** Update: The webinar recording is available at:
http://www.mathworks.com/videos/electricityloadandpriceforecastingwithmatlab81765.html
This example demonstrates building a short term electricity load (and price) forecasting system with MATLAB^{®}. Two nonlinear regression models (Neural Networks and Bagged Regression Trees) are calibrated to forecast hourly dayahead loads given temperature forecasts, holiday information and historical loads. The models are trained on hourly data from the NEPOOL region (courtesy ISO New England) from 2004 to 2007 and tested on outofsample data from 2008.
The application includes an (optional) Excel front end which enables users to call the trained load forecasting models through a MATLABdeployable DLL.
The document titled "Introduction to Load & Price Forecasting Case Study" will guide you through the different components of the analysis.
If you do not have all of the required toolboxes, you can still view the results of running the analysis by clicking on one of the HTML reports below.
NOTE: The Access database shown in the webinar is not provided with this archive due to size restrictions. The equivalent data sets are provided in MATfiles in the folders Load\Data and Price\Data for the load and price forecasting studies respectively. The raw data files can be obtained directly from ISO New England (www.isone.com)
MORE ON LOAD AND PRICE FORECASTS:
Accurate load forecasts are critical for effective operations and planning for utilities. The load forecast influences a number of decisions including which generators to commit for a given period, and acutely affects the wholesale electricity market prices. Load and price forecasting algorithms typically also feature prominently in reducedform hybrid models for electricity price, which are some of the most accurate models for simulating markets and modeling energy derivatives. The electricity price forecast is also used widely by market participants in many trading and risk management applications.
Ameya Deoras (2020). Electricity Load and Price Forecasting Webinar Case Study (https://www.mathworks.com/matlabcentral/fileexchange/28684electricityloadandpriceforecastingwebinarcasestudy), MATLAB Central File Exchange. Retrieved .
1.7.0.1  Updated license 

1.7.0.0  Minor bug fix, added more error checking 

1.4.0.0  Updated readme document and description. No code changes. 

1.2.0.0  Added link to recorded webinar. No change to files. 

1.1.0.0  Changed intro document to PDF 
Inspired by: Intelligent Dynamic Date Ticks
Inspired: Commodities Trading with MATLAB
Create scripts with code, output, and formatted text in a single executable document.
Hi
I am unable to compute forecasting in excel file. It shows error.
hi Ameya and everyone
i can't find the file data.mat to have hourly raw data.
and i have problem finding it in isone.com.
please help me. my email adders: s_shaiyan@yahoo.com
Hello everyone! I tried my excel data for short term forecasting it's still not working. Please help me. rataabnuyo@gmail.com
Hi all, everyone can help me understanding how do i have to change the code as i can use it with a dataset.xlsx??
Thanks to every one :)
Does anyone still have the updated code? or data set. I would appreciate it if u could lend a hand. Thanks
waqarwaheed@hotmail.com
The forcaster.xlsx file is not working.
Hi all, tried working the model with 2019 hourly data and it’s not working. Please help with modifications, menzilennon.dube@gmail.com
Hi does anyone have the dataset? It would be great if you could send it to me at craigheropiero@gmail.com
The forcaster.xlsx file is not working. So I can't test the tranined model with some new data.
Can anyone help me regarding this?
Does anyone still have the updated code? or data set. Would appreciate if u could lend a hand. Thanks
I need matlab code on how to model a short term load forecasting using artificial neural network for my master project.my email ID is :iavokeo@gmail.com
Please I need matlab code on how to model a short term load forecasting using artificial neural network for my final year project. Thanks
Hi guys, could you please send me the data to the email: rok.ciglar@gmail, because I can not open web site... This will mean a lot to me. Thanks!
Dear Ameya, all
Can anyone make me understand the function (or notion) of genPredictor function?
Thanks
Hi does anyone have the dataset? It would be great if you could send it to me at akashm26@gmail.com
Hi, i have the same Problem as Muhammad Asad.
@ M. Asad: did you solve this issue?
will be grateful for any Help from anyone.
thx
Hi, excel application is not running properly. It is giving message "Error in Forecaster.Class1.1_0: Invalid calling syntax for the "predict" command. Type "help predict" for more information".
