of distribution parameters and hypothesis testing serve to determine probabilistic distributions. The validity of the independence assumption for the random variables associated with individual times which compose the repair time is checked via statistical methods in order to confirm applicability of probabilistic-based calculations. By means of such a mechanism, an objective analysis of the time components of the repair time can be conducted, such as areas of improvement, and can be outlined. The results obtained for a large real power distribution system are presented

The analysis of optimal energy losses in two-windings transformers

Objective needs for the determination of electric energy losses for two-windings transformers from transformer posts (TP) and transformer substations (TS) are presented in this work. The paper proposes an original mathematical model to determine the energy losses of TP or TS, valid for the general case of one or several transformers (identical or different from their rated characteristics point of view) nonsymmetrically loaded due to the intrinsic structure of the supplied consumers. The optimal electric energy losses due to symmetrical and balanced loading are emphasized, as well as the factors that affect these losses (i.e. load curve fill coefficient, form coefficient, etc.) taking into account the variety and etherogenity of the consumers. The proposed mathematical model has been applied for a TP and a comparison between the actual and optimal energy losses has been considered. The case study comes from a Romanian TP, exploited by the ELECTRICA Electric Energy Distribution Subsidiary of Bucharest.

Remedial action timings within restructured distribution business environment

This paper deals with the presentation of the emerging framework of the remedial activities since the outsourcing of maintenance and repair activities from the core distribution utility. The focus is set on evaluation of remedial actions timings resulted from this change, using elements of statistical analysis, and on detection of the inter-relationships between various phases of the repair activities. Traditionally from such analysis the repair rates may be determined for reliability computations, and interest goes on validation of probability density functions fit for representation of the repair process. In addition, given the change of faulted element restoration sequence of activities, an assessment of the impact of various additional delays resulted from the re-organization exhibits gives insights in the opportunities for improvement of the restoration process. The paper provides the identification phase of the restoration/remedial action process, techniques for analysis of the data and results obtained upon a real case study extracted from work experience within the restructured environment of a utility company over a period of six-months. Relevant results of the discussed techniques are presented and possibilities for improvement of the overall process are explored.

Aspects concerning daily load curves modelling by means of probabilistic distributions

This paper deals with the presentation of an approach that can be used to decide whether load data gathered by measurements over a limited period of time can be used to produce probabilistic distributions associated to load models. The key issue of this modelling conduct relies with the random nature of load behaviour and the association of stochastic processes to load demand. Certain properties of the stochastic processes have to be checked for in order to allow the implementation of statistical instruments for determination of distributions. A test case over a limited number of customers is presented and discussions over the results and implementation aspects are provided.

Penalty options for over-compensated reactive energy at medium and small customers level

Reactive power circulation in distribution networks represents a major source for the technological consumption, component of a larger package of performance indices of distribution operators. Tackling the compensation issue, given the current co-existence of various perturbation requires good knowledge of phenomena and this paper tries to summarise authors experience in the field. A discussion upon a potential mathematical model together with a possible algorithm for the assessment and monitoring of over-compensation is provided, giving an insight view on the issue of reactive compensation, which is also presented in the paper.