Economical heat production and distribution

Transcription

1 Econoical heat oduction and distribution JOZE TORKAR, DARKO GORICANEC*, JURIJ KROPE* El-tec Mule, d.o.o. Pot na Lisice 7, 4260 Bled, *Faculty of Cheistry and Cheical Engineering University of Maribor Setanova ul. 7, 2000 Maribor, SLOVENIA Abstract: A reliable supply of heat, ovided by eans of district heating systes, depends on faultless and stable operation. Econoic success further requires high quality onitoring and control. The paper deals with an apoach to the onitoring and control of district heating systes while focusing on econoic success. In this respect it is necessary to take into account a possible usage of various energy sources, with regard to energy consuption ediction and operational econoic optiu, throughout the planning as well as in the anaging, onitoring and aintenance of the district heating systes. In order to ensure cost-effective anageent of a heating syste, optial syste control easures ust be adopted requiring odeling and a ediction of the heating syste's future operational state. Key-Words: District Heating, Heat Consuption Prediction, Econoical Production, Heat Distribution Introduction An econoical anageent of coplex district heating systes (DH) ust ebrace a rationalization of the operations of all coponents involved in the ocess of heat oduction and distribution. In this article one possible apoach to cost-effective anageent of district heating systes is described. The anageent is based on deterining the optiu supply teperature, the optiu flowessure conditions in the pipe network and the optiu heat oduction in the near future (a few hours to a few days in advance). Econoical anageent should be based on an accurate knowledge of oduction and distribution capacities, as well as edictions on the future consuption of heat fro the energy syste. The ai of the anageent is to fully eet consuers' needs, whilst eserving the lowest possible variable costs of oduction and distribution of heat. Econoical anageent requires accurate ediction of future heat consuptions as well as an assessent of the risk of exceeding the liit values for heat consuption in the future. The forecast of the required variables is carried out with the INTELPRED software package [], [2], [3]. The calculated values are then forwarded to the econoic odule, which deterines the optiu econoic ofile of heat oduction f( (t)), supply teperature f(t s (t)) and return teperature f(t r (t)), taking into account the relevant boundary conditions. 2 Modeling of the district heating syste A district heating syste can be divided into three eleents: consuption points, the hot water network and oduction sources. An accurate knowledge of the operations of all syste eleents and of their interconnection is a erequisite for the achieveent of optiu results. 2. Consuption points The operation quality of a substation and a data exchange with the control centre can to a large extent influence the operating efficiency of the whole DH syste. To achieve the optiu substation operation paraeters, it is of crucial iportance to correctly plan, execute and control the secondary syste and eleents of the substation. 2.. The consuption-point heat-flow odel Heat fro hot water systes is used for: heating (with radiators, radiant floor heating, convectors) air-conditioning systes, ocess energy consuption, hot water oduction, cooling (absorption chillers).

