1. Distribution of the thermal load of consumers of thermal energy in the heat supply system between sources of thermal energy supplying thermal energy in this heat supply system, is carried out by an authority authorized in accordance with this federal law for approval of the heat supply scheme, by making annual changes to the heat supply scheme.
2. In order to distribute the heat load of consumers of thermal energy, all heat supply organizations that own sources of thermal energy in this heat supply system are required to submit to the body authorized in accordance with this Federal Law to approve the heat supply scheme, an application containing information:
1) on the amount of heat energy that the heat supply organization undertakes to supply to consumers and heat supply organizations in this heat supply system;
2) on the amount of capacity of thermal energy sources, which the heat supply organization undertakes to maintain;
3) on current tariffs in the field of heat supply and predicted specific variable costs for the production of thermal energy, heat carrier and power maintenance.
3. The heat supply scheme should define the conditions under which it is possible to supply thermal energy to consumers from various sources of thermal energy while maintaining the reliability of heat supply. In the presence of such conditions, the distribution of heat load between sources of heat energy is carried out on a competitive basis in accordance with the criterion of minimum specific variable costs for the production of thermal energy by sources of thermal energy, determined in accordance with the procedure established by the pricing bases in the field of heat supply, approved by the Government Russian Federation, on the basis of applications from organizations that own sources of thermal energy, and standards taken into account when regulating tariffs in the field of heat supply for the corresponding period of regulation.
4. If the heat supply organization does not agree with the distribution of the heat load carried out in the heat supply scheme, it has the right to appeal against the decision on such distribution, taken by the body authorized in accordance with this Federal Law to approve the heat supply scheme, to the federal executive body authorized by the Government of the Russian Federation.
5. Heat supply organizations and heat network organizations operating in the same heat supply system, annually before the start of the heating period, are required to conclude an agreement between themselves on the management of the heat supply system in accordance with the rules for organizing heat supply, approved by the Government of the Russian Federation.
6. The subject of the agreement specified in part 5 of this article is the procedure for mutual actions to ensure the functioning of the heat supply system in accordance with the requirements of this Federal Law. Mandatory conditions said agreement are:
1) determining the subordination of dispatching services of heat supply organizations and heat network organizations, the procedure for their interaction;
2) the procedure for organizing the adjustment of heat networks and regulating the operation of the heat supply system;
3) the procedure for ensuring access of the parties to the agreement or, by mutual agreement of the parties to the agreement, to another organization to heat networks for the adjustment of heat networks and regulation of the operation of the heat supply system;
4) the procedure for interaction between heat supply organizations and heat network organizations in emergency situations and emergencies.
7. If the heat supply organizations and heat network organizations have not concluded the agreement specified in this article, the procedure for managing the heat supply system is determined by the agreement concluded for the previous heating period, and if such an agreement has not been concluded earlier, the specified procedure is established by the body authorized in accordance with this Federal law for approval of the heat supply scheme.
As part of the supply of switchboard equipment, power cabinets and control cabinets for two buildings (ITP) were supplied. For the reception and distribution of electricity in heating points, input-distributing devices are used, consisting of five panels each (10 panels in total). Switching switches, surge arresters, ammeters and voltmeters are installed in the input panels. ATS panels in ITP1 and ITP2 are implemented on the basis of automatic transfer units. Protection and switching devices (contactors, soft starters, buttons and lamps) are installed in the distribution panels of the ASU technological equipment thermal points. All circuit breakers are equipped with status contacts signaling an emergency shutdown. This information is transmitted to the controllers installed in the automation cabinets.
To control and manage the equipment, OWEN PLC110 controllers are used. They are connected to the input / output modules ARIES MV110-224.16DN, MV110-224.8A, MU110-224.6U, as well as operator touch panels.
The coolant is introduced directly into the ITP room. Water supply for hot water supply, heating and heat supply of air heaters of air ventilation systems is carried out with a correction according to the outside air temperature.
The display of technological parameters, accidents, equipment status and dispatch control of the ITP is carried out from the workstation of dispatchers in the integrated central control room of the building. On the dispatching server, the archive of technological parameters, accidents, and the state of the ITP equipment is stored.
