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Page 1: Gis Boosts t&d Planning for Asset Management _ Distribution Management Systems Content From Tdworld

21. 01. 14 GIS BOOSTS T&D PLANNING FOR ASSET MANAGEMENT | Distribution Management Systems content from TDWorld

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Oct. 1, 2005

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GIS BOOSTS T&D PLANNING FOR ASSETMANAGEMENTJessica C. Noonan and Amy L. Johnson, PacifiCorp | T&D World Magazine

THE ASSET MANAGEMENT INFRASTRUCTURE

PLANNING ORGANIZATION OF PACIFICORP has

adopted geographic information systems (GIS)-based

spatial-load forecasting for high-growth areas of its service

territory. This method is giving PacifiCorp's long-term

planning efforts a new perspective.

Spatial-load forecasting moves network planning engineers

beyond spreadsheet-based trend analysis into the spatial

analysis capabilities of GIS. It gives geographic answers to the questions: Where will

demand grow, and where is this new growth relative to substation service areas? The

planning department can identify changing end-use patterns, predict future load centers,

identify substation property requirements, and ensure the most defendable and cost-

effective capital expenditures for substation reinforcement. This new approach has the

potential to improve our relationships with the communities we serve, developing a more

cooperative approach with our customers and improving service delivery. Long-term

forecasting will extend the planning horizon beyond five years, increasing the lead time

given to the permitting and land acquisition departments.

WHAT IS SPATIAL-LOAD FORECASTING?

Spatial-load forecasting uses GIS to merge distribution system data with land-use and

development data. The model uses data such as current land use, transportation

infrastructure, mountain slopes and urban centers to forecast the extent, location and

timeline of community development. Every land use is related to a predefined profile of

load on the distribution system. The model then translates the land use into a system-load

forecast, identifying where new load additions are to be expected. This analysis of the

community's projected growth helps target where infrastructure investments should be

directed.

WHY SPATIAL-LOAD FORECASTING?

Spatial-load forecasting allows PacifiCorp's planning engineers to predict large load

additions to the system years in advance of other methods. Planning engineers typically

use trend analysis to forecast future loads, but they are now able to use the power of GIS

to visualize new load and system additions. It will help them determine where new

infrastructure should be added and inform others who need to know. This approach will

help the company's Property Management Department better acquire real estate, apply

for permits and acquire needed rights-of-way.

Spatial-load forecasting produces a forecast of electric load growth inside a region of the

service territory, suitable as a base for comprehensive transmission and distribution

expansion planning. Forecast results are used to predict future load centers, identify

substation property requirements, prioritize projects and obtain budgeting approval while

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minimizing risk. Spatial-load forecasting also helps to explore the impacts of new

initiatives or localized development events, as well as demonstrates effects to the system

due to end-use changes, conversion from winter-to-summer peaking and community

redevelopment.

Spatial-load forecasting does have limitations. It is not a design package and does not

replace the knowledge and experience of T&D planning engineers. It is primarily used to

complement traditional approaches to system planning to challenge planning

assumptions. Spatial-load forecasting can support the transmission system planning

process but does not predict the routing of transmission lines. Spatial load can forecast

expected load demand in a way that creates productive interaction with the communities

being served.

APPLICATION AT THE WASATCH FRONT

A greater appreciation of the value of spatial-load forecasting is evident through

PacifiCorp's experience in modeling its Wasatch Front Range. The forecasted area in

Utah comprises approximately 2000 sq miles (5180 sq km) with boundaries that include

56 cities currently served by 133 distribution substations. The area's population has grown

at a rate of 2.6% per year for the last 15 years, which has driven electric load growth. This

growth has been further inflated by conversion from evaporative cooling (EV) systems

(i.e. swamp coolers) to central air conditioning (AC) systems. PacifiCorp's spatial-load

forecast predicted the locations of large load additions due to rapid development, as well

as where AC conversion will likely occur.