Can anyone help me?
Hi, I could not access the data. Thank you, one of my friends sends the data to me...haniehallahkarami72@gmail.com
Thanks a ton Fred. Will be forever grateful to you.
hi guys, I am not able to find the datasets. could anyone please send me the data to the email: ppoonam_phd18@thapar.edu
Hi guys, could you please send me the data to the email: sevenx@abv.bg. I can not open the site.
Thank you in advance!!
Hi guys,
This is the latest direct link to dataset:
https://www.isone.com/isoexpress/web/reports/loadanddemand//tree/zoneinfo
Thanks,
Fred
Hie guys, if anyone has the dataset for this example please email on bongz82@yahoo.com
if someone can send me (tolias96@gmail.com) the dataset it would be great!
Hello guys, does anyone have the dataset for this example? If you can share it with me please. My email address is jos.idelfonso@gmail.com. Thank you in advance.
Can I use equest data for short term load forecasting? I am doing a project on BEMS for shopping malls. Any help is appreciated. Thank You!
Hi Guys,
I am new to this so i don't exactly know how to run the codes. Would appreciate it if anyone can teach me how to do it step by step. Can the codes also run in Matlab R2017b? Thanks a lot!
Desmond
Hello Matlab mates, I want to create a project in MATLAB that can detect
# No of faces in realtime through webcam or CCTV
# save the values in the database how many customers came to shop or brand today
# and then I want to apply some Artifical intelligence to predict and forecast how many customers come in next day.
*but I don't know how to implement the prediction or forecasting code in Matlab*
hi guys, for this coding.. could anyone explain the purpose of data.Numdate ? i found in not make sense value when converted to datetime? for example 731947.0000 = 39040101
hi Ameya, hope you healthy, i just want to ask how you convert numdate 731947.0417 to real time? hope you could help.tq
Does anyone has the files that needed from ISO New England (www.isone.com)?
hello~
the iso new england webistite is not accessible.
someone please provide me raw data files .
please either upload or send it to me.
These models are really useful, the structure of codes is simple to understand, the results are beatiful, I like. VERY NICE WORK!
hi everyone,
the iso new england webistite is not accessible.
someone please provide me raw data files .
plz either upload or send it to me...
good
Hello, I would like to ask you about the load forecasting presentation. When I have already build the matlab compile for excel add in but I do not know how to add or import figure into excel spreadsheet. Could you tell about? Thanks in advance.
Best regards!
The data is not available
Hi everybody,
I am having trouble downloading the data from
www.isone.com
can somebody help me with this problem?
Maybe somebody can upload it for me or send it to me?
that would be very nice
thanks in advance
Nisarg
good
hi. how can I run this progam?
I cant link the data to main file,plz help me?
When I run the visual query builder, it asks for a user and pass!! anyone have the same issue?
Hi Ameya & All Others
Thanks for providing detailed Electricity Load and Price Forecasting example.
The version that I have 'MATLAB R2013b' won't recognize the 'genPredictors' function.
Am I missing a Toolbox or do you have any idea what might be the probelm?
Thanks
Baran
I want to generate a power consumption graph. I have measured data (power, energy) for every two seconds, for say three year.
Challenge: to write a time defined matlab program that plots every measurement (scatter) for any given day or days (between 00:00 & 24:00). I hope this is clear....requests for more clarity are welcome.
Thank you all
Im pretty new with NN´s but i like this program. Have one question, can be this program edited for predicting only temperature ? Any tips are appreciated, thanks :)
Hi has anyone modified it for long term forecasting ?
i am new for this
can you tell me how to run all file step by step
when i run errors in all files
can this code run in matlab 2008a or 2013a
Hello. I downloaded these files and compiled LoadForecast.m as class and other files and folders as helper files and folders. Everything went OK and compiler generated .dll and .bas files. I linked those bass files in .xlsm file, but when I press compute forecast it doesn't show "Neural Net" (files with 0s) it shows only tree model result.
I don't know if it is relevant, but in holidays file dates are written like this: 01.01.2007, but matlab needs format like this 01012007. I compiled default files and then programmatically changed "." to "" in dates, still "Neural Net" doesn't work in both cases.
Please help me. I will appreciate any response!