Automation of heat points provides for:
- maintaining the temperature of the coolant supplied to the heating and ventilation systems in accordance with the temperature schedule;
- maintaining the temperature of the water in the DHW system at the supply to consumers;
- programming of various temperature regimes by hours of the day, days of the week and public holidays;
- control of compliance with the values of parameters determined by the technological algorithm, support of technological and emergency parameters limits;
- temperature control of the heat carrier returned to the heating network of the heat supply system, according to a given temperature schedule;
- outside air temperature measurement;
- maintaining a given pressure drop between the supply and return pipelines of ventilation and heating systems;
- control of circulation pumps according to a given algorithm:
- on/off;
- control of pumping equipment with frequency drives according to signals from PLC installed in automation cabinets;
- periodic switching main / reserve to ensure the same operating time;
- automatic emergency transfer to the standby pump according to the control of the differential pressure sensor;
- automatic maintenance of a given differential pressure in heat consumption systems.
- control of heat carrier control valves in primary consumer circuits;
- control of pumps and valves for feeding circuits of heating and ventilation;
- setting the values of technological and emergency parameters through the dispatching system;
- control of drainage pumps;
- control of the state of electrical inputs by phases;
- synchronization of the controller time with the common time of the dispatching system (SOEV);
- start-up of equipment after restoration of power supply in accordance with a given algorithm;
- sending emergency messages to the dispatching system.
Information exchange between automation controllers and the upper level (workstation with specialized MasterSCADA dispatching software) is carried out using the Modbus/TCP protocol.
Rice. 6. Two-wire line with two corona wires at different distances between them
16 m; 3 - bp = 8 m; 4 - b,
BIBLIOGRAPHY
1. Efimov B.V. Storm waves in air lines. Apatity: Publishing House of the KSC RAS, 2000. 134 p.
2. Kostenko M.V., Kadomskaya K.P., Levinshgein M.L., Efremov I.A. Overvoltage and protection against them in
high voltage overhead and cable power lines. L.: Nauka, 1988. 301 p.
A.M. Prokhorenkov
METHODS FOR BUILDING AN AUTOMATED SYSTEM OF DISTRIBUTED HEAT SUPPLY CONTROL OF THE CITY
The issues of introducing resource-saving technologies in modern Russia given considerable attention. These issues are especially acute in the regions of the Far North. Fuel oil for urban boiler houses is fuel oil, which is delivered by rail from the central regions of Russia, which significantly increases the cost of generated thermal energy. Duration
The heating season in the conditions of the Arctic is 2-2.5 months longer than in the central regions of the country, which is associated with the climatic conditions of the Far North. At the same time, heat and power enterprises must generate the necessary amount of heat in the form of steam, hot water under certain parameters (pressure, temperature) to ensure the vital activity of all urban infrastructures.
Reducing the cost of generating heat supplied to consumers is possible only through economical combustion of fuel, rational use electricity for own needs enterprises, minimizing heat losses in the areas of transportation (city heating networks) and consumption (buildings, city enterprises), as well as reducing the number service personnel in production areas.
The solution of all these problems is possible only through the introduction of new technologies, equipment, technical means management to ensure economic efficiency work of thermal power enterprises, as well as to improve the quality of management and operation of thermal power systems.
Formulation of the problem
One of important tasks in the field of urban heating - the creation of heat supply systems with parallel operation of several heat sources. Modern systems district heating systems of cities have developed as very complex, spatially distributed systems with closed circulation. As a rule, consumers do not have the property of self-regulation, the distribution of the coolant is carried out by preliminary installation of specially designed (for one of the modes) constant hydraulic resistances [1]. In this regard, the random nature of the selection of thermal energy by consumers of steam and hot water leads to dynamically complex transient processes in all elements of a thermal power system (TPP).
Operational control of the state of remote facilities and control of equipment located at controlled points (CP) are impossible without the development of an automated system for dispatch control and management of central heating points and pumping stations(ASDK and U TsTP and NS) of the city. Therefore, one of actual problems is the management of thermal energy flows, taking into account hydraulic characteristics both the heating networks themselves and energy consumers. It requires solving problems related to the creation of heat supply systems, where in parallel
Several heat sources (thermal stations - TS)) operate on the general heat network of the city and on the general heat load schedule. Such systems make it possible to save fuel during heating, increase the degree of loading of the main equipment, and operate boiler units in modes with optimal efficiency values.
