Determination of Exchanged Goods Amount: Customer Knowledge + System Functionality

1. MMEElecture No. 4Determination of the amount of exchanged goods in the case when customer dos not know its value MMEE lc.No.4

2. „Motto“What to do "not knowing" what it is? - Create a method, based on the knowledge of system functionality, so you could find it, and verify that it works and gives good results. Then this method, by frequent applications, you can enhance and refine it or create new one. MMEE lc.No.4

3. MMEE • What Type Load (Daily) Diagram (TDD) is? • How do we create TDD? • How to correct TDD? • The settlement amount actually measured with the contractual Determination of the tradable goods amount between supplier and customer MMEE lc.No.4

4. Goods Suppliers Customers Money The basic scheme of interconnections between the supplier and the customer • The method of commodity exchange implementation on the market The mutual link is via commodity and cash flows • Customers want to buy goods • Looking for suppliers of goods • Suppliers will ensure supply • Customers pay for the delivery MMEE lc.No.4

5. The problem's exchange process of energy goods • The customer must provide the necessary quantity you want to buy • The supplier offers a price at which it is able to deliver the goods • Agreement shall be concluded on the implementation of trade • There will be the implementation of the supply of goods - measurement supply • There will be payment for the delivery ad1. The customer can not exactly determine the amount of goods (LD) for a period of delivery time, or the immediate value - must be performed continuously during delivery continual balancing by on the side supplier, or on the consumer side. ad4. The supplier is not always, in the given period of time, able to meet the delivery of the goods (loss of production) - the system must constantly keep manufacturing orwarehouse inventory balances, the law of conservation of energy. The measuring device is usually able to make the determination only of the exchanged goods = amount of work, but not its time dependence (immediate value = power). ad5.Payment for the delivery = price of goods should respect all the costs that were caused by the collection from the supplier system. MMEE lc.No.4

6. A A A B C D A A A B C C C B B Location of producers and consumers in ES MMEE lc.No.4

7. D A B C C B D A Linkin of exchange product entities - connecting consumption (couping) points - CCP Consumers systems FS Electricity consumption on VHV GDP Supplies system Location of supply and consumer systemsconnection: consumption on HV consumption on LV Personal use consumption on LV Wholesale customers - connection at high-parameterssupply (voltage pressure), optionally having ordered goods in highvolumes Small customer - connection parameters at low supply (voltage, pressure), parameters or having low consumption goods volumes MMEE lc.No.4

8. B A B A C C D C B A C A Delivery measurement between SS and CS - CCP FS Electricity Consumers systems GNP consumption on VHV Supply system consumption on HV consumption on LV Personal use consumption on LV – continuous metering with remote reading over 400 KW – continuous metering with remote reading with200-400 kW – non-continuous measurements with a local readout MMEE lc.No.4

9. A B A A B B C C A A Producers connection into the supply system Delivering system Distribution system FS Elektricity Distribution VHV Transmission system Distribution system HV Distribution LV – delivering points with voltages higher than 52 kV – delivering points with install power output over 1 MW – delivering points with continuous local measuring, 250 – 1000 kW – delivering points with non continuous measuring MMEE lc.No.4

10. A B C D The amount of traded goods in the ES P Pmax Pmin t 0 W= P*t there is traded 1 hour = 1 MWh = MW Supplies system Consumers system http://clients.rte-france.com/lang/an/visiteurs/vie/courbes.jsp MMEE lc.No.4

11. A B C D Determining the electricity required amount of different customers categories and its measurement Must determine the required amount - can be measuredP, W Must determine the required amount - can be measuredP, W Must determine the required amount - can be measuredonly W Must determine the required amount - can be measuredonly W MMEE lc.No.4

12. Substitute measurement method of Ctype replacing continuous metering (A or B) Method of typical load (daily) diagrams of electricity (TDD) is an alternative procedure for determining the size of the sampling group of customers with measurement type C . TDD method is a "approximation" to the real shape of the hourly electricity consumption MMEE lc.No.4

13. TDD method • Method of TDD is an alternative procedure for estimate determining the value electricity size of hour consumption groups customers with measurement type C, i.e. which replaces the continuous measurement in this group of customers. • For relevant solution is to use an alternative method of load profiles, which represent the type of electricity load diagrams for each of the selected groups of customers with a comparable nature of electricity consumption. MMEE lc.No.4