Hi everybody,
I am having trouble downloading the data from
www.isone.com
can somebody help me with this problem?
Maybe somebody can upload it for me or send it to me?
that would be very nice
thanks in advance
Dorian
Hi everybody,
I am having trouble downloading the data from
www.isone.com
can somebody help me with this problem?
Maybe somebody can upload it for me or send it to me?
that would be very nice
thanks in advance
Dorian
Mr. Deoras,
I am trying to replicate your procedure. I have hit a block when I try to perform a forecast i.e.
forecastLoad = sim(net, testX')';
I get a maximum variable error.
From your data, testX is 17544 x 8.
The error message is as follows:
Maximum variable size allowed by the program is exceeded.
Error in repmat (line 92)
B = A(mind,nind);
Error in fixunknowns.apply (line 14)
meanX = repmat(settings.xmeans,Q);
Error in nnMATLAB.pc (line 28)
pi = hints.inp(i).procApply{j}(pi,hints.inp(i).procSet{j});
Error in nncalc.preCalcData (line 20)
data.Pc = calcMode.pc(net,data.X,data.Xi,data.Q,data.TS,calcHints);
Error in nncalc.setup1 (line 118)
calcData =
nncalc.preCalcData(matlabMode,matlabHints,net,data,doPc,doPd,calcHints.doFlattenTime);
Error in network/sim (line 283)
[calcMode,calcNet,calcData,calcHints,~,resourceText] = nncalc.setup1(calcMode,net,data);
Error in Load_forecasting_test (line 38)
forecastLoad = sim(net, testX')';
Thank you, and great program otherwise.
when i run the excel interface i get the following error :
runtime error '1004' method 'paste' of object '_worksheet' failed
Dear Ameya Deoras
I have a concern about the application made in matlab for forecasting electricity demand in the short term, I'm done my thesis basing on this application, my question is that amendments should do in the loadforecast function if I have variables temperature'm driving variables are: historical date, time and electrical demands from 2010 to 2013, and make the necessary modifications in the LoadScriptNN script and it worked perfectly but I loadforecast function does not work I get the forecast to zero .
I noticed for the genPredictors function, some of the inputs to the short term forecasting model is prevDaySameHourLoad and prev24HrAveLoad. It seems that the prev24HrAveLoad uses the current day load and averages it on a 24 hour basis and the prevDaySameHourLoad uses the load from the previous day. I m not sure how these 2 inputs can be used to predict the next day load forecast for the ANN model. For example if today is Sunday and I want to predict the load for tomorrow (Monday) and I m running the load forecast application today at 1 PM, I can't use prevDaySameHourLoad as an input because Sunday is the previous day for the forecasted day Monday and I wouldn't have the 24 hour historical data for Sunday as I m running the program at 1PM on Sunday, so data from 1 PM up to midnight is unknown. Second the prev24HrAveLoad input depends on the actual load data for that day, which for this example would be the load data that I m forecasting for the next day (Monday). I m not sure how these 2 inputs can be used to predict the day ahead load if it requires historical data that you might not have yet.
When running the forecaster, I find that each time I run the codes, I get a different forecast/model for the loads. Is there a way to guarantee a consistent forecast model or is this always the case given that the neural network may be ending in a different local minima. Thank you for your help.
Ameya:
could you please tell me what did you mean by daily5dayHighAve and daily5dayLowAve in the genpredictor function?
% Long Term Forecast Predictors
X = [data.DryBulb data.DewPnt daily5dayHighAve daily5dayLowAve data.Hour dayOfWeek isWorkingDay];
Dear Ameya,
In order to forecast the electricity price of the day ahead Dutch market I am using neural networks and real data from 20072011.
I constructed the X matrix as you said in the webinar for load forecasting and proved with different combinations. The one with gives me the lower MAPE value consists of 8 inputs (Hour dayOfWeek isWorkingDay prevWeekSameHourPrice prevDaySameHourPrice prev24HrAvePrice prevDayNGPrice prevWeekAveNGPrice), but I can't reduce this value more than 11%.
I need to achieve better accuracy but I don't know whar should I change. Could you send me an example of who to forecast the day ahead electricity price? My email is fran90_7@hotmail.com
Thank you in advance.