Problem solving optimal control technological processes heating boiler house
To solve the problems of optimal control of technological processes of the heating boiler house "Severnaya" of the State Regional Thermal Power Enterprise (GOTEP) "TEKOS", within the framework of a grant from the Import Program for Energy-Saving and Environmental Protection Equipment and Materials (PIEPOM) of the Russian-American Committee, equipment was supplied (funded by the US government). This equipment and designed for it software made it possible to solve a wide range of reconstruction tasks at the base enterprise GOTEP "TEKOS", and the results obtained - to replicate to the heat and power enterprises of the region.
The basis for the reconstruction of control systems for TS boiler units was the replacement of obsolete automation tools of the central control panel and local systems automatic control to a modern microprocessor distributed control system. The implemented distributed control system for boilers based on the microprocessor system (MPS) TDC 3000-S (Supper) from Honeywell provided a single integrated solution for the implementation of all system functions for controlling technological processes of the TS. The operated MPS has valuable qualities: simplicity and visibility of the layout of control and operation functions; flexibility in fulfilling all the requirements of the process, taking into account reliability indicators (working in the "hot" standby mode of the second computer and USO), availability and efficiency; easy access to all system data; ease of change and expansion of service functions without feedback on the system;
improved quality of presentation of information in a form convenient for decision-making (friendly intelligent operator interface), which helps to reduce errors of operational personnel in the operation and control of TS processes; computer creation APCS documentation; increased operational readiness of the object (the result of self-diagnostics of the control system); promising system with a high degree of innovation. In the TDC 3000 - S system (Fig. 1) it is possible to connect external PLC controllers from other manufacturers (this possibility is implemented if there is a PLC gateway module). Information from PLC controllers is displayed
It is displayed in the TOC as an array of points available for reading and writing from user programs. This makes it possible to use distributed I/O stations installed in close proximity to controlled objects for data collection and transfer data to TOC via an information cable using one of the standard protocols. This option allows you to integrate new control objects, including automated system dispatching control and management of central heating points and pumping stations (ASDKiU TsTPiNS), to the existing automated process control system of the enterprise without external changes for users.
local computer network
Universal stations
Computer Applied Historical
gateway module module
The local network management
Backbone gateway
I Reserve (ARMM)
Enhancement Module. Advanced Process Manager (ARMM)
Universal control network
I/O controllers
Cable routes 4-20 mA
I/O station SIMATIC ET200M.
I/O controllers
PLC network devices (PROFIBUS)
Cable routes 4-20 mA
Flow sensors
Temperature sensors
Pressure Sensors
Analyzers
Regulators
Frequency stations
gate valves
Flow sensors
Temperature sensors
Pressure Sensors
Analyzers
Regulators
Frequency stations
gate valves
Rice. 1. Collecting information by distributed PLC stations, transferring it to the TDC3000-S for visualization and processing, followed by the issuance of control signals
The conducted experimental studies have shown that the processes occurring in the steam boiler in the operating modes of its operation are of a random nature and are non-stationary, which is confirmed by the results of mathematical processing and statistical analysis. Taking into account the random nature of the processes occurring in the steam boiler, estimates of the shift of the mathematical expectation (MO) M(t) and dispersion 5 (?) along the main coordinates of control are taken as a measure of assessing the quality of control:
Em, (t) 2 MZN (t) - MrN (t) ^ gMix (t) ^ min
where Mzn(t), Mmn(t) are the set and current MO of the main adjustable parameters of the steam boiler: the amount of air, the amount of fuel, and the steam output of the boiler.
s 2 (t) = 8|v (t) - q2N (t) ^ s^ (t) ^ min, (2)
where 52Tn, 5zn2(t) are the current and set variances of the main controlled parameters of the steam boiler.
Then the control quality criterion will have the form
Jn = I [avMy(t) + ßsö;, (t)] ^ min, (3)
where n = 1,...,j; - ß - weight coefficients.
Depending on the operating mode of the boiler (regulating or basic), a optimal strategy management.
For the control mode of operation of the steam boiler, the control strategy should be aimed at maintaining the pressure in the steam collector constant, regardless of the steam consumption by heat consumers. For this mode of operation, the estimate of the displacement of the steam pressure in the main steam header in the form
ep (/) = Pz(1) - Pm () ^B^ (4)
where VD, Pt(0 - set and current average values of steam pressure in the main steam header.
The displacement of steam pressure in the main steam collector by dispersion, taking into account (4), has the form
(0 = -4r(0 ^^ (5)
where (UrzOO, art(0 - given and current pressure dispersions.
Fuzzy logic methods were used to adjust the transfer coefficients of the regulators of the circuits of the multi-connected boiler control system.
