POWERGEN Asia 2014

Track 1: Market trends, Investment planning

The Value of Dynamic Modelling in Power System Planning

Saara Kujala, Manager, Development & Financial Services

Power Plants, Wärtsilä Singapore Pte Ltd.

Matti Rautkivi, General Manager, Liaison Office Business Development, Power Plants, Wärtsilä Corporation,

Finland

Power system planning in single-buyer markets of Asia traditionally assesses the need for new

generating capacity with relatively static models using expected load duration curves as indica-

tors for quantity and type of capacity needed. This may create a bias towards investing in base

load capacity that eventually is not fully utilized or is too inflexible to respond to demand varia-

tions, thus unnecessarily increasing electricity cost. This paper introduces dynamic investment

plan assessment as an alternative tool for power investment planning in single-buyer markets of

Asia. This tool may offer a better justification for the choice of technology that minimizes the

cost of electricity to consumers.

The use of dynamic investment plan assessment originates from the USA where regulated utili-

ties must use this approach to justify investments in new power plant capacity. In the assessment,

the utility analyzes the feasibility of a new power plant on a system level, not only on a project

level. In other words, the utility analyses how the new plant will affect the operating profiles of

other plants in the power system, and if the new investment results in the lowest cost to con-

sumer.

Dynamic investment plan assessments have quickly become a well established industry practice

in the USA. Regulators and utilities have understood that dynamic modelling provides more ac-

curate information into the investment planning process, helping them to make better investment

decisions. However, it is not yet widely used in the single-buyer markets of Asia. This paper in-

troduces the dynamic investment plan assessment approach and discusses its benefits for the

Asian markets.

1 INTRODUCTION

Power system planning in a regulated environment can be described as an approach to define the

least cost combination of supply and end-user alternatives to meet the system load and reliability

standards while taking into account the political objectives and system limitations. The actual

planning process described in Error! Reference source not found. is quite universal regardless

of the power system or country.

Figure 1.The investment planning process in a regulated utility environment

In the first step of the planning process the objectives for the power system planning are set to-

gether with the state utility, regulator and politicians. The objectives are always system specific

and may highlight the different angle depending on the system and country situation. One power

system planner can consider reliable electric service as the most important objective, while some

other planner would emphasize cost minimization or decarbonisation. The planning objectives

Regulated utility together with interested parties set the system targets

• Energy policy objectives• Reliability standards• Fuel mix, fuel sources, renewable targets

Gather information on the demand pattern and build the demand forecast for the investment period

• Historical demand patterns• Expected load growth over the study period• Changes in load prof iles e.g. due to renewables

Analyze the resource requirements based on status of existing fleet and the expected demand growth in the future

• Existing generation and merit order• Gap between the expected load prof ile and

current generation f leet• Outcome: amount or required capacity

Analyze the supply side options• What are technology options• What are the technical and economical factors of

dif ferent technologies

Build investment plan and evaluate the alternatives• What are the preferred technologies• When to invest• What are the operational prof iles of new plants• What is the impact on existing system

Choose preferred investment plan• Which investment plan provides af fordable

electricity to consumers, while meeting the reliability standards and policy targets

1

2

3

4

5

6

guide the overall planning process, and therefore it is essential that the objectives are clearly de-

fined.

The following steps 2 and 3 analyze the need for new investments. Typically the demand growth

is fast in developing countries leading to a constant need for new investments to meet system

reliability standards. As an outcome of these phases, the system planner is able to answer the

questions: How much and when the new capacity is needed.

When the gap between the future demand and the existing generation capacity is defined, the

system planner defines potential supply and demand side options to fill the gap. A review of op-

tions begins with identification of all applicable options and related infrastructure, review of the

attributes of the options, and selection of promising options for further study and analysis. There

are hundreds of different supply options and configurations of options that could be used in a

power supply system, but only the suitable ones (which meet the set objectives e.g. nuclear is

often excluded) are taken to more detailed analysis.

Until Step 5 the standard system planning process is quite universal. However, there is quite a

big difference in investment planning evaluation internationally. In the evaluation process, the

system planner must assess the impact of new capacity to the existing fleet and the overall sys-

tem operation. The traditional planning and evaluation tool has been load duration curve analy-

sis, which provides a cumulative view of resource usage and stacking. This analysis method is

still widely used especially in countries where electricity demand growth is fast. While the load

duration curve based analysis is easy to build up, it has also limitations as it ignores the actual

dispatch profile of generation fleet.