Kind regards,
Jose Francisco Bolado
Dear Ameya,
I tried to run the loadscriptNN but everytime it went to fatal error. I needed to close the matlab.
I also tried to follow your webinar but there is an error in the fetchDBLoaddata. It said "Undefined function or method 'fetchDBLoadData' for input arguments of type 'char'". Please clarify this. Thank you.
Dear sir,
I hope you are in good health.
Sir I am using Matlab NN toolbox and try to call user define function to train the neural network.
But I have problem to call the user define the function in Matlab script.
Sir let me know how i can call these function to train the NN (in NN toolbox).
Dear Deoras,
In order to forecast 'balancing system marginal price (smf)' of Turkish electricity market, i used load, dayahead price (sgof) and the difference between upregulation volume and downregulation volume in MWh (nth) as inputs. When i give lagged nth (previous day and previous week same hour nth) only,the forecasting performance is bad, however when i give lagged nth with current nth (i.e kth hour nth for predicting the kth hour smf) forecasting performance is really improved successively. The problem is that forecasting nth for a future hour is a challenging task and the performance of forecasting nth is not so good. I want to give a range of current nth instead of one value (maybe probability dist. of nth / monte carlo) in order to forecast a range of smf instead of one value (probability dist.of smf instead of one forecasting value). But i do not know how to create a range of possible nth values as an input of ANN in order to find forecasted smf ranges. Would you please help me about matlab codes? Below i use the script that is modified by your genpredictor script. I hope that I could describe the problem properly and I would be glad to discuss about it with you. Thank you for your contribution and look forward to hear from you.
Best wishes,
Erdem
function [X, dates, labels] = genPredictorssmf4(data, term)
prevDaySameHourLoad = [NaN(24,1); data.SYSLoad(1:end24)];
prevWeekSameHourLoad = [NaN(168,1); data.SYSLoad(1:end168)];
prev24HrAveLoad = filter(ones(1,24)/24, 1, data.SYSLoad);
prevDaySameHoursgof = [NaN(24,1); data.SGOF(1:end24)];
prevWeekSameHoursgof = [NaN(168,1); data.SGOF(1:end168)];
prev24HrAvesgof = filter(ones(1,24)/24, 1, data.SGOF);
prevDaySameHoursmf = [NaN(24,1); data.SMF(1:end24)];
prevWeekSameHoursmf = [NaN(168,1); data.SMF(1:end168)];
prev24HrAvesmf = filter(ones(1,24)/24, 1, data.SMF);
prevDaySameHournth = [NaN(24,1); data.NTH(1:end24)];
prevWeekSameHournth = [NaN(168,1); data.NTH(1:end168)];
X = [data.Hour dayOfWeek isWorkingDay data.SYSLoad prevWeekSameHourLoad prevDaySameHourLoad prev24HrAveLoad data.SGOF prevWeekSameHoursgof prevDaySameHoursgof prev24HrAvesgof prevWeekSameHoursmf prevDaySameHoursmf prev24HrAvesmf data.NTH prevWeekSameHournth prevDaySameHournth];
labels = {'Hour', 'Weekday', 'IsWorkingDay', 'CurrentLoad', 'PrevWeekSameHourLoad', 'prevDaySameHourLoad', 'prev24HrAveLoad', 'CurrentSGOF', 'PrevWeekSameHoursgof', 'prevDaySameHoursgof', 'prev24HrAvesgof', 'PrevWeekSameHoursmf', 'prevDaySameHoursmf', 'prev24HrAvesmf', 'CurrentNTH', 'PrevWeekSameHournth', 'prevDaySameHournth'};
end
Dear Ameya Deoras!
when i compiling the genpredictor.m file then its give me error in
genPredictors
Error using genPredictors (line 29)
Not enough input arguments.
which is dates = datenum(data.Date', 'yyyymmdd HH:MM:SS') + (data.Hour1)/24;
let me know how i can fix this problem.
i am wondering for this problem about half month.
i am waiting for reply1
qamar_raza786@yahoo.com
Dear Ameya Deoras!
i am very new in this area.pleas tell me in detail i want import the load data into Matlab using (i have own data which is provided by the grid to me.
i am waiting for your reply
Thanks alot
Izi, that error seems to suggest that you are calling the genPredictors function without any inputs. “data” is a required input for the function and needs to be specified. See loadScriptNN for an example of how to use this function.