During the pilot operation of automated steam boilers, statistical material was accumulated, which made it possible to obtain comparative (with the operation of non-automated boiler units) characteristics of the technical and economic efficiency of introducing new methods and controls and to continue reconstruction work on other boilers. So, for the period of semi-annual operation of non-automated steam boilers No. 9 and 10, as well as automated steam boilers No. 13 and 14, the results were obtained, which are presented in Table 1.
Determination of parameters for optimal loading of a thermal plant
To determine the optimal load of the vehicle, it is necessary to know the energy characteristics of their steam generators and the boiler house as a whole, which are the relationship between the amount of fuel supplied and the heat received.
The algorithm for finding these characteristics includes the following steps:
Table 1
Boiler performance indicators
Name of indicator Value of indicators for milking boilers
№9-10 № 13-14
Heat generation, Gcal Fuel consumption, t Specific rate of fuel consumption for the generation of 1 Gcal of thermal energy, kg of reference fuel cal 170,207 20,430 120.03 217,626 24,816 114.03
1. Determination of the thermal performance of boilers for various load modes of their operation.
2. Determination of heat losses A () taking into account the efficiency of boilers and their payload.
3. Determination of the load characteristics of boiler units in the range of their change from the minimum allowable to the maximum.
4. Based on the change in the total heat losses in steam boilers, the determination of their energy characteristics, reflecting the hourly consumption of standard fuel, according to the formula 5 = 0.0342 (0, + AC?).
5. Obtaining the energy characteristics of boiler houses (TS) using the energy characteristics of boilers.
6. Forming, taking into account the energy characteristics of the TS, control decisions on the sequence and order of their loading during the heating period, as well as in the summer season.
Another important issue of organizing the parallel operation of sources (TS) is the determination of factors that have a significant impact on the load of boiler houses, and the tasks of the heat supply management system to provide consumers with the necessary amount of heat energy when possible. minimal cost for its production and transmission.
The solution of the first problem is carried out by linking the supply schedules with the schedules of heat use by means of a system of heat exchangers, the solution of the second one is by establishing the correspondence between the heat load of consumers and its production, i.e., by planning the change in load and reducing losses in the transmission of heat energy. Ensuring the linking of schedules for the supply and use of heat should be carried out through the use of local automation at intermediate stages from sources of thermal energy to its consumers.
To solve the second problem, it is proposed to implement the functions of estimating the planned load of consumers, taking into account the economically justified possibilities of energy sources (ES). Such an approach is possible using situational control methods based on the implementation of fuzzy logic algorithms. The main factor that has a significant impact on
the heat load of boiler houses is that part of it that is used for heating buildings and for hot water supply. The average heat flow (in Watts) used for heating buildings is determined by the formula
where / from - average temperature outside air for certain period; r( - the average temperature of the indoor air of the heated room (the temperature that must be maintained at a given level); / 0 - the estimated outdoor air temperature for heating design;<70 - укрупненный показатель максимального теплового потока на отопление жилых и общественных зданий в Ваттах на 1 м площади здания при температуре /0; А - общая площадь здания; Кх - коэффициент, учитывающий тепловой поток на отопление общественных зданий (при отсутствии конкретных данных его можно считать равным 0,25).
It can be seen from formula (6) that the heat load on the heating of buildings is determined mainly by the outside air temperature.
The average heat flow (in Watts) for hot water supply of buildings is determined by the expression
1.2w(a + ^)(55 - ^) p
Yt „. " _ With"
where m is the number of consumers; a - the rate of water consumption for hot water supply at a temperature of +55 ° C per person per day in liters; b - the rate of water consumption for hot water supply consumed in public buildings at a temperature of +55 ° C (assumed to be 25 liters per day per person); c is the heat capacity of water; /x - temperature of cold (tap) water during the heating period (assumed to be +5 °C).
Analysis of expression (7) showed that when calculating the average heat load on hot water supply, it turns out to be constant. The real extraction of thermal energy (in the form of hot water from the tap), in contrast to the calculated value, is random, which is associated with an increase in the analysis of hot water in the morning and evening, and a decrease in the selection during the day and night. On fig. 2, 3 shows graphs of change
Oil 012 013 014 015 016 017 018 019 1 111 112 113 114 115 116 117 118 119 2 211 212 213 214 215 216 217 218 219 3 311 312 31 3 314 315 316 317
days of the month
Rice. 2. Graph of changes in water temperature in the CHP N9 5 (7 - direct boiler water,
2 - direct quarterly, 3 - water for hot water supply, 4 - reverse quarterly, 5 - return boiler water) and outdoor air temperatures (6) for the period from February 1 to February 4, 2009
pressure and temperature of hot water for TsTP No. 5, which were obtained from the archive of SDKi U TsTP and NS of Murmansk.