14. Normalized TDD (TDDn) The normalized TDD (index n) of delivery is 8760 relative values ​​of average hourly sampling year (8784 values ​​in a leap year), relative to the value of the maximum from annual average hourly values of measurement TDD samples. Average hourly values, used to determine the TDDn, are converted to normal climatic conditions (in 2005, the thirty-year national average daily temperatures). TDDn values ​​are in the range 0-1 and define the shape of the load profile of the group of end customers under normal climatic conditions. The total sum of the relative values ​​of average hourly values expresses the utilisation time of maximal value [hour / year]: MMEE lc.No.4

15. Normalized LD - TDDn • They replace the hourly real value in the CCP, which are equipped only with measurement of type C • Normalized TDDn 1 ph=Ph/Pmax 1 =Pmax/Pmax 0 0 h 8760 hours value of hourly consumption Oh=Wh= ph - years consumers consumption MMEE lc.No.4

16. Hour consumption of ith consumer estimated (planned) or measured annual consumption of i-th customer hour value of t-th type LD of yearTDD (8760 values​​) years utilisation time of maximal value Pmax of TDD MMEE lc.No.4

17. Distribution system balance Balance In distribution system in relevant region must fulfil power balance: Agreed electricity = Consumed Electricity + Losses • As agreed electricity as consumed electricity are measured in CCP by measurement types of A, B or C • The power losses in transport are calculated (unknown value) – for the calculation of rest load balance purpose of TDD are assumed as % value of agreed electricity (by unknown value is the measurement of C types) MMEE lc.No.4

18. Settlement of exchange of goods • Determined consumption estimation (O [Ws] ) in trade hour (h), together with measured value (hours values are measured only in A and B) composed total consumption in distribution network - total load. • Measured difference in defined hour represent difference between supposed consumption value and real value and is called rest load diagram (RLD = Z losses [Ws] ). • This rest will be paid by consumers of C type measurement as power losses in distribution system. • After that will be carried out the evaluation of the estimated and measured values ​​= deviation between the agreed value and the taken-value (estimated) arising between SS and CS arising on the spot market. • It shall be carried out payment settlement arising deviation = clearing deviation MMEE lc.No.4

19. Rest Load Diagram of l-th distribution system MWh (C -measurement ) D = balance of supply Z = losses consumption delivering MMEE lc.No.4

20. Influence of RLD RLD – in l-th DS in h-th trade hour: supply balance of electricity in h-th hour on the border with others DS continuously measured supply of A types in l-th DS continuously measured supply of A types in l-th DS MMEE lc.No.4

21. Influence of RLD losses in l-th distribution system in h-th hour percentage value of power losses in l-th distribution system assigned by ERÚ (energy regulation system operator) whole delivery to l-th DS in h-th hour continuous deliver measurement of B type in l-th distribution system supply to C type measurement of h-th hour in l-th DS MMEE lc.No.4

22. Adjustment values ​​for determining the hourly consumption of the customer with measurement type C • There is to the disposal: • RLD of l-th DS in h • sum of all consumers consumption values calculated by TDD for h-th hour of exchange in l-th distribution system • computed value from TDD for consumers in h-th hour of exchange trade MMEE lc.No.4

23. RLD payment • RLD is paid by C-type measurement consumers • Individual financial value for consumers of t-type diagram is calculated in h-th hour, in l-th DS as: MMEE lc.No.4

24. agreed values sjednané hodnoty real D C M p values d i , k S S E s d O O deviation i , k ¶ , i k Course of market realisation CS – clearing subject MEO – market electricity operator DSO – distribution system operator MMEE lc.No.4

25. TDD utilisation for hours consumption • Costumers without continuous measurement are divided in to defined TDD types, with the relative same shape of LD. • Each TDD type has its own specific hour need for power consumption • This need was measured on the statistic data at determined (base) outdoor temperature. • Under water forecast (or other factors) the consumption need can be correct to the preciously value. MMEE lc.No.4

26. Dividing of TDD • Possibilities how to create TDD can be based on: • consumption character, • consumption value, • tariff structure – more component price • combination privies points. • In CZ, TDD types was based on tariff structures from 1. 7. 2001 in ES. • With the respect to tariff structure were 7 types of TDD implemented. MMEE lc.No.4

27. TDD types tariff character, duration time customers n. single tariff double tariff double tariff single tariff single tariff double tariff double tariff double tariff NT = low tariff MMEE lc.No.4

28. Evaluation of statistical TDDsamples • Each class of TDD was monitored the total number of customers and the number of customers at the intervals consumption. • Defined precision of TDD. • Other criteria (failure of samples ...) • The number of measurement samples in each class TDD = 128 MMEE lc.No.4

