load forecasting techniques.pdf

AJAY BHATNAGAR, NRLDC

Load Forecasting Techniques &

Scheduling

POSOCO - NRLDC

lOAD FORECASTING IS USED by POwER COMPANIES TO

ANTICIPATE THE AMOUNT OF POwER NEEDED TO SUPPly THE

DEMAND.

JURISDICTION OF LOAD DESPATCH CENTERS

NLDC:Apex body to ensure integrated operation of National Power System

RLDC:Apex body to ensure integrated operation of power system in the concerned region

SLDC:Apex body to ensure integrated operation of power system in a state

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PECULIARITIES OF REGIONAL GRIDS

SOUTHERN REGION

WESTERNREGION

EASTERN REGION

NORTHERN REGION NORTH-

EASTERN REGION

REGIONAL GRIDS

Deficit Region

Snow fed – run-of –the –river hydro

Highly weather sensitive load

Adverse weather conditions: Fog & Dust Storm

Very low load

High hydro potential

Evacuation problems

Industrial load and agricultural load

Low load

High coal reserves

Pit head base load plants

High load (40% agricultural load)

Monsoon dependent hydro

CHICKEN-NECK

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lOAD FORECASTING

What is Load forecasting

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Load forecasting is sort of planning & It issaid that “To work with plan is to work withaccuracy”.

Load forecasting is used by powercompanies to anticipate the amount ofpower needed to supply the demand.

LOAD FORECASTING

• The first crucial step for any planning study

• Forecasting refers to the prediction of the load behaviour for the future

• Words such as, demand and consumption are also used instead of electric load

• Energy (MWh, kWh) and power (MW,kW) are the two basic parameters of a load.

• By load, we mean the power.

• Demand forecast

• To determine capacity of generation, transmission and distribution required

• Energy forecast

• To determine the type of generation facilities required

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NATURE OF LOADS

Load characteristics:• Demand factor

• Load factor

• Diversity factor

• Utilization factor

• Power factor

• Higher the values of load factor and diversity factor, lower will be the overall cost per unit generated.

• Higher the diversity factor of the loads, the fixed charges due to capital investment will be reduced.

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demandMaxfactorDemand

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demandMax

demandAvgfactorLoad

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stationpowerofdemandMax

demandsindividualofSumfactorDiversity

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stationpowerofcapacityRated

stationpowerondemandMaxfactornUtilisatio

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TYPES OF LOADS

Five broad categories:• Domestic

• Demand factor: 70-100%

• Diversity factor: 1.2-1.3

• Load factor: 10-15%

• Commercial


• Diversity factor: 1.1-1.2


• Industrial

• Small-scale: 0-20 kW

• Medium-scale: 20-100 kW

• Large-scale: 100 kW and above



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TYPES OF LOADS

• Agricultural


• Diversity factor: 1-1.5


• Other loads

• Street lights, bulk supplies, traction etc.

Commercial and agricultural loads are characterized by seasonal variations.

Industrial loads are base loads and are little weather dependent.

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DEMAND ESTIMATION AS PER

IEGC PROVISIONS

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DEMAND ESTIMATION

Demand estimation for operational purposes is to be done on adaily/weekly/monthly basis. The mechanism and facilities at SLDCs shallbe created to facilitate on-line estimation of demand for daily operationaluse for each 15 minutes block.

The monthly estimated demand by the SLDC shall be provided to RLDCand RPC

The SLDC shall take into account the Wind Energy forecasting to meetthe active and reactive power requirement.

In order to facilitate estimation of Total Transfer Capability / AvailableTransfer Capability on three month ahead basis , the SLDC shall furnishestimated demand and availability data to RLDCs.

DEMAND-SIDE MANAGEMENT

Grouping of Loads by SLDC without overlapping between different Groupsas given below

Loads for scheduled power cuts/load shedding

Loads for unscheduled load shedding

Loads to be shed through under frequency relays/df/dt relays

Loads to be shed under any System Protection Scheme identified at theRPC level.

TECHNIQUES OF

lOAD FORECASTING

FACTORS AFFECTING LOAD FORECASTING

• Time factors such as:

• Hours of the day (day/night)

• Day of the week (week day/weekend)

• Time of the year (season)

• Weather conditions (temperature and humidity)

• Class of customers (residential, commercial, industrial, agricultural, public, etc.)

• Special events (TV programmes, public holidays, etc.)

• Population

• Economic indicators (per capita income, Gross National Product (GNP), Gross Domestic Product (GDP), etc.)

• Trends in using new technologies

• Electricity price

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FORECASTING METHODOLOGY

• Forecasting: systematic procedure for quantitatively defining future loads.

• Classification depending on the time period:

• Short term

• Intermediate

• Long term

• Forecast will imply an intermediate-range forecast

• Planning for the addition of new generation, transmission and distribution facilities must begin 4-10 years in advance of the actual in-service date.

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FORECASTING TECHNIQUES

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Three broad categories based on:

• Extrapolation

– Time series method

– Use historical data as the basis of estimating future outcomes.