With the onset of warm days, when the ambient temperature does not drop below +8 °C for five days, the heating load of consumers is turned off and the heating network works for the needs of hot water supply. The average heat flow to the hot water supply during the non-heating period is calculated by the formula
where is the temperature of cold (tap) water during the non-heating period (assumed to be +15 °С); p - coefficient taking into account the change in the average water consumption for hot water supply in the non-heating period in relation to the heating period (0.8 - for the housing and communal sector, 1 - for enterprises).
Taking into account formulas (7), (8), heat load graphs of energy consumers are calculated, which are the basis for constructing tasks for the centralized regulation of the supply of thermal energy of the TS.
Automated system of dispatching control and management of central heating points and pumping stations of the city
A specific feature of the city of Murmansk is that it is located on a hilly area. The minimum elevation is 10 m, the maximum is 150 m. In this regard, the heating networks have a heavy piezometric graph. Due to the increased water pressure in the initial sections, the accident rate (pipe ruptures) increases.
For operational control of the state of remote objects and control of equipment located at controlled points (CP),
Rice. Fig. 3. Graph of water pressure change in central heating station N° 5 for the period from February 1 to February 4, 2009: 1 - hot water supply, 2 - direct boiler water, 3 - direct quarterly, 4 - reverse quarterly,
5 - cold, 6 - return boiler water
was developed by ASDKiUCTPiNS of the city of Murmansk. Controlled points, where telemechanics equipment was installed during the reconstruction works, are located at a distance of up to 20 km from the head enterprise. Communication with the telemechanics equipment at the CP is carried out via a dedicated telephone line. Central boiler rooms (CTPs) and pumping stations are separate buildings in which technological equipment is installed. The data from the control panel are sent to the control room (in the dispatcher's PCARM) located on the territory of the Severnaya TS of the TEKOS enterprise, and to the TS server, after which they become available to users of the enterprise's local area network to solve their production problems.
In accordance with the tasks solved with the help of ASDKiUTSTPiNS, the complex has a two-level structure (Fig. 4).
Level 1 (upper, group) - dispatcher console. The following functions are implemented at this level: centralized control and remote control of technological processes; display of data on the display of the control panel; formation and issuance of
even documentation; formation of tasks in the automated process control system of the enterprise for managing the modes of parallel operation of the city's thermal stations for the general city heat network; access of users of the local network of the enterprise to the database of the technological process.
Level 2 (local, local) - CP equipment with sensors placed on them (alarms, measurements) and final actuating devices. At this level, the functions of collecting and primary processing of information, issuing control actions on actuators are implemented.
Functions performed by ASDKiUCTPiNS of the city
Information functions: control of readings of pressure sensors, temperature, water flow and control of the state of actuators (on/off, open/close).
Control functions: control of network pumps, hot water pumps, other technological equipment of the gearbox.
Visualization and registration functions: all information parameters and signaling parameters are displayed on the trends and mnemonic diagrams of the operator station; all information
PC workstation of the dispatcher
Adapter SHV/K8-485
Dedicated telephone lines
KP controllers
Rice. 4. Block diagram of the complex
parameters, signaling parameters, control commands are registered in the database periodically, as well as in cases of state change.
Alarm functions: power outage at the gearbox; activation of the flooding sensor at the checkpoint and security at the checkpoint; signaling from sensors of limiting (high/low) pressure in pipelines and transmitters of emergency changes in the state of actuators (on/off, open/close).