The spatial-load forecast consists of six main steps to the model setup. The following

briefly discusses these steps and the hurdles the GIS and engineering team encountered

while working on the project:

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1. Determining the load classes

The initial step is to determine the load classes to be represented. The foundation of the

spatial-load forecast is a representation of the study region according to current land

use; however, to represent the regional load, land use is actually defined by its

consumer load class. A load class distinguishes customers based on energy

consumption, defined in kilowatts per acre and a unitized daily load curve. For

example, a typical land-use classification might be “medium-density residential,” and

the representative load class or customer class would be “medium-density residential

with EV” or “medium-density residential with AC.”

This classification system allows representation of land uses according to their typical

load profile and also allows changing end-use analysis. Load classes were selected

through analysis of substation SCADA data. The eight load-bearing classes used were:

Several additional nonload-bearing classes also were used to identify vacant available

lands, federal nondevelopable lands and municipal service areas not served by

PacifiCorp distribution.

Medium-density residential with AC

Medium-density residential with EV

Low-density residential

High-density residential

Commercial retail

Commercial office and institutional

Light industrial (major industrials were excluded from the model)

Commercial business district.

2. Data resources and the land-use model

The land-use model represents current land use and development in the Wasatch

Front. Key to the land-use model is reproducing the current land use in the area, as

well as indicating the current development environment. In many cases, this is done

using zoning regulations that restrict or encourage particular load classes — or that

restrict or encourage land-use-type development in certain regions. It is also

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important to model the land that is currently (or soon will be available) for

development. For example, it is possible that land currently considered nonvacant as

part of a large multi-acre parcel may be divided later into multiple vacant residential

parcels.

Initially, each of the individual cities were contacted to obtain current land-use

information. Unfortunately, many of the communities included in the study area did

not maintain accurate enough information to be useful in the land-use model. As part

of PacifiCorp's Real Estate Management GIS environment, parcel and ownership data

is collected from each of the counties served. Assessor data was also requested from

the counties. This allowed each individual parcel to be classified into a load class

according to its assessed land use. When assessor data was insufficient, current aerial

photographs were used.

Gathering information from city and county planners was critical in identifying

known developments and coordinating with master plans. Spending time with local

planners provided insight not otherwise available.

Cooling system conversions

The primary concern in the current Wasatch Front development environment is the

conversion of older homes from EV systems to centralized AC. This conversion is

generating a significant increase of the system electrical load. Therefore, it was

important to model this conversion in addition to new development.

Many assessors maintain a residential housing characteristic regarding AC. However,

the information is only collected when a home is reassessed. Additional data was used

in cases where an AC characteristic was not available, including square footage, year

built and total value. Homes built after 1995 with a square footage greater than 2000

or a total value greater than $150,000 were assumed to have central AC. These homes

were placed in the medium-density residential AC class. All other residential parcels

were placed in the medium-density residential evaporative cooling class.

It was important to simulate the end-use conversion in the residential class to show

the gradual increase in load growth, which is occurring independent of land

development.

Additional development parameters

Much of the low-density residential and rural lands of the Wasatch Front will become

available for higher-density residential and commercial development in the future. It

was important to model the predicted conversion of these lands by incorporating them

into a redevelopment model as well. Those areas classified as low-density

residential/rural were coded to allow for redevelopment into any of the load classes.

Future land-use drivers

An activity center map, locating regions of employment or commercial activity was

used as a factor in the model to encourage residential and commercial growth in

locations that planners labeled as high-growth regions.

At this stage of the model it became evident that multiple growth scenarios would be

helpful. Running the forecast to show results of development scenarios allowed

investigation of the investment needs that may be required if a proposed event occurs.

Using these growth scenarios, the company was able to investigate the impacts due to

major development activities and proposed transportation corridors, both of which

substantially affect load distribution in the study area.

3. Load curve development

The load profiles or load curves represent the average daily patterns and usage of

energy as a function of time for a particular load class. This is used to build a load

model from the represented land use. Planners must accommodate peak load

conditions; consequently, planners need to know how loads behave during the system

peak. The first step in developing the load curves was determining the system peak

day. Next, hourly data was extracted from the company's system control and data

acquisition (SCADA) system for selected distribution feeders that were representative

of each load class. The final curves were presented to the company's metering group

for verification.

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The factors and development influences are mathematically combined to develop

suitability maps for each of the load classes. The suitability maps are used to match load

classes to their most suitable growth areas. For each forecasted year's growth, the model

uses the highest ranked locations on the suitability maps to assign new growth to that

particular area. The end result for each year of the forecast was a new land-use map

showing the predicted growth in the region.