• Correlation

– Econometric forecasting method

– identify the underlying factors that might influence the variable that is being forecast.

• Combination of both

EXTRAPOLATION

• Based on curve fitting to previous data available.

• With the trend curve obtained from curve fitted load can be forecasted at any future point.

• Simple method and reliable in some cases.

• Deterministic extrapolation:

• Errors in data available and errors in curve fitting are not accounted.

• Probabilistic extrapolation

• Accuracy of the forecast available is tested using statistical measures such as mean and variance.

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CORRELATION

• Relates system loads to various demographic and economic factors.

• Knowledge about the interrelationship between nature of load growth and other measurable factors.

• Forecasting demographic and economic factors is a difficult task.

• No forecasting method is effective in all situations.

• Designer must have good judgment and experience to make a forecasting method effective.

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IMPACT OF WEATHER IN LOAD FORECASTING

• Weather causes variations in domestic load, public lighting, commercial loads etc.

• Main weather variables that affect the power consumption are:

• Temperature

• Cloud cover

• Visibility

• precipitation

• First two factors affect the heating/cooling loads

• Others affect lighting loads

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• Average temperature is the most significant weather dependent factor that influences load variations.

• Temperature and load are not linearly related.

• Non-linearity is further complicated by the influence of• Humidity

• Extended periods of extreme heat or cold spells

• In load forecast models proper temperature ranges and representative average temperatures which cover all regions of the area served by the electric utility should be selected.

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• Cloud cover is measured in terms of:

• height of cloud cover

• Thickness

• Cloud amount

• Time of occurrence and duration before crossing over a population area.

• Visibility measurements are made in terms of meters/kilometers with fog indication.

• To determine impact of weather variables on load demand, it is essential to analyze data concerning different weather variables through the cross-section of area served by utility and calculate weighted averagesfor incorporation in the modeling.

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ENERGY FORECASTING

• To arrive at a total energy forecast, the forecasts for residential, commercial and industrial customers are forecasted separately and then combined.

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RESIDENTIAL SALES FORECAST

• Population method

• Residential energy requirements are dependent on:

• Residential customers

• Population per customer

• Per capita energy consumption

• To forecast these factors:

• Simple curve fitting

• Regression analysis

• Multiplying the three factors gives the forecast of residential sales.

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RESIDENTIAL SALES FORECAST

• Synthetic method

• Detailed look at each customer

• Major factors are:

• Saturation level of major appliances

• Average energy consumption per appliance

• Residential customers

• Forecast these factors using extrapolation.

• Multiplying the three factors gives the forecast of residential sales.

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COMMERCIAL SALES FORECAST

• Commercial establishments are service oriented.

• Growth patterns are related closely to growth patterns in residential sales.

• Method 1:

• Extrapolate historical commercial sales which is frequently available.

• Method 2:

• Extrapolate the ratio of commercial to residential sales into the future.

• Multiply this forecast by residential sales forecast.

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INDUSTRIAL SALES FORECAST

• Industrial sales are very closely tied to the overall economy.

• Economy is unpredictable over selected periods

• Method 1:

• Multiply forecasted production levels by forecasted energy consumption per unit of production.

• Method 2:

• Multiply forecasted number of industrial workers by forecasted energy consumption per worker.

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PEAK LOAD FORECASTING

• Extrapolate historical demand data

• Weather conditions can be included

• Basic approach for weekly peak demand forecast is:

1. Determine seasonal weather load model.

2. Separate historical weather-sensitive and non-weather sensitive components of weekly peak demand using weather load model.

3. Forecast mean and variance of non-weather-sensitive component of demand.

4. Extrapolate weather load model and forecast mean and variance of weather sensitive component.

5. Determine mean, variance and density function of total weekly forecast.

6. Calculate density function of monthly/annual forecast.

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WEATHER LOAD MODEL

• Plot a scatter diagram of daily peaks versus an appropriate weather variables.

• Dry-bulb temperature and humidity

• Using curve fitting three line segments can be defined in the example

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sw

www

sss

TTTif0

TTifTTk

TTifTTkw

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Parameters of the model:• Slopes: ks and kw• Threshold temperatures: Ts and Tw

SEPARATING WEATHER-SENSITIVE AND NON-WEATHER SENSITIVE COMPONENTS

• From the weather load model

• Weather-sensitive (WS) component of weekly peak load demand data is calculated from the weekly peak coincident dry-bulb temperatures.

• Non-weather-sensitive (NWS) component of peak demand is obtained by subtracting the first component from historical data.

• NWS component is used in step-3, of basic approach for weekly peak demand forecast , to forecast the mean and variance of the NWS component of future weekly peak demands.

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TOTAL FORECAST

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LOAD FORECASTING CATEGORIES

Load Forecasting Categories

Short-term load forecasting

One hour ~ One week

Control and schedule power system in everydayoperations

Medium-term and Long-term load forecasting

One week ~ longer than one year

Determine capacity of generation, transmission,distribution systems, type of facilities required intransmission expansion planning, development ofpower system infrastructure, etc.