The load duration curve analysis was the cornerstone of planning in the regulated areas of the

USA still 10 years ago. The fast development of advanced computer models and especially the

calculation power enabled an implementation of more detailed evaluation tools. These dynamic

dispatch tools provide more accurate view on the future power system costs, as taking into ac-

count the expected hourly or sub-hourly load profiles, ancillary services, and system constraints.

The benefit of the dispatch evaluation tools in the system planning is indisputable; consequently

majority of the regulated utilities in the USA are required to use these tools in their evaluation

process nowadays.

2 POWER SYSTEM INVESTMENT PLANNING TOOLS

New generation assets are not generally islanded or isolated - they operate in concert with nu-

merous power stations and in concert with transmission lines to neighbouring sub-systems across

which energy is generated and consumed. Therefore a system planner should propose assets that

minimize the cost of capital and operations for the entire fleet. Cost minimization in this context

can mean, for example, recognizing that it may be lower cost to invest in peaking type of genera-

tion that enables existing generation to operate in more stable manner instead of ramping up and

down the existing baseload plants.

The traditional way of analyzing the system level impact of a new investment has been load dur-

ational curve analysis. This analysis tool is a well established method, but it has its limitations

also. Therefore new tools are implemented in the markets like the USA. These new tools are

called dynamic dispatch tools which are complex software packages that mathematically deter-

mine the optimal, minimum cost build out of new generation capacity. Regardless the complex

nature of the dispatch tools, those have been widely used in the investment planning in the USA

markets during the last decade, since the more granular analysis and evaluation of investment

alternatives lead to lower cost to consumers.

2.1 Load duration curve analysis and its limitations

A load-duration curve shows the percentage (or number) of hours of the year at which the load is

at or above a given value or percentage of peak load. To make a load-duration curve, the 8,760

hours of the year are sorted in decreasing order of their average hourly load. The y-axis can then

represent either the actual load levels (MW) or the percentage of the peak load over the course of

the year (Figure 2).

Figure 2 Load duration curve example

The system planner has a task to “fill” the load duration curve with generation capacity, while

trying to minimize the overall system cost. Figure 3 illustrates the methodology in a simplified

example.

Figure 3 Simplified example of load duration curve analysis

Operating hours

Demand duration (hours)

Demand (MW)

Total cost

1500 5000 8760

10 000

15 000

20 000 22 000

Baseload

Intermediate

Peaking

Peaking Intermediate Baseload

Demand (MW)

1500 5000 8760

10 000

15 000

20 000

22 000

Baseload generation (coal, nuclear) has the highest capital and fixed costs but low operating

costs, which provides quite flat plot for the total costs for these types of assets. Due to high fixed

costs, the baseload investment is a feasible alternative if the investment receives high capacity

factor. For the peaking capacity (gas engines, open cycle gas turbines), the cost structure is the

opposite: low capital cost but relatively higher operating cost. Consequently, under the load du-

ration curve analysis, an investment in peaking capacity is the best option, if the plant is operat-

ing with relatively low capacity factor (5-20%).

The investment planning does not start from the empty table, but the new investments are inte-

grated into the existing generation fleet. The system planner assess the need for new investments

based on the expected load growth, which means that the load duration curve is shifted up ac-

cordingly. The load duration approach favours investment in baseload capacity especially in the

markets with fast demand growth, as there is always “room” for new baseload investment.

The new baseload investment has typically higher efficiency (and lower operating cost) than the

existing plants in the system, which allows it to go into the bottom of merit order that enables the

high capacity factor for the plant. However, the new plant also changes the operational profiles

of the existing plants. The existing base load plants move up in the merit and start to operate in

intermediate mode. This change on load profiles of existing base load capacity is excluded from

the load duration curve analysis.

While the load duration curve gives a good estimate on the load profile for the new investment, it

does not tell how the remaining generation assets are operated to cover the remaining hourly

patterns (See Figure 4 for an example of weekly chronological load curve).

