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Sultanov Murodjon Baxtiyarovich, Scientific and Technical Center Joint Stock Company "Uzbekenergo", Senior scientific researcher-applicant E-mail: [email protected]
MODELS AND ALGORITHMS OF THE OPTIMUM SOLUTION OF THE PROBLEMS OF THE ENERGY MANAGEMENT SYSTEM
Abstract: The article considers models and algorithms for the optimal solution of the tasks of the energy management system. A functional model of the energy management system and algorithms for solving problems of optimal planning, operational accounting, control and regulation of consumption of fuel and energy resources in the production process are given. Models and algorithms of the decision support system for the energy management system are proposed and a general algorithm for the decision support system is presented.
Keywords: method, models, algorithm, process, energy management system, decision making, decision support systems.
In the conditions of constantly growing prices for fuel and energy resources (FER) and the deficit at all oil and gas producing enterprises of the Republic of Uzbekistan, the Energy Management System (EMS) - management and optimization of energy consumption and energy costs - is becoming especially important. Recognizing the importance of energy as a resource that requires the same management as any expensive product is the first step towards improving energy and environmental efficiency. EMS is a constantly operating energy management system that allows to significantly optimize energy consumption, forecast and control the processes of generation, transportation and use of the necessary amount of energy resources to support the economic activities of the facilities. EMS is a complex of interrelated and interacting elements (organizational arrangements, technical means and software and methodological support) aimed at the formation of energy policy, setting goals and developing activities to achieve these goals.
EMS allows management to make operational management decisions aimed at consuming the minimum required amount of fuel and energy resources. The functional model of EMS is shown in Figure 1.
Based on the functional model of EMS, as well as on the basis of a methodology known as the cycle of continuous improvement, the process of energy management can be represented as:
EM = (PN, PP, PIF, PMA, ADM) (l)
where PN is the process of normalizing energy indicators and calculating standards. PP is the process of energy planning and forecasting, PIF is the process of implementing and functioning of EMS tasks, PMA is the process of monitoring and analyzing the functioning of EMS, ADM is analysis by decision makers on continuous improvement of the performance of
EMS in accordance with energy policy. Let us consider the process of solving the EMS functional problems [1].
The process of rationing fuel consumption in EMS. Analysis of the work of oil and gas enterprises of Uzbekistan shows that they have considerable reserves of fuel and energy saving, which should be realized with the aim of increasing energy efficiency. To a large extent, this depends on the effectiveness of economic instruments for increasing energy efficiency, such as rationing energy consumption, energy tariffs, material incentives for energy efficiency, etc. Energy standards should reflect the optimal technological and energy regimes for loading equipment. When developing norms for energy consumption, the following should be taken into account: - equipment performance; - technological parameters, characteristics of raw materials and materials; - graphics of equipment operation during the shift, day, week and month. This is important for accounting for losses during launches, to take into account the possibility of using secondary energy resources and other energy-saving reserves.
Rationing should be aimed not only at saving energy, but also at improving technological processes. For this purpose, rationing should cover all elements of the technological process. For energy-intensive processes, it should be detailed, and for small consumers it is permissible to increase the standardization. When developing norms, energy consumption should be taken into account not only for basic, but also for auxiliary production needs (lighting, heating, ventilation, water supply, etc.).
The norms of energy consumption, as noted earlier, depend on a number of factors, for example, on the level of loading of the main equipment of the enterprise, which can change during the year. In this case, we can talk about the need for differentiation of the norms for the seasons of the year. Decrease in the load can occur due to the decline in
industrial production, due to a decline in market demand for manufactured products. There may be other factors that affect the amount of specific energy consumption. In this case, it is
appropriate to raise the question of the development of energy characteristics, which express the dependence of the specific energy expenditure on these or other factors [2].
1 r
Creation and introduction of databases of Correction of norms and
normative and reference information norms
1 r
Calculation of planned and forecasted indicators Adjustment of planned
of FER consumption and forecasted indicators
1 r
Operational accounting and control of actual indicators of FER consumption
^^ Analysis of the deviation of <T the actual consumption of FER from planned ^^ \ Yes Decision support system
No
Figure 1. Diagram of the functional model of EMS
The process of planning fuel consumption in EMS. The most decisions to achieve the goals set with rational allocations of
important complex tasks in EMS are the tasks of energy plan- FER, minimal costs and losses. In the course of the energy
ning and the calculation of planned consumption of fuel and planning of the enterprise, it is necessary to achieve the full
energy resources on the basis of reliable calculated norms and volume of production and employment of available resources,
standards. The energy policy of the oil and gas industry en- which in turn implies the optimal use of fuel and energy re-
terprises largely depends on the quality of their long-term, sources, production assets, inventories, working hours, tech-
strategic, current and operational energy planning, which are nological methods, money resources, information opportuni-
closely related to energy analysis and the definition of basic ties and other factors [3].
