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ERCOT Load Forecasting Forum

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1 ERCOT Load Forecasting Forum
Pattern Recognition Technologies (PRT), Inc. On-Line Load Forecasting Services Al Khotanzad, Ph.D., P.E. President PRT, Inc. 17950 Preston Road, Suite 916 Dallas, Texas (214) ERCOT Load Forecasting Forum January 24, 2007

2 Corporate Profile Founded in 1994 Products & Services
Online load and price forecasting services Stand-alone load and price forecasting software Custom forecasting solutions Clients Over 90 energy firms consisting of Utilities in North America & Overseas ISOs, Municipalities, Coops. Government Agencies Power marketing and trading organizations The Electric Power Research Institute (EPRI) First company to develop a commercial neural network based load forecaster in the early 90’s – ANNSTLF for EPRI PRT, Inc.

3 Load Forecasting Accurate forecast of future demand required by all entities involved in the energy markets Electric Utilities Independent System Operators Power Marketers Different forecast horizons Long Term: Several years out – required for planning purposes Mid Term: Several weeks to months – scheduling maintenance, planning fuel supply, transactions Short Term: Next hour to next week – daily operation, energy transactions, reliability studies PRT, Inc.

4 Short Term Load Forecasting
Hourly or sub-hourly forecasts starting from next hour to next seven to ten days Forecasts used for: Unit commitment selection of generators in operation start up/shut down of generation to minimize operation cost Hydro scheduling to optimize water release from reservoirs Generator type coordination to determine the least cost operation mode (optimum mix) Interchange scheduling and energy purchase Transmission line loading Power system security assessment Accuracy has significant economic impact Even a 0.5% improvement in accuracy can result in thousands of dollars in savings PRT, Inc.

5 Factors Affecting Short Term Load
Factors affecting short-term load are: Mix of customer in the service area (residential, commercial, industrial) Weather condition (temperature, humidity, cloud cover, wind speed) Seasonal effects & recent load trends Time of day (morning, afternoon, night) Day of week (weekdays, weekends) Holidays (Christmas, New Years) Special events (popular sporting events or TV shows) Demand side management Random disturbances Forecasts used for: Unit commitment selection of generators in operation start up/shut down of generation to minimize operation cost Hydro scheduling to optimize water release from reservoirs Generator type coordination to determine the least cost operation mode (optimum mix) Interchange scheduling and energy purchase Transmission line loading Power system security assessment Accuracy has significant economic impact Even a 0.5% improvement in accuracy can result in thousands of dollars in savings PRT, Inc.

6 Example of Load and Temperature
PRT, Inc.

7 Major STLF Techniques Any STLF technique attempts to model the relationship between the load and factors that affect it – these relationships are nonlinear and complex Regression models Stochastic time series Spectral decomposition Similar-day search Intelligent system based models Superiority of intelligent system based techniques have been demonstrated in many studies PRT, Inc.

8 PRT’s LF Technologies Products & services are based on cutting-edge intelligent system technologies of: Artificial Neural Networks Fuzzy Logic Genetic Algorithms/Evolutionary Computing PRT, Inc.

9 Artificial Neural Networks (ANNs)
Neurologically inspired systems consisting of highly interconnected elementary computational units (neurons) Distributed processing by neurons results in intelligent outcome ANNs learn to perform a desired task directly from examples using special training algorithms ANNs can generalize; after training, they can produce good results for data that only broadly resembles the data they were trained on originally ANNs are nonlinear systems, well suited for real world problems that are often nonlinear PRT, Inc.

10 Forecasting Using ANNs
A key feature of ANNs is their ability to learn a complex pattern mapping, i.e., model the underlying relationship between a set of variables and an outcome that is a function of them – Future Load – Function of past loads and weather, recent load trends, upcoming weather, calendar effects Train with historical data (examples of the underlying relationship) A properly trained ANN can predict the outcome of the modeled process based on the available observations ANN based predictors employed in a wide variety of forecasting applications such as prediction of: electric load, weather, gas consumption, stock market, economic trends time series data, future sales, traffic patterns and grade point average of students PRT, Inc.

11 Unique Aspects of PRT ANN Forecasters
Architecture of ANN specifically designed for electric load forecasting Optimal set of inputs selected for load forecasting application No need for frequent re-training Quick response to deviations between forecast and actual load Special algorithms for unusual days, e.g., weekday holidays PRT, Inc.