Satya, is the Neural Network predicting 0 load in MATLAB or in the Excel spreadsheet? If it is fine in MATLAB you may need to investigate if the model is being loaded correctly in the Excel side.
Ameya,
I have the same problem like Ali in May 2011. Solution?
The fun (genPredictors.m) it showed the errors as shown below:
??? Input argument "data" is undefined.
Error in ==> genPredictors at 27
dates = datenum(data.Date, 'yyyymmdd HH:MM:SS') + (data.Hour1)/24;
Could you please kindly solve the problem?
Hi Ameya, When I try to use this forecaster, NeuralNet forecasts to Zero load all the day, However the other model shows the forecast load. I tried for several days all the time it is the same case where NN shows zero load. Is there anything that I can do to get NN work?
Hello.
How can i do it with a NAR Network ?
I have a temporal serie with 99 values, and I want to predict the 100 value. And finally plot this 2 series y the same figure.
Somebody can help me, I prefer with the script.
Thk u
Suposing that is necessary generate multiple demands time series forecast with the demand model made with the Neural Network Tool, this would be possible??
Thinking specifically of the demand model presented, this would be possible with a single predictor scenario (temperature for exaple).
If it were possible to generate multiple paths to the model hourly demand made, which would be the commands to use?
Thank you for this wonderful work,
I've increased the factors like RELATIVE HUMIDITY ,WIND SPEED, but it showed the errors as shown below:
Error using ==> network.sim at 178
Inputs are incorrectly sized for network.
Matrix must have 8 rows.
Error in ==> LoadScriptNN at 94
forecastLoad = sim(net, testX')';
Could you guide me how to treat it?
Thank you very much!
This case study has been really helpful, thanks. I am having a problem with changing my network to a timeseries forecast tool in which I can feed the current load back through the network to forecast the next day, or possibly the next few hours. It fits the load very well, but due to the complexity in the input preparation I can't figure out how to use it with the sim function (in my regular network I could just use what you did, i.e. sim(net,inputs'), but this won't work with the timeseries setup)to actually predict new data coming in. My inputs are similar to your case study. Do you have any recommendations for preparing new inputs for a predicting function in this setup? I have played around with the network code to try and mimic what it does to the inputs, but no luck.
Jack, there are two places where prediction is shown. In loadForecastNN, look for the line "forecastLoad = sim(net, testX')';". Please also take a look at my comment from 20 May 2011 for an example on using the function forecastLoad to create a prediction.
There are 3 ways of doing multistep prediction:
1. You can build a NARX network. There are examples in the documentation that show how to do multistep with such a network.
2. You can build a feedforward network designed for predicting N steps ahead. That is what I do in this example  build a network for 24 stepahead prediction. This is done by lagging the inputs 24 observation. The function createLags above will do this for you.
3. Run the prediction in a loop. The function multiPredict above does this for a 1step network. In the context of this example, you can use the Nstep model to do 2N, 3N, 4N... step prediction.
While I don't think the lack of multistep prediction warrants a 1star rating, you are of course entitled to rate it based on whatever criteria make sense to you. This is not intended to be a tutorial on Neural Networks Toolbox so I can't possibly include everything there is to know about using it. I encourage you to consult the documentation or contact technical support for help with your specific needs.
Here is a function that can be used to run multistep prediction from a 1step feedforward network:
function pred = multiPredict(net, X, numSteps)
% multiPredict performs iterated prediction with a feedforward neural
% network.
%
% SYNTAX: pred = multiPredict(net, X, numSteps)
%
% INPUTS:
% net is a feedforward neural net
% X is a matrix of size numObservations * numPredictors
% numSteps is the number of steps to predict (eg. 10)
%
% OUTPUTS:
% pred is a matrix of size numObservations * numSteps where every column is
% the ith step prediction for that sample observations. The first column is
% the 1step prediction, the second columns is the 2step prediction and so
% on.
numObs = size(X,1);
pred = zeros(numObs, numSteps);
pred(:, 1) = net(X')';
for i = 2:numSteps
X = [pred(:,i1) X(:,1:end1)];
pred(:,i) = net(X')';
end
Here is a function that can be used to create an arbitrary predictor matrix with any number of lags:
function mat = createLags(vec, lags)
% CREATELAGS generates lagged versions of an input vector or matrix to
% generate a predictor matrix.