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LOAD FORECASTING METHODS

Parametric methods

Regression method

Time series

Similar day Approach

Autoregressive Moving Average (ARMA)

Spectral expansion technique (Fourier Series)

State equations

Artificial intelligence methods

Artificial neural networks

Fuzzy logic

Expert systems

POSOCO - NRLDC

INFLUENCE – WEATHER, TIME & TYPE

Electric load has an obvious correlation to weather. The mostimportant variables responsible in load changes are:

Dry and wet bulb temperature Dew point Humidity Wind Speed / Wind Direction Sky Cover Sunshine

In the forecasting model, we should also consider time factorssuch as:

The day of the week

The hour of the day

Holidays

Electric utilities usually serve different types of customers such asresidential, commercial, and industrial. The following graphsshow the load behavior in the above classes by showing theamount of peak load per customer, and the total energy.

POSOCO - NRLDC

SCHEDUlING AS PER

IEGC PROVISIONS

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SCHEDULING RESPONSIBILITY

RLDC has Scheduling Responsibility for

a) Central Generating Stations (excluding stations where full Share isallocated to host state),

b) Ultra-Mega power projects

c) If a generating station is connected only to the ISTS, (except forCentral Generating Stations where full Share is allocated to one State)

d) If a generating station is connected to both ISTS and the Statenetwork and if the state has 50% Share of power or less ( of thegenerating capacity put into commercial operation)

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SCHEDULING RESPONSIBILITY

SLDC has Scheduling Responsibility for

a) Generating station which is connected only to the State transmission network

b) Central Generating Station whose full Share is allocated to host state.

c) If a generating station is connected both to ISTS and the State network and if the state has more than 50% Share of power (of the generating capacity put into commercial operation)

d) Generating station supplying power to any state other than host state

POSOCO - NRLDC

SCHEDULING RESPONSIBILITYNLDC shall be responsible for

scheduling and despatch of electricity over inter-regional links inaccordance with the grid code specified by Central Commission incoordination with Regional Load Despatch Centers.

NLDC shall be responsible for coordination with Regional LoadDespatch Centers for the energy accounting of inter-regional exchangeof power.

NLDC shall also be responsible for coordination for trans-nationalexchange of power.

NLDC shall develop a procedure for scheduling of collective transactionthrough Power Exchanges, scheduling of inter-regional power exchangesincluding HVDC setting responsibility and power exchanges of thecountry with other countries.

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SCHEDULING PROCEDURE

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TIME LINE OF SCHEDULE

By 09.00 hrs. ISGSs shall advise NRLDC the Station-wise MW and MWhcapabilities

By 10.00 Hrs. NRLDC shall advise the States / Beneficiaries the Station wise MW& MWh entitlements.

By 1500 hrs. SLDCs/ Beneficiaries shall communicate the Station-wiserequisitions and details of bilateral exchanges to NRLDC.

By 1800 hrs. NRLDC shall convey the ex-power plant despatch schedule to eachISGS and net drawal schedule to each State / Beneficiary. Thedetails of unrequisitioned surpluses shall also be intimated.

By 2200 hrs.* ISGSs / States / Beneficiaries shall inform the modifications, if any,for incorporating in the final schedule

By 2300 hrs. NRLDC shall issue the final despatch and drawal schedule.

* Since issuing the final despatch and drawal schedule is a critical activity andconsiderable time is involved in its preparation and carrying out requisitemoderation, if any, it has been agreed to complete this activity by 2100 hrs.

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COMPOSITE TIMELINE

AvailabilityDeclaration

Entitlements

SLDC

Requisition &Bilateral Agreements

Injection Schedule Drawal Schedule

Revision in DC Revision in Requisition

FinalInjection Schedule

FinalDrawal Schedule

09:00

10:00

15:00

18:00

22:00

23:00

RLDC

ISGS

Time

Revisions duringCurrent day

Revisions duringCurrent day

0 to 24 hours

CollectiveTransactions (PX)

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SPECIAL REQUIREMENT OF SOLAR / WIND

5.2

(u) Special requirements for Solar/ wind generators

System operator (SLDC/ RLDC) shall make all efforts to evacuate theavailable solar and wind power and treat as a must-run station. However,System operator may instruct the solar /wind generator to back downgeneration on consideration of grid security or safety of any equipment orpersonnel is endangered and Solar/ wind generator shall comply with thesame. For this, Data Acquisition System facility shall be provided fortransfer of information to concerned SLDC and RLDC

(i) SLDC/RLDC may direct a wind farm to curtail its VAr drawl/injection incase the security of grid or safety of any equipment or personnel isendangered.

(ii) During the wind generator start-up, the wind generator shall ensure thatthe reactive power drawl (inrush currents incase of induction generators)shall not affect the grid performance.

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DEVIATIONS FROM SCHEDULE - UI

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load forecasting techniques.pdf

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