employee
University of Cadiz
graduate student
Krasnoyarsk, Russian Federation
Russian Federation
employee
Puerto-Real', Spain
graduate student
University of Cadiz
graduate student
Krasnoyarsk, Russian Federation
The authors applied the Data Envelopment Analysis (DEA) to assess the performance of the heat supply system in the city of Krasnoyarsk. The article provides a detailed description of the DEA method, its positive sides and shortcomings. The research included a comparative analysis of performance assessment methods in terms of advantages and disadvantages. The DEA method proved the most convenient tool for measuring the production efficiency of an object. The authors modified the architecture of the universal decision support system into a DEA-based one. The DEA method also proved highly efficient in assessing the performance of the heat supply system in the city of Krasnoyarsk. The analysis made it possible to develop recommendations to improve the efficiency of the local heat supply system using the case of thirteen unites, e.g. boilers, heat and power plants, etc. The input indicator was represented by the available heat capacity. Heat output to the grid and emission mass were used as output indicators. Based on the available initial data, the authors constructed an output-oriented model for analyzing the functioning environment with one input and two outputs. They identified inefficient units of the Krasnoyarsk heat supply system and proposed optimization of input and output values for each unit to improve the functioning of the heat supply system as a whole. The developed for the upgrading of boilers and heat and power plants had an efficiency index in the range up to 1.
decision support system, model, decision module, linear programming, heat supply system, level of harmful substances emitted, heat output, heat energy supply to the network, mass of emission, environment
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