INTERPRETING THE RESULTS

After the model had been run for each of the forecast years, the new total land-use

calculations were broken down by substation boundary to determine the new growth

within each substation's service area. Acreage totals for each substation were then

converted to megawatt additions. To better understand the systemwide results, the

substations were grouped into significant zones according to the planning organization's

load flow base cases. The purpose of a spatial-load forecast is to forecast regional load.

However, that forecast is of little value without a measure of the impact the projected

load will have on the planned and existing infrastructure. Due to the enormous

complexity of the entire Wasatch Front electrical system, new infrastructure

requirements were evaluated on a purely quantitative level for the distribution

transformer level only. Results were analyzed to quantify needed additional capacity by

zone according to projected load additions. The results predicted capacity requirements in

30-MVA blocks, corresponding to transformer banks in substations. The results were

weather adjusted to look at extreme weather demands. Each zone was analyzed to a

standard utilization threshold, and infrastructure enhancement needs were forecasted for

each study year.

DELIVERING THE BENEFITS

Last-minute property acquisitions for new facilities can be fraught with conflict, resulting

in delays in the siting process. In high-growth regions, acquisition costs are lower when a

parcel is secured earlier. If the planning group can anticipate future load centers and

equipment utilization issues years in advance, property can be purchased earlier, at a

lower price and in a manner that can be incorporated into the local government's master

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4. Calibration

Calibration is the process of matching the model's calculated load for the base year to

the actual load on the system and substations. The goal is to achieve the best possible

match for the entire system and individual substations, both in magnitude and shape.

Matching the magnitude is only a first-order test, but matching the shape ensures the

correct type of load has been assigned to each area.

The actual 24-hour-per-unit load curves for each selected substation were obtained

from SCADA for the 2003 system peak day. The calculated 24-hour load curves

require three inputs: land-use acreage by load class, per-unit load curves for each load

class and load multipliers (kilowatts per acre by load class). The only adjustable

parameter input to the calibration process was the load multiplier. This value was

adjusted within maximum and minimum set bounds until an indication of success

was met. Success was measured by the total load difference at the time of peak, time

of system peak, average percent difference for substation peaks and time of substation

peaks.

5. Growth rates

There are two circumstances that cause load growth: new customers and the

consumption growth of existing customers. In the former case, new customers are

responsible for the steep section of an area's “S” curve. In the latter case, consumption

growth drives the flatter sections of the “S” curve. Both types of growth had to be

incorporated in the model to accurately simulate load growth and changing patterns.

6. Factors, urban poles and preferences

Any spatial-load forecast uses a model to simulate the effects of real-world factors to

systematically determine the extent and timeline of community development.

Forecasts use the theories of urban planning to predict the most likely locations of new

land development. To achieve this, the model's growth simulation was based on user-

determined factors that tend to influence a region's growth. Factors include

transportation infrastructure, locations of employment and commercial centers,

barriers to development and general land-use attractors or detractors.

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planning process.

The principal benefit of PacifiCorp's spatial-forecasting approach is improved

communication. More insightful communication occurs between T&D planning

engineers, utility real estate agents and city planners. Spatial-load forecasting creates

more flexibility within the distribution system planning process. It helps identify future

load centers and changing end-use patterns.

Identifying substation property requirements earlier ensures the most defensible and cost-

effective capital expenditures for substation reinforcement. GIS is revolutionizing the

ways in which PacifiCorp can visualize and track the changing load patterns throughout

its service territory, and provides a basis for comprehensive transmission and distribution

planning.

Jessica C. Noonan is a GIS specialist at PacifiCorp, where she has prepared spatial-load

forecasts for the Wasatch Front, Central Oregon and Medford, Oregon, areas. Noonan

holds a master's degree in geographic information sciences from the University of Denver

and a bachelor's degree in environmental geoscience from Boston College.

[email protected]

Amy L. Johnson joined PacifiCorp as a planning engineer in 2002, after graduating

with a BS degree in electrical engineering from the University of Washington. She

provided the engineering data and analysis for the Wasatch Front spatial-load forecast.

[email protected]

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