29. Accuracy of the method • TDD method is only suitable for a longer time interval and the number of supply points to final customers in that group higher than about 1000 to achieve the desired national (only for regional with TDD5) error which does not exceed 10%. The level error is a value indicating the extent to which they may be monitored variables exist with respect to its mean value MMEE lc.No.4

30. Determination of the number of statistical samples Determination of the samples number is given by the formula of mathematical statistics, in which the required number of samples is determined by the reliability level, degree of change value and the accuracy level. In the case of ignorance the distribution law of the sampled values ​​is advisable to choose the values ​​of these criteria which are sufficiently large to ensure adequate accuracy. Therefore, the selected values must be able to ansure: • reliability level on 95%, i.e. for a range of two standard deviations • degree value changes on the level of 0.5 and - 0.5, i.e. the maximum probability of occurrence, the accuracy is chosen arbitrarily. • for the purpose of TDD system was chosen accuracy level of 10%, with respect to the cost measurement. For such values ​​of the selected criteria is available Yamaneho simplified formula that is a function only of the size of the precision level as the independent variable and the number of customers in the group. . MMEE lc.No.4

31. Yamaneho formula The value of the accuracy level depends on the number of samples = number of customers in the group n – total number of customers in a given TDD, e - accuracy level (value 0,1 = 10 %), V - required number of samples in the group. With the chosen level of 10% accuracy occurs the saturation, when the number of elements is on the level of 1000 units and sufficient number is equal to 100 pcs. In practice TDD it means that the number of measurement samples in all types is the same even the number of elements in the groups are much greater. The required number of samples have to be increased by 30%, which form a reserve for cases where measurements are for any reason, incomplete or otherwise unusable MMEE lc.No.4

32. 10 000 2 V = N / (1+N * e ) 1 000 0,10 0,07 0,05 100 0,03 Rrepresentative number of samples for a given accuracy (V) 0,01 10 1 1 10 100 1 000 10 000 100 000 1 000 000 Total number of PCC ( N ) The dependence of the samples number in the total number of consumers at different levels of accuracy values ​​(e) MMEE lc.No.4

33. 1 h å TDD = T n u 0 8760 Normalized Type Daily Diagram TTDn TDDn MMEE lc.No.4

34. What affects the demand value ? • There were set out the basic relations between temperature and load, represented by the TDD. • It has been shown that the relationship between temperature and the given TDD is the same as the bond between the temperature and the consumption based on the TDD. • The only difference is the numerical representation, which is in direct proportion with the work carried by diagram (energy). MMEE lc.No.4

35. The possibility to use TDD • Static TDD method is based on determining normalised TDD for designated groups of final customers with measurement type C and their conversion into actual weather conditions on day D. • Dynamic TDD method is also based on the normalized TDD, but they are not converted to actual weather conditions on the day D (used for static methods). There is based on measurements of samples on day D and data transmission, on the basis of which consists of standard 24 values ​​of TDD of individual groups of final customers on day D MMEE lc.No.4

36. Procedure for the determination of normalised TDD LD, PE = f (t), can be considered as a time series. A time series is a sequence of values ​​of a statistical character (indicators) arranged in terms of time away from the past to the present. Indicator (PE) must be materially and spatially defined consistently throughout the period. The indicator has continuously changes over time, time series indicates the indicators status in certain moments. The status values ​​may not directly depend on the length of the interval between readings (at longer intervals may of course lead to greater change.). Simple counting indicator values ​​of this series does not make sense - we get a value that has no meaning MMEE lc.No.4

37. Composition of the time series • Time series can be divided into three components: • Trend (T) - main direction of development of a long-term trend (increasing range, decreasing range, etc.) • Periodic (P), oscillations - periodic fluctuations around the trend, long-aligning periodic series: • fluctuations - having a specific frequency, period length, amplitude (size deviation). Depending on the length fluctuations are: • seasonal - period of one year, fluctuations within a year in certain months and quarterscyclic - period longer than one yearshort - period shorter than one year, fluctuations in months, in weeks, in days • Randomly (e-residue - error estimate) – small fluctuations causedby intangiblesreasons (this component in the time series is always). The basic assumption is that the random component is a random variable with zero mean value (balancing positive and negative fluctuations). MMEE lc.No.4

38. Smoothing of time series Trend has a sigmoid course. Time series first moving away from a constant value with increasing speed and then after crossing the inflection point is approaching at low speeds to a constant (Gompertz curvehas the center of gravity behind the inflection point). For example, time course of the sales volume of consumer goods when the sale first gooes slowly growing interest in the goods and then gradually reached saturation. Similarly to the effect of temperature on load PE (t). Decreases with rising temperature and decreasing increasing. MMEE lc.No.4

