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Mathematical model and algorithms for reasonable power saving management systems
5. Kopein VV., Filimonova E. A. Economy and politics: what comes first for the economic security of the State?//European science review, ISSN 2310-5577. «East West» Association for Advanced Studies and Higher Education GmbH. - Vienna. 5-6 (May-June), 2014. - Р. 200-203.
6. Kopein V. V., Filimonova E. A. Structural Transformation of the Economy of the Region and its Financial Security (for example, Kemerovo Region). - Novosibirsk: Siberian Branch RA.S Publ., 2008. - 384 p.
7. Economic safety of Russia: General course. Tutorial. Ed. V K. Senchagov. - Moscow: Delo Publ., 2005. - 896 p.
8. Filimonova E. A. The problems of economic security methodology in the conditions of economic crisis.//Journal of Russian Entrepreneurship. - 2015. - vol. 16, no. 13. - Р. 1949-1964. doi: 10.18334/rp.16.13.495.
9. Kopein V V., Filimonova E. A., Kopein A. V Regional factor in economic security.//Journal of Russian Entrepreneurship. - 2014. - no. 14 (260). - Р. 13-25. doi: http://dx.doi.org/10.18334/rp.15.14.983.
10. Kopein VV Modern problems of monitoring food security.//Food Processing: Techniques and Technology. - 2014 -no. 4. - Р. 158-163.
11. Hacker Jacob S., Huber Gregory A., Nichols Austin, Rehm Philipp, Craig Stuart. Economic Insecurity Across the American States: new state estimates from the economic security index. Economic Security Index, The Rockefeller Foundation. - June, 2012.//[Electronic resource]. - Available from: http://economicsecurityindex.org (Dates Views 10.07.2014).
Biryulin Vladimir Ivanovich, South-West State University, Candidate of Engineering Sciences, Associate Professor
E-mail: [email protected], Alyabyev Vladimir Nikolaevich, Candidate of Engineering Sciences, Associate Professor E-mail: [email protected], Larin Oleg Mikhailovich, Candidate of Engineering Sciences, Associate Professor
E-mail: [email protected], Gorlov Alexei Nikolaevich, Candidate of Engineering Sciences, Associate Professor E-mail: [email protected], Kudelina Daria Vasilyevna, South-West State University, postgraduate student, Computer Engineering Department E-mail: [email protected]
Mathematical model and algorithms for reasonable power saving management systems
Abstract: The paper deals with models and algorithms for the management information systems of power consumption modes.It shows the problem of the most effective interventions choice aimed at reducing energy consumption given limited funds. It is proposed to use the voltage drop in the power-supply system of industrial enterprise as one of the possible ways of energy saving.
Keywords: management, model, algorithm, power consumption, information systems.
Introduction
The importance of technical, organizational and management energy saving measures, which define and control a highly complex set of administrative decisions in the power system of industrial enterprise is determined by the necessity to consider the complex of production, economical and administrative requirements. On the one hand, there is an increase in energy intensity in industry (46 %), metallurgy, machinery, tools and molds, other production — expansion
of the products nomenclature, the dynamic change of the daily and annual load in the industrial enterprise work. On the other hand, there isa large deterioration of the industrial enterprise power system equipment that leads to significant losses of electricity, which is unacceptable for industrial enterprise in modern conditions (up to 13.5 % of total energy resources production) [1].
A perspective approach of the enterprise internal capabilities activation is to increase the efficiency of the management
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system atthe industrial enterprise power system. The overall objective of the industrial enterprise power system management includes the task of electricity consumption reduction, which can be achieved by choosing the optimal level of voltage reduction at the industrial enterprise power system. However, the voltage reduction is accompanied by the manifestation of various negative consequences. First of all, it is the performance drop of technological equipment with a subsequent decrease in enterprise profit, which may lead to negative economic and social effects [2].
The industrial enterprise management is basically distributed [3]. This means that a single task is divided into multiple sub-tasks with their own local objective functions (the subtask of value and resources volume management, the subtask of specific investment per unit of output determining, the subtask of energy consumption optimization, the consolidated task of coordination, etc.). The basis for the breakdown into subtasks is a formalized multilevel description of the industrial enterprise structure in the form of conceptual, informational or structural-functional representation. This integration of the industrial enterprise power system information representation in the overall structure of the industrial enterprise will allow the location and the impact intensity of the voltage level change for typical nodes to be determined [10].
Results and Discussion
First of all, the solution to this problem is complicated by the following factors:
1. A large number of levels and voltage control points in a multilevel industrial enterprises electricity supply system structure with irregular bonds [4].
2. The output volume and electricity consumption amount changing over time.
3. The voltage change during the year due to the nonuniformity of energy consumption in different time periods [5].
4. Temporary change of cost price, products price and resources of the industrial enterprise in the market economy conditions [6].