criteria. And also depends on the indicators of energy effi- These goals can be achieved by making management de-
ciency, the setting of goals, objectives and the development cisions that are oriented to the future. Therefore, planning in
of action plans necessary to achieve results to improve energy a broad sense has the content of the formation of managerial
performance in accordance with the energy policy of the en- decisions based on systemic decision-making. At the level
terprise. In this regard, the development of management deci- of production enterprises in the oil and gas industry, both
sions in operational energy planning is becoming urgent, as prospective energy planning (forecasting) and current en-
in planning there arises the need to find and make managerial ergy planning are implemented, as well as operational energy
planning as a detailed elaboration of the development of the current energy plans of the enterprise as a whole, its deposits, large production units up to the process units.
Monitoring process and analysis of the functioning of EMS. For the implementation of the procedure for monitoring, measuring and analyzing the key characteristics of operations that determine energy performance, FER consumption accounting systems are used. The main purpose of such accounting systems is the automated collection of factual data about consumers' facilities. The accounting system performs the following functions: - obtaining operational and accurate information on the consumption of all types of energy; - accumulation, processing and analysis of information on energy consumption and the parameters of the functioning of the electrical subsystem; - forecasting of energy consumption; - timely response to emerging problem and emergency situations; - control costs for the use of electricity, because - this is the way to save it, and therefore has a real financial result; - centralized collection of information on energy consumption in order to optimize energy consumption costs and their long-term planning; - monitoring of emergency situations in the operation of the device; -providing accurate and truthful information to the end user about the energy resources used by them. The application of the accounting system minimizes the expenses necessary for monitoring energy consumption in the building, such as additional equipment or the appointment of responsible persons.
The decision-making process (PPR) in EMS. When implementing the EMS's functional tasks, the PPR is carried out to develop and implement measures aimed at achieving economic performance. Under Decision Support Systems (DSS) we mean an automated system that allows us to use data, knowledge, objective and subjective models for analyzing the solution ofweakly structured problems. As a result of the analysis, a conclusion is made about the need to implement the DSS for knowledge-based EMS, and it is necessary to use models and methods of intellectual information processing to extract knowledge about the process of using and consuming energy.
Such DSS will be considered as a hybrid of the intellectual system of support for decision-making in energy management systems and a system of corporate reporting and analysis for managing the efficiency of EMS.
The decision-making process is a key process that influences the quality of the products or services produced, the enterprise development strategy. In Figure 2, we present a universal algorithm for solving the problem of the decision-making process, establishing the set and sequence of steps in the decision-making, and we will designate the main actors of this process and their role. The universal algorithm for solving
DSS tasks consists of several stages and is a multi-stage iterative procedure.
Necessity of decision-making arises at occurrence of a problem situation (a stage occurrence of a problem situation). In this case, the problem is identified (steps of a meaningful description of the problem - definition of constraints), i.e. a meaningful description of the problem is given, the desired result of its solution is determined, and the available limitations are evaluated.
In the next stage, the problem of making a decision is formulated (stages of a meaningful description of the problem -the formulation of the decision-making task). For this, it is required to define a set of possible solutions (alternatives). Depending on the problem under consideration, the number of possible variants of the solution can be several units and can reach tens, hundreds and even thousands. Theoretically, the number of options considered can be infinite. In order to fully describe all possible solutions, it is usually necessary to collect and analyze various information pertaining to the problem and alternative ways of solving it. The absence or inability to obtain the necessary information can make the problem un-solvable. In such cases one has to return to the original formulation of the problem and change its description. Such a need can arise at all the previous stages of the decision process. In complex choice situations, it may also be necessary to develop a special model of the problem situation in order to obtain a simplified model solution to the problem with its help.
The second stage ends with the formulation of the decision-making task. It should be noted that a detailed, meaningful description of the problem being solved, already at the first stage, largely determines the possible approaches to its solution and can immediately lead to the formulation of the problem of making a decision, bypassing all or; many of the subsequent stages.
Having formulated the problem of decision-making, they pass to the decision of the decision (the stages of choice / development of the method of solving the problem - the choice of the most preferable option).
This stage includg to specially selected or constructed criteria, reflecting the features of options important for the participants in the selectioes, first, the selection of a method for solving a problem from already known or developing a new method; secondly, the very decision process itself, which consists in evaluating and analyzing the various solutions and choosing the most preferable among them. In a number of problems obtaining the final result does not present great difficulties. However, these are often rather complicated and time-consuming procedures that require the knowledge and skills of many people and the capabilities of modern computational techniques.