39. The influence of different climatic conditions - Regions • Czech Republic, in terms of geographic sizes, is small country, so that thera are not drastically different local teritory conditions given by show the latitude and longitude. • Areas with higher altitude, which affects the nature of consumption occupy a small area, and include a small portion of the volume of consumption (each region has its own specific area). • Character of the settlement, and therefore the nature of consumption is not very different depending on the area (the greatest weight in agglomerations). Nationwide TDD applications - in all regions of the same shape TDD MMEE lc.No.4

40. The impact of weather (temperatures) to TDD • Temperature conversion takes place according to the following formula (HD, the number of hours in the day): • TDD corrected = k. TDD normalized MMEE lc.No.4

41. The impact of weather on TDD • The conversion is done for each hour and each class TDD • For all hours of the day are used, one normal value and one value smoothed by actual temperature • Smoothing out is done by the following formula (smoothing is respected by the delayaltered temperature)): • Ti = Ti/2+Ti-1/4+Ti-2/8+ ……. + Ti-9/1024 MMEE lc.No.4

42. The procedure for the determination of normal TDD LD, PE = f (t) shoud be considered as a time series. The time series is a sequence of values of certain statistical sign (indicator) arranged in terms of time away from the past to the present. Indicator (PE) must be materially and spatially defined consistently throughout the period. The indicator has continuously varies in time, the time series indicates the status indicators in certain moments. The status values may not directly depend on the length of the interval between readings of values (at a longer interval, however, can understandably lead to greater change.). Simple counting indicator values in this series does not make sense - we get a value that has no meaning MMEE lc.No.4

43. The value of time-series • Sum - Additive Model – yi = Ti + Pi + ei • Multiplying - multiplicative model - yi = Ti * Pi * ei • Multiplicative model can be converted into additive components with logarithmic transformation: MMEE lc.No.4

44. Smoothing out of time series Smoothing can be determined by the trend component of time series, ie. to cleanse it from periodic and random variations. We are looking for a trend indicator as a function depending on the time using regression analysis. In simpler cases, it can be done by the method of least squares. The trend function (mathematical relationship) can be used to predict the settlement for the whole time series Vyhlazením lze zjistit trendovou složku časové řady, tj. očistit ji od periodického a nahodilého kolísání. Hledáme trend jako funkci závislosti ukazatele na čase pomocí regresní analýzy. V jednodušších případech metodou to lze provést metodou nejmenších čtverců. Trendovou funkci (matematický vztah) lze použít k předpovědi vyrovnání pro celou časovou řadu. Gompertzova (S – metoda): , MMEE lc.No.4

45. Regresní rovnice pro TDD Základem při tomto postupu je vysvětlená dekompozice průběhu zatížení na více složek (průběhů) s jasně definovaným vztahem k teplotě – první tři členy rovnice. Tyto složky jsou definovány pomocí regresní rovnice, jejíž konkrétní podoba vyjadřuje konkrétní vztah zatížení na teplotě. Poslední člen je regresní člen vyjadřující vliv změny teploty oproti normálové. Na základě dříve provedených analýz je tento trend - regresní rovnice, vyjádřena pomocí modifikované exponenciální závislosti. Potom celková modifikovaná exponenciální regresní rovnice (s využitím logistické trendové funkce; S -křivka) má tvar: MMEE lc.No.4

46. Regresní rovnice pro TDD denní průměrná hodnota odhadovaného (teoretického) průběhu TDD, konstantní složka nezávislá na teplotě, regresní koeficient trendu, pořadí dne v roce, regresní koeficient normálové teploty, denní průměrná hodnota normálové teploty, denní průměrná hodnota skutečné teploty, regresní koeficient udávající amplitudu nelineární složky, regresní koeficient udávající teplotu v inflexním bodu nelineární funkční závislosti, regresní koeficient udávající rychlost nasycení nelineární složky MMEE lc.No.4

47. Vliv teploty MMEE lc.No.4

48. Vyhlazení skutečných a normálových teplot Vyhlazením teplot se respektuje vliv určité časové setrvačnosti v obecné závislosti zatížení na venkovní teplotě. Dosahuje se tak zpravidla lepších korelačních vazeb mezi skutečným průběhem zatížení a průběhem zatížení odhadovaným na základě regresních modelů. MMEE lc.No.4

49. Vliv počasí na TDD • Teplotní přepočet probíhá dle následujícího vzorce ( HD je počet hodin v daném dni ): TDD přepočtený = k . TDD normalizovaný MMEE lc.No.4