12 Fuzzy Logic Fuzzy logic (FL) is a means to transform subjective/expert knowledge about a process expressed in the form of linguistic rules into computer algorithms. FL employs fuzzy sets, fuzzy membership functions and fuzzy if-then rules to model the uncertainty in nature, and express the knowledge A fuzzy set is a set without a crisp, clearly defined boundary, and can contain fuzzy variables with a partial degree of membership PRT, Inc.

13 Fuzzy Rule & Membership Function
An example of a typical fuzzy IF-Then rule : IF next-day temperature is hot, and today’s temperature is hot, THEN next-day load is high Subjective interpretation of “hot temperature” or “high load” Characterized by fuzzy membership function – an example shown In Mamdani model both fuzzy premise part and consequence part are represented in linguistic terms. In Takagi-Sugeno model, linguistic term is only for the fuzzy premise part PRT, Inc.

14 Fuzzy Logic Based Load Forecaster
Develop applicable fuzzy membership functions Extract relevant IF-THEN rules from historical data – There could be hundreds of such rules During the forecasting phase several of the rules become activated along with some of the fuzzy membership function Fuzzy inference engine converts all this information into a final crisp forecast PRT, Inc.

15 Genetic Algorithms (GAs)
Genetic Algorithms (GAs) are optimization algorithms that are based on the concept of natural evolution GAs can find the optimal solution quickly and efficiently, especially when there is little information about the solution available. GAs emulate natural evolution, and make use of four operators, including reproduction, crossover, mutation, and survival of the fittest to produce and keep the optimal solutions. PRT, Inc.

16 GA Based Forecaster Create M sets of forecasts (in random) for a given set of actual historical data Sort based on accuracy Retain the top K most accurate sets (stronger solutions) and discard the rest (weaker solutions) – survival of the fittest Use the retained K sets as parents to create a second generation of M solutions through mutation & crossover – repeat the process After several generation, the top K solutions converge toward a single solution – Strongest solution This is the optimal solution used as the final forecasting model PRT, Inc.

17 PRT’s e-ISOForecast Price & Load Forecasting Service
e-ISOForecast is an on-line real-time price & load forecasting service that has been set up for all wholesale power markets/ISOs in North America ERCOT, PJM, NY-ISO, ISO-NE, MISO, CA-ISO, ONTARIO IESO, ALBERTA AESO Hourly forecasts for current day and six days beyond Hourly load forecasts for one year out using various simulated weather scenarios Forecasts are posted on Subscribers use a Web browser to access and download the forecasts – available 24/7 Forecasts are updated every hour or faster based on the most recent price/load/weather data that become available Weather forecasts are used in the models - updated several times per day PRT, Inc.

18 e-ISOForecast Price & Load Forecasts
ERCOT System-Wide & Congestion Zone Load Forecasts Zonal Market Clearing Price Forecasts PJM System-Wide, Regional and Zonal Load Forecasts Real-Time & Day-Ahead LMP Price Forecasts ISO New England (ISO-NE) System-Wide & Zonal Load Forecasts Zonal Real-Time & Day-Ahead LMP Price Forecasts New York ISO (NYISO) PRT, Inc.

19 e-ISOForecast Price & Load Forecasts
Midwest ISO (MISO) System-Wide Load Forecast Real-Time & Day-Ahead LMP Price Forecasts for Five Hubs and Various CPNs California ISO Zonal Supplemental Real-Time Price Forecast s ONTARIO EISO System-Wide Price Forecast ALBERTA AESO PRT, Inc.

20 Forecasting Engines Multiple models based on different technologies run in parallel generating independent forecasts A top layer of intelligence decides to: Select one of the forecasts as the final forecast Combine multiple forecasts (“Combination of Experts”) into a final forecast Accuracy is improved over use of a single modeling technique PRT, Inc.

21 Weather Data PRT has affiliations with two major weather service providers, WSI and Meteorlogix Most free internet based weather forecast services simply provide forecasts generated by NWS or other computer models Weather service providers bring human meteorologists in the loop who scrutinize/edit computer generated forecasts Weather forecasts updated several times throughout the day Actual temperature updated every hour and with every update, new load forecasts are generated PRT, Inc.