The emergence of a problem situation
A meaningful description of the problem
Setting the desired solution result
Defining constraints
Determination of possible solutions
Collection and analysis of information
Development of a problem situation
■
Formulation of the decision problem
Choice of the method for solving the problem
Evaluation and analysis of solution options
Choosing the most preferred option
i
Changing the wording of the problem
Figure 2. Diagram of a universal algorithm for solving the DSS problem
At the same time, even after passing through the stages of the process of solving the problem, it is not always possible to make the final choice. There are situations when you can not find a better solution. The desired option may simply not be in place. Then you can either change the wording of the initial problem (the stage of changing the formulation of the problem), or go back to the previous stages and collect the necessary additional information, make changes in the formal formulation of the problem or the model of the problem situation, expand or narrow the number of the considered alternative, to construct new variants.
In any case, the search for a better solution, even if it did not lead to a positive result, will not be useless. O may prompt a new understanding of the problem in question, pay attention to some new aspects that need to be taken into account, and point out other ways of solving the problem.
If an acceptable variant is found, then the stage of implementation of the decision (stages of implementation and control of the decision taken, evaluation of the result of the solution of the problem), at which the implementation of the decision takes place, the control over the implementation process is carried out and the result of the resolution of the problem situation is assessed. Strictly speaking, this stage does not belong to the decision making procedure. However, the inclusion of the execution of a solution in a general scheme is important from the methodological and practical point of view, as this stage closes the life cycle of the process of the emergence, resolution and disappearance of the problem situation. In addition, the implementation of the adopted decision may pose a new problem requiring the search for its solution.
The task of making a decision is to form a set of possible options that provide a solution to a problem situation under existing constraints, and identify among these options one best or several preferred options that meet the requirements for them. Formally, the problem of making a decision can be written down in the following generalized form:
DS = (PO, AI, AC, Cy, DSS) (2)
PO - a set of possible options from which to choose. These can be real variants, depending on the context of the problem, objects, candidates, ways of achieving goals, actions, decisions, etc., or a hypothetical set of all theoretically possible variants, which may even be infinite. We emphasize once again that the choice arises only when there are at least two possible solutions to the problem.
AI - a set of indications (attributes, parameters) describing the variants and their distinctive features. As indicators, first, objective indicators that characterize certain properties inherent in the options, and which, as a rule, can be measured; secondly, subjective assessments, which are usually given accordinn.
AC is the set of conditions that limit the range of acceptable variants of the solution of the problem. Restrictions can be described both in a meaningful way and in the form of some formal requirements for options and / or their attributes. For example, this may be a restriction on the values of a feature or a different degree of characterization of the characteristic for certain variants, or the impossibility of simultaneously combining certain values of signs for actual variants.
DSS - the preferences of one or several decision-makers, which serve as a basis for evaluating and comparing possible solutions to the problem, selecting acceptable options and searching for the best or acceptable option. It is often enough to simplify the formulation of the decision-making problem, some of the information describing the preferences of decision-makers turns into limitations [4].
The problem of making decisions will be considered in the formulation known in artificial intelligence - search in the state space. In general, the problem is formulated as follows: an initial state or subset of such states is defined, a final state or subset of such states, and a set of rules for transforming states. It is required to find a sequence of transformation rules, possibly satisfying certain requirements, which allows you to convert the initial state to the final one. If the desired sequence must satisfy the requirement of optimality, then we have the problem of finding the optimal solution, if the admissibility requirements are the problem of finding an admissible solution.
The formulation of the DSS proposed below is somewhat different from the formulation (2). So DSS is a tuple:
DS=(S,Sv,Sn,Sk,R,Ql (3)
S is the set of states (situations), called the universe, S"C S is the subset of possible states, respectively S"fl S is the subset of impossible statses S" is the set of admissible states; S C S is a subset of the initial states; Sk d S is a subset of finite states; R: S S is a finite set of transformation rules, each rule R C R is a function realizing the map R : S S, where S is the domain of definition R It is assumed that the rule R is applicable to the state S c S ifS d S • Qjs the set of criteria for estimating the solution found. We will assume that states are described by the final words of a language and can express both structured and unstructured concepts. Consequently, the solution of the decision-making problem is represented in the form of a sequence of transformation rules.
The development of classical DSS is the direction associated with the adoption of operational decisions that take into account the time limit reserved for decision making [5]:
TC < TD (4)
where TC is the solution time of the problem; TD is the allowable time.
World and domestic practice shows that the use of the system approach is a prerequisite for the creation of modern control systems for complex objects, including when solving EMS tasks, both with the appropriate scientific research and when implementing technical projects. In the development of mathematical modeling methods aimed at solving the above-mentioned problem complexes, as well as in the implementation of procedures for overcoming uncertain-
ties and making decisions, optimization methods that are developed taking into account the specifics of the oil and gas industry and the formation of energy supply and energy consumption balances play an important role. In practical terms, the results of studying general problems of mathematical modeling are used in two ways: for automating all types of system studies and for creating automated energy management systems.
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