The automated dispatch control systems are designed to generate the managerial decisions in power systems during
their exploitation. However, the specificity of the industrial enterprise, which consists in the electricity consumption for output production, is practically not taken into account in this class of automated information management system, as the energy system is responsible for the production, transmission and distribution of electricity. The main task of the automated information management system for industrial enterprise is to ensure the output production cycle and the optimization issues of electricity at the industrial enterprise [7, 11].
The automated dispatch control systems («Parus», «ElectriCS 3D», «ElectriCS ADT», «Elsna»), applied in the industrial enterprise power systems, show that they are aimed at the design and exploitation of electrical equipment and electrical networks [8]. Their models and algorithms don’t take into account the negative effect associated with the productivity reduction of technological equipment at lower voltage level, which in turn preventsthe control of the energy saving measures and calculate the required operating mode with reasonable energy saving effect.
Developing the mathematical model the following technical, economic principles and assumptions adopted in practice were taken into account:
- positive, negative effects of voltage reduction are compared in the same (monetary) units;
- the total final effect is defined as the maximum difference between the positive and negative effects when the voltage level changes within certain limits;
- the final effect in one regulation embodiment doesn’t depend on the other options.
Comparing with existing mathematical models, our mathematical model allows to calculate the following values (part of the developed mathematical model is shown below):
- the section, workshop or enterprise productivity reduction expressed in units of the products;
- enterprise cost savings defined as the payment for electricity consumed decrease;
- losses due to the output volume reduction in monetary terms.
AP = f (U*)
6Uf
AP = —- • (1 -U*) - for resistance furnaces,
” R V 7
P = a(ri + r„ /s) + klp^nom,
AP = (l - Р*АД )ном - for asynchronous motors;
(1)
P* = 1.6U* - 0.6- for incandescent lamps,
ДР = f2 (U*)
P* = 2.2124U* -1.1871 - for high pressure mercury lamps, P* = 2.4978U* -1.4939 - for low-pressure mercury lamps,
(2)
ДР = (1 - P*) ;
where U — the electric network phase voltage; R- the heating element resistance; Р* =P/Pnom, Q* =Q/ Qnm — active, reactive powers; Р , Q — the nominal active and reactive
A 'у пот пот
power values of asynchronous motor during the transition
to magnetizing circuit; s — the current value of the motor slip; r — the stator winding resistance of the asynchronous motor; rn — the intermediate value equal to Ar ; kx = 00 + 0lkU + a2kU ; U, = kU = U/Unom — the voltage in relative units.
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Mathematical model and algorithms for reasonable power saving management systems
The static characteristics used in the electricity consumption reduction assessment have the following relationship for almost all electrical receivers: with a decrease in the voltage level the power consumption of both active and reactive power reduces [12]. In general, the decrease in consumption of active AP and reactive power AQ of electrical receivers under consideration was calculated based on the use of the static characteristics and was expressed in general by the equations AP = ф (AU), AQ = ф (AU), where ф, ф — polynomials of first, second and higher orders.
To calculate the resulting positive component of the objective function at lower voltage levels in the industrial enterprises electricity supply system the E function is applied:
Е = APtc +11. (3)
The reduction of the voltage nominal value also creates the negative effect: the light levels drop and the associated decrease in productivity, the technological installations power reduction, etc. The function Z is introduced to calculate the resulting negative component of the objective function at lower voltage levels at the industrial enterprises electricity supply system:
Z = AQR ■ k +12. (4)
The found values Е and Z are used to find the objective function F:
F = E - Z (5)
The maximum positive effect is defined as the maximum of the objective function F (AU) in the interval of voltage deviations from the nominal value [- AU; U ].
L ' nomJ
Productivity change is defined by the following expres-
sion:
QR_
QR
1
(6)
1 - k' + k' / q’
where QR — the machine productivity at Unom; QR1 — the machine productivity at U* Unom, q = n’ / n; n — the rotation frequency of the main drive at U ; n — the rotation frequency of the main drive at U * U .
nom
The decrease in products AK produced by the enterprise, expressed in monetary terms, will have the following meanings:
AK = (tqrfa (1 -E------------Л--------------)), (7)
1 - k ' + ki + U.(1 - kiSni)
; U.2 - k s .
where h0i — the i — type unit cost; h — the load factor of the i-th engine; sni — nominal slip of the i-th engine; N — the number of i-type products, manufactured over the time period T at the nominal work conditions; m — the number of products types produced in the guilt; N' — the number of i-type products, manufactured for the same period of time T at the reduced voltage value in the workshop electrical network.
Based on this mathematical model, algorithms have been developed to determine the application points of managerial influence in the industrial enterprises electricity supply system (Fig. 1), the stability regions definition of making the optimal decision (Fig. 2).
Fig. 1. Algorithm for the application points determining of the managerial influence at the industrial enterprises electricity supply system where d — number of ways to regulate; pd — the current voltage level regulation step; md — the number of voltage level regulation steps
The algorithm (Fig. 1) in contrast to known allows defining the nodes in the hierarchical structure of the industrial enterprises electricity supply system, which should be applied to the impactsofthe voltage level management.The novelty of this algorithm is determined by the original pro-
cedure of calculating the Fd values which depends on the location and voltage regulation step.When the enterprise works there is a change of parameters, which were on the basis of objective function calculating, which leads to the necessity to find outthe change interval parameters of the
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Section 16. Economics and management
objective function, in which the found value AU remains the optimal.