Figure 4.Example of chronological weekly load curve

Consequently a number of operational complexities are ignored in the investment analysis,

which may lead to sub-optimal investment decision. The excluded elements of the load duration

curve analysis are:

Hourly load pattern and operational pattern for all plants

Dependencies between operating hours

Number of starts and stops, including start-up costs

Part load generation efficiency

Provision of ancillary services

Forced outage rates for each technology

As these real operational elements and cost factors are not included into the investment analysis,

there is a risk that part of the actual costs is excluded. For instance, a new baseload investment

might change the operational profile of intermediate combined cycle gas turbines (CCGT) in a

way that increases the number of starts and part load generation of these plants, which leads to

increased system costs.

2.2 Dynamic dispatch modelling tools in the system planning

Dynamic dispatch modelling tools are used in the system planning to tackle the limitations of the

load duration curve based analysis. The load duration curve analysis can be still used as an input

for more detailed investment analysis, as it is fast to use and can provide relatively reliable re-

sults in general level. The dynamic dispatch modelling tools are used to provide more accurate

information on the power system operations and costs with the planned asset fleet. The objective

of the tool is to analyze the total system production cost for singular expansion plan subject to

hourly load, ancillary services, system constraints and generation asset constraints. In other

words, the dynamic dispatch model optimizes the system operation cost with the given fleet of

assets while maintaining the system reliability for each hour of the year.

The system planning process and the investment planning process is similar to the one illustrated

in Figure 1, but the evaluation of each proposed investment portfolio is done using a more granu-

lar approach. The process to build dynamic dispatching evaluation is described in Figure 5.

Figure 5.Dynamic dispatch evaluation process

The First step is to define the inputs for the model. The required amount of information is larger

and more granular than in the load duration curve analysis. In the system planning perspective,

several different investment portfolios are built on top of the existing generation fleet. The input

information includes detailed information on the technical characteristics of each power plant,

GEN

ERAT

E D

ISPA

TCH

•Dispatch the system for each hour to meet system needs

System demand + operating reserves

•Optimize the operation of capacity mix to minimise costs reliably

•The dispatch tools takes into account the technical limitations of power plants e.g. Ramp rates

INVE

STM

ENT

POR

TFO

LIO •Load forecast and load

pattern for each hour

•Reliability standards and reserve amounts

• Information on the generation assets

EfficienciesDynamic features (start times, ramp rates)O&M costs, starting costReliability

•Cost information (fuel cost, water etc.)

•Transmission network with constraints

AN

ALYZ

ETH

E O

UTC

OM

E •Total system operating cost

•Cost division of generation to meet the load

Fuel off-takeStart-up costsO&M costsEmissions Cost to serve reserves

•Generation by power plant

•Operating profiles of each power plant

•Transmission grid power flows

STEP 1 STEP 2 STEP 3

transmission constraints and system reliability standards. As the dynamic dispatch tool tries to

minimize the system operating costs, also the cost information e.g. fuel prices are required.

The Second step consists of the actual system level dispatch modelling, which requires a specific

tool. There are several commercial tools available, such as PLEXOS, AURORA and PROMOD.

Dynamic dispatch tool optimizes the system generation fleet against the hourly load and reserve

requirements while taking into account dependencies between the hours. For instance, the dis-

patch tool notices power demand changes from hour to hour and takes into account the start-up

costs and efficiencies during ramping periods while optimizing the operation for each dispatch

period. This typically increases the dispatch of flexible peaking capacity that is able to reach

maximum efficiency fast after the start up and maintain it over the whole dispatch period. The

dispatch analysis is completed for each investment portfolio with hourly granularity to support

the system planning process.

The Third step focuses on the dispatch modelling output analysis. The dynamic dispatch tools

provide large amount of information on the generation fleet operation as well as about the system

metrics. From the system planning perspective, the most interesting element is obviously the

total system operating cost between the modelled investment scenarios. Analysis of the outcome

is a very important element of the analysis as it usually provides new information on the system

optimization, which enables the system planners to make better decisions about the new invest-

ments.

2.3 Experience on dynamic dispatching tool analysis from the USA

As energy demand across the USA rises and the generation fleet ages, utilities must plan to add

and retire generation capacity in the most cost-efficient way while meeting reliability standards.

The process to meet these objectives varies among the states and markets. In the regulated areas

of the USA, Integrated Resource Planning (IRP) started to be utilized in the late 1980s and ever

since it has been an accepted way for utilities to create long term plans. The general IRP process

was described in Figure 1.The investment planning process in a regulated utility environment.

