Annotation. The article discusses the possibility of developing a model of the process of controlling the parameters of the functioning of a steam generating unit of small-scale power generation based on the use of fuzzy logic methods in conditions of uncertainty for the optimal distribution of raw materials and fuel and energy resources. Introduction.Currently, the fuel and energy complex (FEC) is in the process of carrying out new structural transformations. In remote areas of Siberia, the Far East, the Far North, economic development is being held back. The reason for this is the lack of a reliable heating and power supply. A significant limitation in energy resources hinders the economic and social development of these regions of the country. This can be solved by developing small-scale power generation for the production of electricity and heat to provide the population of remote areas using a steam generator unit (SGU) with automated control of the optimal distribution of raw materials and fuel and energy resources.A functional model of optimal resource allocation has been developed, the main functions and interrelationships of control modules have been determined. The model consists of the following modules: the module for calculating the parameters, the module for setting the operating conditions of the SGU unit, the module for solving the optimization problem, the module for analyzing the results obtained and issuing recommendations for optimizing the parameters of the SGU unit operation.
1. Module for calculating parameters.1.1 Calculation of parameters characterizing thermal, gas-dynamic and other modes of SGU operation. The estimation of the parameters should be carried out using the balance model of the process developed within the framework of the natural-model approach, which can be conditionally divided into two parts: the base state model and the predictive model. The model of the base (reference) state makes it possible to assess the state of the SGU unit and the influence of the input parameters on the thermal, gas-dynamic and other modes using all actually available information about the process parameters. 2. Module for setting the operating conditions of the SGU.
2.1 Planned average consumption of fuel, water and steam, electricity.2.2 Restrictions for the SGU unit on the supply of raw materials, fuel consumption, steam, electricity. 2.3 Technological limitations of SGU.3. Module for solving the optimization problem.
3.1 Selection of the optimal consumption of raw materials. 3.2 Selection of the optimal consumption of fuel and energy resources. 3.3 Selection of the optimum temperature, pressure and other parameters of steam generation for the normal operation of the SGU.4. Module for analyzing the results obtained.
The structure of the control model of the control process with optimal resource allocation is shown in Fig.1.Investigation of the control process under conditions of uncertainty.The peculiarities of the process of fuzzy control of the functioning of the SGU are built on the principles of fuzzy logic, the concepts of the theory of fuzzy sets for control under conditions of uncertainty in the absence of complete information.Selection of mathematical control methods for various types of uncertainty:the type of data uncertainty about the control object;type of model (linguistic and expert);mathematical methods of formalizing uncertainty: methods of the theory of fuzzy sets, methods of decision-making, fuzzy logic, situational control.
A control model scheme based on fuzzy control regulates a certain number of parameters and is shown in Fig. 2.A fuzzy inference model is proposed that contains 4 input and 4 output linguistic variables. The controlled input variables are the volumes of supplied resources (fuel, water, electricity, fuels and lubricants).The resulting output parameters are the optimal values of the generated resources (electrical power, water heating temperature of systems, cooling temperature). The possibility of using fuzzy control to create a model of the process of fuzzy control of the SGU operation was considered to regulate a certain number of input parameters to minimize costs and obtain the maximum output resource.
In the presented work, a model for controlling the functioning of a SGU unit is considered, which is built on the principles of fuzzy logic, the concepts of the theory of fuzzy sets and situational control in conditions of uncertainty, conditions of uncertainty and changes in functioning parameters. It is proposed to use fuzzy situational control to solve this problem.
|Affiliation of speaker||Graduate student|
|Position of speaker||Graduate student|
|Publication||International journal «Resource-Efficient Technologies»|