Problems of optimizing the energy consumption of households in the tasks of improving the energy efficiency of the housing sector
https://doi.org/10.21686/2500-3925-2018-2-59-68
Abstract
The aim of the work is to study the problem of optimizing energy consumption and practical application of methods for improving energy efficiency in the housing sector. Optimization of energy efficiency management allows to reduce the expenditure of energy resources in the performance of various works, heating of buildings, etc. The creation of optimization methods will make it possible to reduce payments for utilities in a short time, and in general for the industry, will help reduce the consumption of various resources and improve the ecological state of the region. Unlike other approaches, the emphasis in this paper is on the convenience and simplicity necessary for using this technique by the population in households. The proposed integrated approach uses methods of probability theory, linear programming, heat exchange models. The conducted research confirms the effectiveness of the solution obtained and can serve as a basis for the creation of training and research stands. The article consists of two parts: the first part analyzes the leading works in this field and identifies the reasons that make it difficult to apply the solutions proposed in these papers. Further, the statement of the problem was proposed and justified, and a number of basic requirements to the mathematical model of energy consumption, necessary for the constructed technique to be used to optimize energy consumption in households, were formulated. In the second part, a mathematical model of their functioning is proposed using examples of specific household electrical appliances. When researching existing methods for optimizing energy consumption in households, problems were identified that were difficult to apply these methods in practice and recommendations were obtained that allowed to formulate the basic principles of constructing an optimization technique that was convenient for practical application. It was shown that when constructing such a technique, the primary question is the data that the user can provide. The minimum composition of input data was determined, according to which the necessary algorithms for optimizing energy consumption were designed. A number of algorithms for determining some input indicators that are easy to use in households have also been proposed. Thus, the general plan of research in this paper is as follows:
• carry out grouping of devices by the way of setting functional
requirements;
• determine the acceptable composition and type of input data for
the user;
• define the minimum set of input data for formalizing the limitation
of the total power consumption;
• design optimization algorithms that work with the input data
specified above. The most important results of the work performed are the following:
• the methodology for forecasting the graph of the maximum total
power consumption has been developed.
• methods for optimizing energy consumption for each of the selected subsets of household appliances have been developed.
• the optimization algorithms obtained have been simulated, which showed their operability, efficiency and the possibility of their practical application without any adaptation.
Thus, the article proposes the solution of the problem of optimization of energy consumption in the housing sector, oriented to practical application.
About the Authors
G. G. GrebenukRussian Federation
V. A. Trapeznikov Institute of Control Sciences of RAS, Moscow, Russia
S. M. Nikishov
Russian Federation
V. A. Trapeznikov Institute of Control Sciences of RAS, Moscow, Russia
A. A. Krygin
Russian Federation
V. A. Trapeznikov Institute of Control Sciences of RAS, Moscow, Russia
L. A. Sereda
Russian Federation
V. A. Trapeznikov Institute of Control Sciences of RAS, Moscow, Russia
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Review
For citations:
Grebenuk G.G., Nikishov S.M., Krygin A.A., Sereda L.A. Problems of optimizing the energy consumption of households in the tasks of improving the energy efficiency of the housing sector. Statistics and Economics. 2018;15(2):59-68. (In Russ.) https://doi.org/10.21686/2500-3925-2018-2-59-68