For this, the following search methods of finding the stability of the solution may be used: the solutions sensitivity analysis, the method of parametric programming and the
phase plane method [9]. The first two methods require the expression of the objective function as an analytic function of its parameters; the objective function is given by means of calculation, resulting for the stability regions finding the method of phase plane was applied.
Fig. 2. Algorithm for optimal decision stability regions determining, where j — months number; N — the number of months; h — the discrete step of regulation AU; Fj — the objective months function value j
Algorithm (Fig. 2) in contrast to the known allows to determine the stability regions of a decision based on the phase plane when the initial data changes.
Conclusion
The decision remains stable if the representative points don’t extend beyond a half of the voltage level regulation interval h as the voltage level regulation is in steps.
The objective function values were calculated on the basis of voltagevalues determining both in the industrial enterprises electricity supply system circuit nodes, and consumers alike after the regulation (decrease) ofvoltage and power consumed by the electrical receivers on this or that level, that is calculation of the industrial enterprises electricity supply system working modes.
The objective function values (5) were calculated for one of the Kursk city plant having a typical industrial enterprises electricity supply systemstructure for most industrial enterprises inRussia, per month and per year for the whole enterprise (Fig. 3) depending on the voltage reduction magnitude.In calculations of the enterprise the voltage level regulation on workshop substations and supply transformers substation were regarded.
In Fig. 3, the curve 1 shows the dependence of the objective function F from the voltage reduction regulating only on the supply transformer substation, the curve 2 — for joint regulation at both supply transformer substation and workshop substations, and the curve 3 — the regulation on the guild transformer substations. The second voltage level regulation way has been selected as the maximum value of the objective function has been received.
Fig. 3. The F changes graphs depending on the place of voltage regulation for the enterprise as a whole
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Ecologizing parameters of the world economy
References:
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2. Horoshilov N. V. Model and algorithms for the modes management information system of the industrial enterprises electricity consumption. In: the dissertation for the degree of technical sciences candidate. - Kursk: KurskSTU, 2007.
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9. Biryulin V I., Larin O. M., Horoshilov N. V., Gorlov A. N. Analysis of some issues that arises when expert energy management systems for industrial plants are being created. - Kursk, 2011.
10. Smirechov G. N., Sorokin A. A., Telnov Y. F. Economic information systems designing.//Finance and Statistics. - 2001.
11. Biryulin V I., Larin O. M., Horoshilov N. V., Gorlov A. N. The prospects for energysaving in lighting systems.//Energy security and energy efficiency. - (33): 11-13.
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Tsybuliak Anastasiia Gennadievna, Institute of International Relations of Kyiv National Taras Shevchenko University, Candidate of Political Sciences, researcher of international finance department
E-mail: [email protected]
Ecologizing parameters of the world economy
Abstract: The article investigated the essence and parameters of the world economy ecologization. Its impact on the development of international economic relations is determined.
Keywords: ecologization, ecologizing parameters, ecology, environmental component of the global community, environmental management, international ecologically-oriented institutes.
The functioning of the world economic space goes under the influence of varied factors which have both positive and negative meanings for its development. First of all, it presupposes that intensification of integration processes, globalization, transnationalization, expanding of the structure and dynamics of international economic relations by promoting the development of interstate cooperation simultaneously enhance the environmental burden on the environment. Environmental concerns are one of the key contradictions of the modern world. The increase of pressure on the environment leads to aggravation of environmental situation globally, causes the loss of natural reproductive capacity and ultimately leads to the ecological crisis that is irreversible changes in ecological system and disorder in natural balance.
The concept of ecology has very ancient roots. Even a primitive man without a scientific understanding of ecological processes in the practice that was directly tied to natural processes, understood the need to protect the most valuable objects for being living. In the period when the below mentioned public forms of development were existing, individual elements of ecological knowledge were being improved in the framework of other sciences. The
period from the mid-19th to mid-20th century was characterized by intensive development and research of bioecology and global geographic processes. It was during this period in 1866-1868 that German scientist Haeckel launched the term “ecology”. He was the first who singled out the part of biology which investigated the interaction of living organisms with the ecological environment.
Equally important for the development of ecology was also the doctrine about the noosphere, the study of which was started by famous Ukrainian scientist V I. Vernadskyi. He first defined the person with economic activity as a geological force of planetary size and showed that human impact on the environment is not less strong than the global natural processes. This stage also acquired environmental perspective, as it actualized the need to solve specific regional and local problems of pollution, deforestation, destruction of agricultural fields, etc.
Further development and awareness of the environmental component of the global community functioning has been continuing so far. The defining features of its functioning include the development of an idea about the global natural and anthropogenic processes and the inability to solve
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