%
% USAGE:
% predictorMatrix = createLags(series, lags)
%
% Here series is a numObsbynumDim matrix of observations. If numDim > 1,
% it implies the input series is a multidimensional series. lags is a
% vector of integer lags where 0 corresponds to no lag, +1,+2,+3... correspond to
% lags of 1,2,3... steps, and 1,2,3 correspond to "leads" of 1,2,3
% steps. predictorMatrix is a numObsbynumDim*numLags matrix of the
% shifted versions of the input matrix
% x = [1 2 3 4; 1 2 3 4]'
% y = createLags(x, [1 0 2])
[numObs, numDim] = size(vec);
numLags = length(lags);
mat = NaN(numObs, numDim * numLags);
for i = 1:length(lags)
mStaInd = max(1, lags(i)+1);
mEndInd = min(numObs, lags(i)+numObs);
vStaInd = max(1, 1lags(i));
vEndInd = min(numObs, numObslags(i));
mat(mStaInd:mEndInd, (i1)*numDim+1:i*numDim) = vec(vStaInd:vEndInd,:);
end
The problem with this example it is that Ameya doesn't show how to make a multi step prediction.
This should have been it the example because the title is FORECASTING.
I see a lot or questions everywhere on the web about multi step ahead prediction.
Everyone know how to load datas. I means it's almost like opening an Excel file. But to make a prediction is very difficult.
I've a NARX neural network with 10 hidden neurons and 2 delays. As input I have a 510x5 (called Inputx) and as output I have a 510x1 (called Target).
I want to forecast 10 days ahead but it's really not working...
I tried the following code but I'm stuck now. :(
Would you mind to help me ? Some code will be awesome. :(
***////////////////////////////////////////////******** ***/////////////////////////////////////////// ******
inputSeries = tonndata(Inputx,false,false);
targetSeries = tonndata(Target,false,false);
netc = closeloop(net);
netc.name = [net.name '  Closed Loop'];
[xc,xic,aic,tc] = preparets(netc,inputSeries,{},targetSeries);
yc = netc(xc,xic,aic);
***////////////////////////////////////////////******** ***/////////////////////////////////////////// ******
How do we make a prediction with the Matlab generated script above ?
The example should have shown that ... really !!!
Dear Ameya,
I have problem with command:
data = fetchDBLoadData('20040101','20081231')
This is the dislay after entering the command:

??? Error using ==> chkprops at 18
Invalid com.mathworks.toolbox.database.PrefsDBPanel property: ' DefaultRowPreFetch '.
Error in ==> setdbprefs at 91
p = chkprops(DatabasePrefs,p,prps);
Error in ==> setdbprefs at 88
setdbprefs(flds,vals)
Error in ==> fetchDBLoadData at 14
setdbprefs(s)

That's all. Could you guide me how to treat it?
Thank you very much!
Ameya,
When I tried to run the fun (genPredictors.m) it showed the errors as shown below:
??? Input argument "data" is undefined.
Error in ==> genPredictors at 27
dates = datenum(data.Date, 'yyyymmdd HH:MM:SS') + (data.Hour1)/24;
Could you please kindly solve the problem?
Hi. A simple example call to loadForecast has been provided in a previous post. If you need something more, could you please describe it in more detail?
Here is the example again:
% Temperature forecast
temp = [38 36 36 36 35 34 35 35 36 38 40 41 42 43 44 44 44 43 42 41 40 40 40 40;31 30 30 30 30 29 30 31 32 32 32 32 32 32 32 32 34 35 36 37 38 38 38 38]';
% Load forecast for that temperature forecast for April 2, 2008
y = loadForecast('April 2, 2008', temp, 'No');
Dear ameya
i'm trying to run the price forecast program,but i receive errors,would you please send me an example of this program.