The utilities must provide as accurate information on their investment plan to the regulator as

possible, since the regulator gives the final approval for the plans.

To guarantee a higher level of accuracy on the forecasted system costs, the regulators started to

require dynamic dispatch analysis to be conducted on the investment plans in late 1990s. This

analysis method was spread over the regulated utilities in the early 2000s. Nowadays, a dynamic

dispatch analysis is the prerequisite for each investment plan approval in the regulated parts of

the USA. The following chapters describe two examples of dynamic dispatch analysis conducted

as part of the IRP process in the USA.

2.3.1 Arizona Public Service

Arizona Public Service (APS) is a regulated utility that operates in the state of Arizona in the

USA. In the 2014 IRP1 APS has analyzed potential ways to meet its projected 13,000 MW re-

source requirement in its service region by 2029. When combining the projected load growth and

expected unit retirements, APS anticipates a need of over 6,600 MW of additional resources of

which more than 4,000 MW will be flexible gas capacity. The IRP process of APS is shown in

Figure 6, and it follows very closely the “standard” process presented earlier in Figure 1 and it

includes dynamic dispatch evaluation process, presented in Figure 5.

1 Arizona Public Services: Integrated Resource Plan 2014 (http://www.aps.com/en/ourcompany/ratesregulationsresources/resourceplanning/Pages/resource-planning.aspx)

Figure 6.The integrated resource planning process of Arizona Public Service1

Figure 7 shows the resource planning model of APS including the inputs for each step. The first

four steps feed information to Step 5 (the scenario analysis), which tests the investment scenarios

over the planning horizon, while taking into account several uncertainties, such as changes in gas

prices.

Figure 7.Resource Planning Model of Arizona Public Service1

The developed resource portfolios include the existing generation fleet and power contracts, as

well as potential future conventional, renewable and energy efficiency measures. The portfolio

analysis includes dynamic dispatch simulations and thus captures how an individual resource

would be expected to be operated in APS system. Several resource portfolios are developed as

part of the IRP process, and the most promising ones are tested with the PROMOD IV dispatch

tool. In the 2014 IRP process, six different portfolios were tested with the PROMOD tool.

The 2014 IRP results were something new for APS, which has mainly invested in baseload gen-

eration in the past. The fastest growing capacity types during the evaluation period will be in-

flexible nuclear generation and intermittent renewable generation, mainly solar PV. The intermit-

tent generation will require corresponding increases in highly flexible resources to provide APS

with the tools to manage the future power system. The analysis results showed that the invest-

ment focus will be in renewables and flexible gas capacity, which is totally new investment path

after the previous baseload era. The high level IRP results are shown in Figure 8.

Figure 8.Changes in the APS generation assets by 20291

The dynamic dispatch analysis took into account the increasing variability caused by increasing

share of variable renewable generation, and helped to recognize the need for fast ramp rates and

short start-up times. Based on the dynamic dispatch analysis, APS decided to invest in flexible

gas generation instead of less flexible coal or CCGT units. The investment plan was approved by

the regulator, as APS’ analysis showed clearly that the more flexible generation portfolio will

lead to the lowest cost to consumers. Without the dispatch analysis the starting costs and ramping

costs – which have been minor cost elements in the past - would have been excluded. This would

have lead to investments in less flexible assets and caused excess cost to consumers.

2.3.2 Portland General Electric

Portland General Electric (PGE) is a regulated utility in the state of Oregon in the USA. PGE has

successfully used dynamic dispatch modelling in their IRP process over the years with special

focus on generation side flexibility. The flexibility dilemma has risen due to growing demand

and increasing share of wind generation in PGE’s service area. In their 2009 IRP2, PGE states

following:

PGE, like other utilities in the region that have benefited from a historically robust hydro system,

has traditionally had greater energy needs than capacity needs. Due to reduced access to hydro,

increased reliance on non-dispatchable and intermittent wind generation, and the continued

growth of summer peak loads, our capacity needs now exceed our energy requirements and oc-

cur sooner than expected2.

Based on their analysis, PGE found out that they will need around 870 MW of new supply side

resources to meet with the growing demand, required operating margin and planning reserves

(Figure 9). The traditional load duration curve analysis would potentially suggest baseload gen-

eration as the best option to fill the gap, as the demand is steadily increasing.