2 Consuption points are divided into categories, with regard to the consuption characteristics. Every category coises i consuption points fro which the data on the syste's operating states can be obtained via a reote onitoring and control syste. Consuption points belonging to the category fro which the data cannot be obtained are apoxiated with the factor p. The factor p is calculated as the ratio between the heat flow of all consuption points belonging to category and the heat flow at consuption points of category which are connected to the reote onitoring and control syste [4]. The atheatical odel of heat flow at consuption points can be exessed as: K N = i p () = i= i =, 2, 3,, N, =, 2, 3,, K Data on heat consuption in the district heating syste, together with weather data and day type, are recorded in the data base at 30-inute intervals Consuption-point heat-flow ediction The INTELPRED software package is used for heat consuption ediction. It enables energy consuption forecasting in all types of district heating systes. INTELPRED is based upon ethods of siulated neural networks and genetic algoriths. On the basis of available data on the operation of the selected district heating syste, it creates a odel of syste operation and response to control easures. In so doing, it deterines the connections between the individual environental variables values (weather data, day type) and energy consuption in the syste. On the basis of the syste s current state and the given oected future values of certain environental variables, the software forecasts future syste operation and assesses the risk of exceeding the set energy consuption liit values in the future. The estiated forecasts and risk of exceeding the heat consuption liit values in the future for the basis for the deterination of the econoically ost apoiate heating syste control. The ediction leads to a tie-dependent function of heat consuption: f ( ( t)) (2) The iniu supply teperature T st and the axiu hot water network return teperature T rt, which depend on the outdoor teperature, are deterined with technical conditions laid down by the heat supplier. With regard to the ediction of tiedependent outdoor teperature T o the following functions can be defined: f ( Tst ( t)) (3) f ( Trt ( t)) (4) On the basis of functions (2), (3) and (4) the function of volue flow (according to technical conditions) ay be thus calculated: f ( qvt ( t)) (5) 2.2 The hot water network Hot water networks are generally coplex piping networks, coposed of nuerous straight sections, unctions or loops. Specialized software packages enable static hydraulic analysis of different types of piping networks [5]. The data obtained are crucial for the design of the hot water network, the deterination of the optiu configuration of puping stations, the detection of critical points in the syste and the assessent of possibilities for consuption extension [6], [7], [8]. For optiu anageent of the syste the pipe network odels ust be siplified by grouping into individual units. In this way the odel can be siplified by 80-95%, without any significant deterioration in accuracy [5]. However, it is iportant to eserve soe iportant characteristics of the network, such as the volue of the ediu in the pipe network, tie lags, volue flow, heat losses and essure conditions. The siplified odel ust agree with the real odel to a certain level of accuracy, especially as regards essure conditions and heat transfer dynaics A heat flow odel for the distribution of heat The paper assesses the possibility of heat storage in the hot water network for the purposes of optiization of oduction and distribution of heat. The atheatical odel for the distribution of heat flow at the heat source threshold can be exessed as: ds = (6) hl ak A corrected consuption-point heat-flow odel In a corrected consuption-point heat-flow odel the heat distribution tie delay needs to be taken into account t K (fro the source to the last consuption hlak

3 point), with regard to volue flow. The delay ay be deterined with: a siulation of operating states of the syste in a syste for hydraulic analysis of pipe networks, easureents of tie delays in different operating states. t = f q ) (7) K ( vt Functions (3) and (4) are then corrected with the tie delay: f ( Tst ( t + t K )) (8) f ( Trt ( t + t K )) (9) On the basis of functions (2), (8) and (9) the corrected tie-dependent function of volue flow ay be calculated: fq vt (( t + t K )) (0) The changes of tie delay due to corrected volue flow are inial and can therefore be disregarded. The volue flow depending on the chosen supply teperature T s and return teperature T r of the hot water network can be exessed as: Tst Trt qv = q () vt Ts Tr The heat flow equation for consuption points goes as follows: = q ρ c T T ) (2) v p ( s r The heat flow odel for heat losses This odel features the distribution of hot water by eans of a double-pipe hot water network. Heat losses can be divided into two groups: losses in the supply pipe and those in the return pipe. When calculating heat losses it is necessary to take into account the effects of the return pipe on losses in the supply pipe and vice versa. A atheatical odel for heat flow due to heat losses at T st and T rt for einsulated pipes laid directly into the ground, exessed in a siplified anner, is as follows: = L λ T + T 2 T ) (3) hl ( st rt so The pipe heat conductivity coefficient λ for the individual hot water network ay be deterined on the basis of: pipe oducers' data, with regard to easureents and quality of insulation of individual pipe segents, easureents and calculations that are based upon the heat that was oduced and sold within a period of several years. On the basis of heat losses and T s and T r during the years 2003 and 2004 in the hot water network TOM (Toplotna oskrba Maribor d.o.o.) the calculated pipe heat conductivity coefficient aounts to λ = 0.33 W/K. Producer s data: λ 2 = W/K for series 2 hot water pipes and λ 3 = W/K for series 3 hot water pipes, the average pipe diaeter being 244. The hot water network pipeline L has a length of The volue of water in the pipe network aounts to The variation of teperature T so at a depth of, depending on the season, is shown in figure : Tso (K) Month of the year Figure : T so at a depth of, depending on the onth A heat flow odel for heat storage For the storage of heat in the pipe network at low consuption rates in the network it is necessary to install a bypass on apoiate segents enabling volue flow q v,bp. The degree of opening of the bypass is regulated via a reote onitoring and control syste, depending on the heat storage needs. Heat storage in the hot water network ay be exessed for the supply and return pipes ointly: = q ρ c ( T + T T T ) (4) ak v, bp p s r st rt The heat flow odel for heat losses due to heat storage Heat losses due to heat storage in the hot water network ay be exessed for the supply and return pipes ointly: = L λ T + T T T ) (5) hlak ( s r st rt 2.3 Production sources Heat ay be oduced separately or be co-generated together with electricity (CHP). In both cases it is