The concept of a decision support system
A modern automated process control system (APCS) is a multi-level human-machine control system. The dispatcher in a multilevel automated process control system receives information from a computer monitor and acts on objects located at a considerable distance from it, using telecommunication systems, controllers, and intelligent actuators. Thus, the dispatcher becomes the main character in the management of the technological process of the enterprise. Technological processes in thermal power engineering are potentially dangerous. So, for thirty years, the number of recorded accidents doubles approximately every ten years. It is known that in the steady state modes of complex energy systems, errors due to inaccuracy of the initial data are 82-84%, due to the inaccuracy of the model - 14-15%, due to the inaccuracy of the method - 2-3%. Due to the large share of the error in the initial data, there is also an error in the calculation of the objective function, which leads to a significant area of uncertainty when choosing the optimal mode of operation of the system. These problems can be eliminated if we consider automation not just as a way to replace manual labor directly in production management, but as a means of analysis, forecasting and control. The transition from dispatching to a decision support system means a transition to a new quality - an intelligent information system of an enterprise. Any accident (except natural disasters) is based on human (operator) error. One of the reasons for this is the old, traditional approach to building complex control systems, focused on the use of the latest technology.
scientific and technological achievements while underestimating the need to use situational management methods, methods of integrating control subsystems, as well as building an effective human-machine interface focused on a person (dispatcher). At the same time, it is envisaged to transfer the functions of the dispatcher for data analysis, forecasting situations and making appropriate decisions to the components of intelligent decision support systems (ISDS) . The SPID concept includes a number of tools united by a common goal - to promote the adoption and implementation of rational and effective management decisions. SPPIR is an interactive automated system that acts as an intelligent intermediary that maintains a natural language user interface with a 3CAOA system and uses decision rules that correspond to the model and base. Along with this, the SPPIR performs the function of automatic tracking of the dispatcher at the stages of information analysis, recognition and forecasting of situations. On fig. Figure 5 shows the structure of the SPPIR, with the help of which the TS dispatcher manages the heat supply of the microdistrict.
Based on the above, several fuzzy linguistic variables can be identified that affect the load of the TS, and, consequently, the operation of heat networks. These variables are given in Table. 2.
Depending on the season, time of day, day of the week, as well as the characteristics of the external environment, the situation assessment unit calculates the technical condition and the required performance of thermal energy sources. This approach allows solving the problems of fuel economy in district heating, increasing the degree of loading of the main equipment, and operating boilers in modes with optimal efficiency values.
The construction of an automated system for distributed control of the heat supply of the city is possible under the following conditions:
introduction of automated control systems for boiler units of heating boiler houses. (Implementation of automated process control systems at the TS "Severnaya"
Rice. 5. The structure of the SPPIR of the heating boiler house of the microdistrict
table 2
Linguistic variables determining the load of a heating boiler house
Notation Name Range of values (universal set) Terms
^month Month January to December Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov , "dec"
T-week Day of the week working or weekend "working", "holiday"
TSug Time of day from 00:00 to 24:00 "night", "morning", "day", "evening"
t 1 n.v Outside air temperature from -32 to +32 ° С "lower", "-32", "-28", "-24", "-20", "-16", "-12", "-8", "^1", "0", "4", "8", "12", "16", "20", "24", "28", "32", "above"
1" in Wind speed from 0 to 20 m/s "0", "5", "10", "15", "higher"
provided a reduction in the specific fuel consumption rate for boilers No. 13.14 compared to boilers No. 9.10 by 5.2%. Energy savings after the installation of frequency vector converters on the drives of fans and smoke exhausters of boiler No. 13 amounted to 36% (specific consumption before reconstruction - 3.91 kWh/Gcal, after reconstruction - 2.94 kWh/Gcal, and
No. 14 - 47% (specific electricity consumption before reconstruction - 7.87 kWh/Gcal., after reconstruction - 4.79 kWh/Gcal));
development and implementation of ASDKiUCTPiNS of the city;
introduction of information support methods for TS operators and ASDKiUCTPiNS of the city using the concept of SPPIR.
BIBLIOGRAPHY
1. Shubin E.P. The main issues of designing urban heat supply systems. M.: Energy, 1979. 360 p.
2. Prokhorenkov A.M. Reconstruction of heating boiler houses on the basis of information and control complexes // Nauka proizvodstvo. 2000. No. 2. S. 51-54.
3. Prokhorenkov A.M., Sovlukov A.S. Fuzzy models in control systems of boiler aggregate technological processes // Computer Standards & Interfaces. 2002 Vol. 24. P. 151-159.
4. Mesarovich M., Mako D., Takahara Y. Theory of hierarchical multilevel systems. M.: Mir, 1973. 456 p.
5. Prokhorenkov A.M. Methods for identification of random process characteristics in information processing systems // IEEE Transactions on instrumentation and measurement. 2002 Vol. 51, N° 3. P. 492-496.