22 Access via the Web Forecasts are posted to a dedicated password protected page Can be accessed using any standard Web browser from any computer Provides easy access for all in the company Forecasts are displayed in tabular and graphical forms Actual data of previous day and any available data of current day are displayed Forecasts can be downloaded in EXCEL format Other statistics including actual prices of past week, similar day comparisons and price bands are provided PRT, Inc.

23 e-ISOForecast Main Page
PRT, Inc.

24 e-ISOForecast PJM Segment
PRT, Inc.

25 e-ISOForecast Load Forecast View
PRT, Inc.

26 e-ISOForecast LF View - Graphical
PRT, Inc.

27 e-ISOForecast LF Performance for 2006
Forecasts Recorded at 8 am CT Load: Hourly MAPE/ Daily Peak Load MAPE Temperature: Hourly MAD/Daily Peak Temp MAD Market After-the-Fact CurrentDay Next Day Day 3 Day 4 Day 5 ERCOT Load 1.51/1.84 1.81/2.69 2.99/3.48 3.50/3.87 3.99/4.59 4.54/5.13 Temp 1.38/1.73 2.14/1.98 2.41/2.13 2.86/2.68 3.21/3.02 PJM East 1.24/1.33 1.32/1.91 2.49/2.64 2.88/2.93 3.25/3.45 3.67/3.81 1.48/2.00 2.56/2.46 2.73/2.78 3.20/3.46 3.68/4.05 ISONE 1.70/1.60 1.24/1.88 2.30/2.32 2.73/2.91 3.04/3.31 3.34/3.60 1.49/2.00 2.47/2.57 2.76/2.93 3.27/3.62 3.78/4.32 NYISO 1.15/1.28 2.21/2.40 2.56/2.59 2.73/2.74 2.93/3.05 3.26/3.47 2.72/2.81 3.04/2.99 3.22/3.23 3.53/3.60 3.98/4.30 MISO 1.21/1.39 1.21/1.83 2.29/2.54 2.79/3.05 3.20/3.53 3.54/3.87 1.29/1.70 2.15/2.32 2.37/2.48 2.82/3.05 3.32/3.57

28 e-ISOForecast Performance for Forecast of Next-Day ERCOT Total Load – 2006 i Forecasts Recorded at 3:00 PM of Previous Day Month Load MAPE Temp MAD Jan 2.10/2.02 2.13 Jul 2.51/2.77 1.71 Feb 3.01/3.18 3.14 Aug 2.70/2.81 2.06 Mar 2.52/2.85 2.42 Sep 3.86/5.03 2.35 Apr 3.17/4.11 1.78 Oct 3.53/5.06 2.36 May 3.05/3.57 1.83 Nov 2.21/2.25 2.21 Jun 2.70/2.92 1.62 Dec 2.45/3.49 2.14 PRT, Inc.

29 Comparison of PRT and ISO LF Performance
Forecasts Recorded at 8 am CT Hourly MAPE/ Daily Peak Load MAPE Market Period By Current Day Next Day Day 3 Day 4 Day 5 ERCOT 1/1-12/31 PRT 1.81/2.69 2.99/3.48 3.50/3.87 3.99/4.59 4.54/5.13 ISO 2.28/2.96 3.22/3.45 3.75/4.08 4.56/4.79 5.04/5.40 PJM East 1.32/1.91 2.49/2.64 2.88/2.93 3.25/3.45 3.67/3.81 1.70/2.00 3.30/2.91 3.32/3.23 3.79/3.60 4.27/4.13 ISONE 1.24/1.88 2.30/2.32 2.73/2.91 3.04/3.31 3.34/3.60 3.08/1.77 3.23/2.15 - NYISO 12/5-12/31 0.64/1.06 1.51/1.54 1.74/1.85 1.99/2.29 2.10/2.34 2.54/2.62 2.22/2.09 2.12/1.59 2.08/1.43

30 e-LoadForecast Service
An online load forecast service for company-specific load data Standard Service: Hourly/sub hourly forecasts for current day and six days beyond Extended Service: Additional Hourly/sub hourly forecasts for several months and years out User only needs to: Provide historical load data for initial model training Upload the most recent actual load data as it becomes available (via FTP, , provided Excel interface) All the required actual and forecast weather data acquired by PRT from Load and weather data quality checked and validated Forecasts posted to a dedicated and secure website in tabular and graphical forms PRT, Inc.