please be concider simple example without excel file
dear ameya
would you please send me the example of this program .includ "temp,holiday,price"
The second input to loadForecast is the temperature forecast for the day for which you want to predict the load. The second requirement is that the day you choose must have some historical data in the database for the week prior. You will therefore also need the database installed. You can contact me to get access to the access database used for this example. Once the database is set up, you can call loadForecast as follows:
y = loadForecast('April 2, 2008', temp, 'No');
where temp is a 24by2 array of hourly temperature and dew point forecasts for the day in question.
temp = [38 36 36 36 35 34 35 35 36 38 40 41 42 43 44 44 44 43 42 41 40 40 40 40;31 30 30 30 30 29 30 31 32 32 32 32 32 32 32 32 34 35 36 37 38 38 38 38]';
Hi; I want to run this load forecast without using Excel front page. Can you please identify what is the process? In "LoadForecast.m" file at line 46 I am receiving error showing that "temperature" is not defined. How should I define this temperature?
For long term forecasting, you may need to take into account additional predictors such as the economic growth in an area and new industrial or residential developments. The existing model could be modified to remove the lagged load dependence. This would give you a model that would generate a forecast based only on temperature, date/time and holiday information. You could then use it either in a MonteCarlo fashion or for different scenarios of future temperatures (average, 1 std dev, 2 std dev etc) to create a profile or distribution of load forecasts. Check out my other submission "Energy Trading & Risk Management with MATLAB" for an example of a temperature simulation model.
The temperature data in provided is historical. If you were to use to model to make a forecast, you would use forecast temperature values. In my example, I pretend that today is April 2, 2009 and use actual temperatures for the next day as my assumed temperature forecast. So, only actual temperatures and not forecasts are being used to create the load forecast.
For the purposes of the 'long' term forecasting, is the period any different than the short term's period? Are we really only changing the factors used to build the model in order to forecast the future load?
In addition, is the temperature data that was provided in the test set a forecast or the historical data? I see that the slides/pdf show that we would be using forecasts, but I wasn't sure if that was the case on the provided data.
Thank you,
Jesse
Thanks for the feedback. You can certainly use timedelay networks for such an application. In this example, I manually create timelagged versions of the response (load) and use them as variables in the predictor matrix. I use the 168hour lagged load, the 24hour lagged load and a smoothed or averaged 24hour lagged load.
Ameya, your data also has time series property. So is it possible to have a model that is using timedelay dynamic networks? Also may be narx network, with multiple inputs and past y data. If possible and you update your webinar with new models, it will be great. Thx.
Ameya,
I wish to supplement one more point regarding the problem mentioned above: I could successfully run the loadForecast.m in Matlab and generate the forecast.
So, I wonder if there was something wrong with my setups in the operating system or in the Visual Studio environment at the compiletime and runtime, e.g., the path or whatsoever possible.
I look forward to your hints and helps. Thanks.
I wish to get some helps from you to test the running the function in the spreadsheet.
I have compiled your Forecaster.prj and imported the corresponding .bas files into the Forecaster.xlsm. But when I tried it by clicking the "Compute Forecast" button, it showed the runtime errors in the forecast cells, as shown below:
Error in Forecaster.Class1.1_0: Undefined function or method 'sim' for input arguments of type 'struct'.
Error in => loadForecast.m at line 56
The folder where the sim.m situated was already in my Matlab path when I checked through the Set Path command.
I also noticed that you had indicated in the loadForecast.m the paths for looking up the NN and tree models as well as the data file.
Could you please kindly provide some hints to pin point and solve the problem?
Thanks for your question. The methodology in this example isn't taken from any one source. There are a couple of papers I read which gave me some ideas. Please also check the references within.
* Eugene Feinberg & Dora Genethliou, Applied Mathematics for Power Systems, Chapter 12 Load Forecasting
* K. Liu et al, "Comparison of Very ShortTerm Load Forecasting Techniques", IEEE Transactions on Power Systems Vol 11 No 2, May 1996
* Rafal Weron, "Modeling and Forecasting Electricity Loads and Prices" Wiley
Would you be able to provide some of the sources/authors that contribute to the background to the code?
Thank you for your help
I have updated the submission to include the relevant data in MATfiles so you shouldn't need the Access database anymore. The Intro document has also been updated to reflect this.
Could you kindly advise me how can I get energy.accdb file?
Thanks for your cooperation.
Hi, don't get energy.accdb file