4 iportant to have the optiu anageent of energy oduction with respect to ofit, with all technical boundary conditions ovided for. The ai of the optiu oduction control is to oduce as uch heat as possible fro low-cost and environent-friendly sources. To achieve this goal, two eleents are extreely iportant, naely: choice of the right configuration of oduction sources at the tie of planning the installation, considering the hourly ofile of consuption in the hot water network; and establishent of an optiu energy-oduction plan, in accordance with high-quality short-ter and long-ter ediction of heat consuption. The heat flow odel of heat oduction is shown below as the su total of all oduction sources: n = i (6) i= 3 Cost-effective oduction and distribution of heat The basis of cost-effective oduction and distribution of heat, with regard to a known future consuption rate, is a balance equation between the heat flow odel for heat oduction (6) and the heat flow odel for heat distribution (6) within any given period of tie, taking into account all relevant boundary conditions: = t = = ds t (7) Certain siplifications are carried out: considered tie period: 24 hours; tie interval t 30 in; the nuber of tie intervals 48; all paraeters are average values of the given tie interval. Using a nuerical siulation of the balance equation (7), with regard to all boundary conditions, the possible control easures for heat oduction and distribution within a period of 24 hours are siulated. The chosen tie-dependant cobination of control easures should ensure the axiu of the variable part of the ofit function within the chosen tie frae: C( t) = C ( t) C ( t) (8) ds Variable revenue due to heat distribution ay be exessed as: C ds = ( = c S + ( hl ± ak hlak ) c ) t (9) Variable costs due to heat oduction ay be exessed as: C n = ( = i= i c i ) t C (20) Figure 2 shows the daily ofile for heat oduction (unbroken line) and the daily ofile for heat consuption (broken line). In the graph the inciple of heat storage inside the pipe network is evident, enabling us to avoid initiation of a third heat source. A siilar inciple is used to avoid switching on a second boiler during suer operations. Figure 3 shows the consuption of heat in the network of the copany TOM. The broken line reesents the hourly ofile of heat oduction for the year 2004 and the unbroken one the hourly ofile of heat oduction for the year The graph shows that up to a heat deand of apox. 6.5 MW, heat was oduced fro a cheaper source in coparison with This result was achieved thanks to the choice of a suitable cobined heat and power oduction facility (gas engine CHP: P el = 3 MW, th = 3 MW) and the storage of surplus heat in the pipe network. Savings resulting fro heat oduction and distribution anageent with heat storage in the pipe network are reesented by the difference in ice of energy oduced within the range of hours in the year 2004, reduced by the costs of heat losses due to heat storage. 4 Conclusion Consuers are deanding ever ioving services at lower ices. The arket for energy sources has been steadily opening. Heat oducers and distributors ust be ever ore copetitive, which is possible with greater efficiency and flexibility. The required return on investent can be achieved by taking good organizational easures and by cutting heat oduction and distribution costs. In the last two years our developent work in collaboration with the Faculty of Mechanical Engineering, Lublana, and the Faculty of Cheistry and Cheical Engineering, Laboratory of Heating Engineering, Maribor, has been directed towards the developent of oducts and services for the cost-

