PREFERENCE AGGREGATION IN INTERPRETATION OF ENERGY SURVEY DATA

Abstract

The relevance of the research is caused by the fact that systematic energy surveys of power networks to identify possible energy loss is the basis for energy saving and energy efficiency. Energy survey data processing is a work with large volume of unstructured data that is difficult to fully account. The main aim of the paper is to solve the problem of energy survey data processing on the base of preference aggregation approach, which will enable efficient data compression preventing the loss of useful information and provide clear visualization of energy audit results. The Backbone Electric Grids (BEGs), being a part of the Unified National Electric Network of Russia are considered as the object of the research. The Backbone Electric Grids, in their turn, consist of the Enterprises of Backbone Electric Grids, each of which may unite a large number of substations. Annual energy survey data of Russian Backbone Electric Grids are included in the database of the Federal Grid Company of Unified Energy System. Methods. The authors propose the method, based on the preference aggregation, which allow obtaining and representing a great amount of data of instrumental survey of substation energy losses in a form of a compact integral estimate in the ordinal scale convenient for rapid decision making and visualization. Application of the proposed method to processing energy survey data of real backbone electric grids of Russia is discussed in the paper. Results. The method makes it possible to identify sources of economically inefficient expenditure of energy resources and unjustified energy losses, and also to provide compression of large volumes of energy survey data without diminution of essential information. The proposed method can be an appropriate and promising tool for organizations engaged in energy consulting.

Keywords

• Energy audit
• losses of electrical energy
• preferences aggregation
• consensus ranking
• Kemeny rule.