6. Prokhorenkov A.M., Kachala H.M. Random Signal Processing in Digital Industrial Control Systems // Digital Signal Processing. 2008. No. 3. S. 32-36.
7. Prokhorenkov A.M., Kachala N.M. Determination of the classification characteristics of random processes // Measurement Techniques. 2008 Vol. 51, No. 4. P. 351-356.
8. Prokhorenkov A.M., Kachala H.M. Influence of classification characteristics of random processes on the accuracy of processing measurement results // Izmeritelnaya tekhnika. 2008. N° 8. S. 3-7.
9. Prokhorenkov A.M., Kachala N.M., Saburov I.V., Sovlukov A.S. Information system for analysis of random processes in nonstationary objects // Proc. of the Third IEEE Int. Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS "2005). Sofia, Bulgaria. 2005. P. 18-21.
10. Methods of Robust Neuro-Fuzzy and Adaptive Control, Ed. N.D. Yegupova // M.: Publishing house of MSTU im. N.E. Bauman, 2002". 658 p.
P. Prokhorenkov A.M., Kachala N.M. Effectiveness of adaptive algorithms for tuning regulators in control systems subjected to the influence of random disturbances // BicrniK: Scientific and Technical. well. Special issue. Cherkasy State Technol. un-t.-Cherkask. 2009. S. 83-85.
12. Prokhorenkov A.M., Saburov I.V., Sovlukov A.S. Data maintenance for processes of decision-making under industrial control // BicrniK: scientific and technical. well. Special issue. Cherkasy State Technol. un-t. Cherkask. 2009. S. 89-91.
Heat supply features are the rigid mutual influence of heat supply and heat consumption modes, as well as the multiplicity of supply points for several goods (thermal energy, power, coolant, hot water). The purpose of heat supply is not to provide generation and transport, but to maintain the quality of these goods for each consumer.
This goal was achieved relatively effectively with stable coolant flow rates in all elements of the system. The “quality” regulation we use, by its very nature, implies changing only the temperature of the coolant. The emergence of demand-controlled buildings ensured the unpredictability of hydraulic regimes in networks while maintaining the constancy of costs in the buildings themselves. Complaints in the neighboring houses had to be eliminated by excessive circulation and the corresponding mass overflows.
The hydraulic calculation models used today, despite their periodic calibration, cannot provide for accounting for deviations in costs at building inputs due to changes in internal heat generation and hot water consumption, as well as the influence of sun, wind and rain. With the actual qualitative-quantitative regulation, it is necessary to “see” the system in real time and provide:
- control of the maximum number of delivery points;
- reconciliation of current balances of supply, losses and consumption;
- control action in case of unacceptable violation of modes.
Management should be as automated as possible, otherwise it is simply impossible to implement it. The challenge was to achieve this without undue expense of setting up checkpoints.
Today, when in a large number of buildings there are measuring systems with flow meters, temperature and pressure sensors, it is unreasonable to use them only for financial calculations. ACS "Teplo" is built mainly on the generalization and analysis of information "from the consumer".
When creating the automated control system, typical problems of outdated systems were overcome:
- dependence on the correctness of calculations of metering devices and the reliability of data in unverifiable archives;
- the impossibility of bringing together operational balances due to inconsistencies in the time of measurements;
- inability to control rapidly changing processes;
- non-compliance with the new information security requirements of the federal law "On the Security of the Critical Information Infrastructure of the Russian Federation".
Effects from the implementation of the system:
Consumer Services:
- determination of real balances for all types of goods and commercial losses:
- determination of possible off-balance sheet income;
- control of actual power consumption and its compliance with technical specifications for connection;
- introduction of restrictions corresponding to the level of payments;
- transition to a two-part tariff;
- monitoring KPIs for all services working with consumers and assessing the quality of their work.
Exploitation:
- determination of technological losses and balances in heat networks;
- dispatching and emergency control according to actual modes;
- maintaining optimal temperature schedules;
- monitoring the state of networks;
- adjustment of heat supply modes;
- control of shutdowns and violations of modes.
Development and investment:
- reliable assessment of the results of the implementation of improvement projects;
- assessment of the effects of investment costs;
- development of heat supply schemes in real electronic models;
- optimization of diameters and network configuration;
- reduction of connection costs, taking into account the real reserves of bandwidth and energy savings for consumers;
- renovation planning
- organization of joint work of CHP and boiler houses.