5 60 HFds HF 50 Heat flow, HF (MW) :00 :00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 0:00 :00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 20:00 2:00 22:00 23:00 Tie (h) Figure 2: An exaple of cost-effective anageent of heat oduction and distribution at TOM Heat oduction (MW) Operating hours (h) Figure 3: Hourly ofile of heat oduction in the TOM network effective anageent of heat oduction and distribution. The results of this collaboration are the aforeentioned software package for the onitoring and control of consuption points, the software package for long-ter and short-ter ediction of heat consuption and the software package which allows calculations of the axiu variable part of ofit and the deterination of control easures within a certain tie frae, whilst ensuring stability in the operation of the syste. All of the operational tests are being executed on a ediu-sized district heating syste ( = 94 MW), in cooperation with the copany TOM. Operational testing of the software package for the onitoring and

6 control of consuption points and the software package for long-ter and short-ter ediction of heat consuption has been concluded. The developent of phase of the econoic odule and the deterination of a schedule for different control easures are scheduled to be concluded by autun The coenceent of coercial use of the entire syste for cost-effective heat oduction and distribution is planned for the 2006/07 heating season. The cost-effective heat oduction and distribution described above enables the highest savings levels in: systes in which heat is generated by using several different sources and fuels; systes, where a base load consuption of power fro CHP plants is ovided for. The peak heat loads of heat generation facilities can effectively be reduced which, when building new or renovating already existing sources, leads to savings in investent into oduction sources for covering these peak loads. The developent of a syste for cost-effective puping stations anageent is currently being planned in cobination with the dynaic control of essure conditions. Noenclature: c C variable part of cost ice of heat (EUR/J) c p specific heat capacity (J/kgK) c variable part of heat oduction expenditure via source i (EUR/J) c S variable part of selling ice of heat (EUR/J) C ds variable revenue fro the distribution of heat (EUR) C variable expenditure due to oduction of heat (EUR) K nuber of consu. characteristics categories L hot water network pipeline length () nuber of tie intervals n nuber of oduction sources N nuber of category consuption points p category reote control factor q v volue flow at T s and T r ( 3 /s) q v,bp volue flow through the bypass ( 3 /s) q vt volue flow at T st and T rt ( 3 /s) t tie interval (s) t K tie delay of heat distribution (s) T o outdoor teperature (K) T r chosen return teperature (K) T rt axial return teperature (K) chosen supply teperature (K) T s soil teperature at a depth of (K) inial supply teperature (K) Greek letters: ak heat flow for heat storage (W) heat flow at consuption points (W) T so T st ds distribution heat fl. at the source threshold (W) hl heat flow for heat losses (W) hlak heat fl. due to heat losses because of storage (W) heat flow of heat oduction(w) λ pipe conductivity coefficient (W/K) ρ density (kg/ 3 ) References: [] M. Thaler, A. Poredos, I. Grabec, Epirical odel for ediction of gas consuption and other types of energy, VII oceedings SDDE, Portorož, March 2004, pp [2] M. Thaler, I. Grabec, A. Poredos, Prediction of energy consuption and risk of excess deand in a distribution syste ; First Bonzenfreies Colloquiu on Market Dynaics and Quantitative Econoics, Alessandria 2004, Italia [3] I. Grabec, W. Sachse, Synergetics of Measureent, Prediction and Control, Berlin, Singer-Verlag, 997 [4] M. Thaler, A. Poredosš, I. Grabec, J. Torkar, Prediction of energy consuption as the basis of district energy distribution syste control, VIII oceedings SDDE, Portorož, March 2005, pp [5] D. Goricanec, A. Jakl, J. Krope & V. Kranc, A Software Tool for Pressure-Flow Analysis of Conditions in Pipe Networks, Journal of Mechanical Engineering, 44 (3/4), 998, pp [6] J. Krope, D. Goricanec: Analysis of Pipe Networks Including Pups, Energy build., 7, 99, pp [7] A. Krope, J. Krope & D. Goricanec, Optiization of Transport Pipe Networks, Proceedings of the IASTED International Conference: High Technology in the Power Industry, IASTED: Orlando, 997, pp [8] D. Goricanec, J. Krope, Z. Knez. Drag reduction in district heating networks with surfactant additives. WSEAS Trans. Circuits, Oct. 2004, Vol. 3, iss. 8, pp