31 e-LoadForecast Service, Cont’
Forecasts are updated every hour with preceding hour’s actual observed weather Forecasts are updated any time an actual load data is uploaded by user 24/7 access through Via Internet at any location An Excel Interface with built-in functions enabling user to remotely interact with the forecasting system FTP ERCOT uses this service for forecast of its eight weather zones PRT, Inc.

32 Forecasting Engines Multiple models based on different technologies run in parallel generating independent forecasts A top layer of intelligence decides to: Select one of the forecasts as the final forecast Combine multiple forecasts (“Combination of Experts”) into a final forecast Accuracy is improved over use of a single modeling technique PRT, Inc.

33 Weather Data PRT has affiliations with two major weather service providers, WSI and Meteorlogix Most free internet based weather forecast services simply provide forecasts generated by NWS or other computer models Weather service providers bring human meteorologists in the loop who scrutinize/edit computer generated forecasts Weather forecasts updated several times throughout the day Actual temperature updated every hour and with every update, new load forecasts are generated PRT, Inc.

34 Other Features The provided Excel Interface allows user to:
Modify forecasted temperatures and generate corresponding load forecasts – “What-If” scenarios Modify predicted morning and/or afternoon peak loads. Forecasts for other hours are reshaped accordingly View load and temperature of three most similar days (temperature wise) in the history PRT, Inc.

35 Access via the Web - View & Download
Forecasts are posted to a dedicated password protected page Can be accessed using any standard Web browser from any computer Provides easy access for all in the company Forecasts are displayed in tabular and graphical forms Actual data of previous day and any available data of current day are displayed Forecasts can be downloaded in EXCEL format PRT, Inc.

36 Access via Excel Interface – View, Download & Interact
An Excel interface with easy-to-use built-in features Download and view most current load and temperature forecasts in tabular and graphical forms Modify forecasted temperatures and generate corresponding load forecasts Modify predicted peak loads and reshape load forecasts accordingly Download and view three most similar days Upload actual load updates to PRT’s servers PRT, Inc.

37 Profile Based Forecasting
Retailers operating in deregulated markets work with individual accounts that may not be metered hourly (e.g., residential load) Energy transactions and settlements are done based on hourly demand Hourly load is simulated using pre-specified standard load profiles for client type To forecast their retail load, load profile for each account must be scaled appropriately to account for pattern of usage by that account Profile based module of e-LoadForecast – User provides: List of current accounts in the portfolio along with their corresponding profile type The historical usage data for each account Backcasted profiles for corresponding profile types are used to develop a profile multiplier (scale factor) for each account using historical meter reads. Forecasted standard profiles are multiplied by the scale factor to get the final hourly forecast PRT, Inc.

38 Mid-Term/Long-Term Module
Optional service includes mid-term/long-term hourly load forecast Forecast horizon can be extended to five years out ANN technology is used – Models are different from those used for short-term forecasting Impact of load growth is considered Weather forecast is needed for the forecast horizon Simulated using historical weather data Three scenarios of “Normal”, “Hot”, and “Cold” available for each month in forecast horizon Additional scenarios for generating “High Load” and “Low Load” cases Two statistical methods available for simulation of scenarios from historical weather data Tools are provided for easy manipulation of simulated weather – user can build heat waves/cold fronts PRT, Inc.

39 Quality Control Extensive quality control system in place
Actual load and temperature data continually quality checked Detected anomalies such as spikes and gaps corrected Every day accuracy of load and temperature forecasts for various forecasts horizons are computed and reviewed by our experienced staff Corrective action taken if degradation in quality detected Analysis of the cause Calibrate forecasting models Use of different kind of forecasting engines PRT, Inc.

40 Forecasting Service Advantages
Uses state-of-the-art load forecasting models More accurate forecasts than in-house systems More economical than maintaining an in-house system Frees up valuable manpower & resources No data hassles, IT overhead, software maintenance & upgrade Performance continuously monitored by specialists with extensive experience and background in forecasting Models are continually calibrated and upgraded Convenient access to forecasts for all who need it in the organization Unlimited use by all in the organization PRT, Inc.


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