Figure 9.PGE's energy load balance in the 2009 integrated resource plan2

The regulator of Oregon State requires detailed portfolio level investment analysis for the future

generation asset. To meet the targets of the regulatory process, and to provide affordable service

to customers, PGE uses the following evaluation process2 for each potential supply side portfolio.

1. Define supply side portfolios to meet the future energy demand and reliability standards

(870 MW of new capacity by 2015 in this case)

2 Portland General Electric Co.2009 Integrated Resource Plan (http://www.portlandgeneral.com/our_company/energy_strategy/resource_planning/docs/irp_nov2009.pdf)

2. Use hourly dispatch model called AURORAxmp to define operating profile and whole-

sale electricity cost for the whole region. The analysis region covers the whole intercon-

nected system in the Western USA called WECC.

3. Dispatch existing and future alternative resources available to PGE in AURORAxmp,

using its projections for hourly electric market prices and resource availability for all ar-

eas in the WECC

4. Group alternative resource mixes in different portfolios and calculate the total long-term

variable power cost of each portfolio.

5. Combine the variable power cost from AURORAxmp with the fixed revenue require-

ment (capital and fixed operating cost) for each of the alternative portfolio.

6. Calculate the overall net present value for each portfolio

7. Use scenario analysis to assess portfolio risk performance for each portfolio based on

changes in portfolio cost under varying future conditions (changes in fuel prices, emis-

sion costs etc.)

The hourly dynamic dispatch modelling with AURORAxmp provides detailed information on

the portfolio’s operating cost and performance in future market situation. By testing different

portfolios in their 2009 IRP, PGE found out that the optimal future investment portfolio contains

400 MW of baseload gas generation, 250 MW of flexible gas generation capacity, and around

270 MW of energy efficiency measures. The investment in flexible gas generation was not an

obvious solution, but the dynamic dispatch modelling extracted the value of flexibility, since it

optimizes the operation of the whole generation for each hour to meet the demand and ancillary

service requirements.

In PGE’s case, the provision of required ancillary services made a big difference. Figure 10 illus-

trates the weekly ancillary service provision from the existing Beaver CCGT plant before in-

vestment in flexible capacity. In the base scenario, Beaver CCGT provides constantly ancillary

services. This means that the plant is operating on partial load for energy generation which re-

duces its electrical efficiency. Figure 11 shows the ancillary services provision from the same

CCGT after 200 MW of flexible capacity has been implemented into the dispatch modelling.

After the flexible capacity has been implemented the CCGT is not needed for the provision of

ancillary services anymore. Instead, it is operating at full load with higher efficiency, while the

new flexible capacity is providing the required ancillary services.

Figure 10.Weekly average ancillary service provision of the Beaver CCGT before the new flexible gas capacity3

Figure 11.Weekly average ancillary service provision of the Beaver CCGT after the new flexible gas capacity3

3 Presentation by Portland General Electric at Flexible Power Symposium 2013

The PGE example case shows well the value of dynamic dispatch modelling in the power system

planning. When the real dispatching requirements and the system needs are considered in the

planning phase, also the total system costs are visible. Provision of ancillary services, part load

operation and starting costs are traditionally considered to be negligible, but in real life these cost

elements can have a significant impact when. The dynamic dispatch modelling helped PGE to

uncover these costs and to make the right decision on future investments.

3 DISCUSSION – VALUE OF DYNAMIC MODELLING FOR ASIAN SINGLE BUYER UTILITIES

The examples on Integrated Resource Planning from different US single-buyer utilities highlight

how dynamic investment plan assessment is being used to assess different alternative generation

portfolios by simulating their performance over different dispatch patterns. Comprehensive soft-

ware packages also allow power system planners to test alternative portfolios over many vari-

ables, including fuel price, demand growth and asset performance uncertainties. Based on the

IRP outcomes, dynamic investment plan assessment when conducted over multiple alternative

capacity expansion plan portfolios, supports the selection of lowest total cost portfolio in the

investment planning process.

Dynamic modelling has a lot of potential in supporting Asian single-buyer utilities in their capac-

ity expansion planning, too. Dynamic investment assessment planning is a relatively new ap-

proach even in developed markets because, until recently, computer capacity was not available

for conducting such detailed system studies. Thus, single-buyer utilities’ choices were limited to

fairly simple load duration curve based planning. At the time, most Asian single-buyer utilities

were also experiencing an era of rapid GDP growth, rapid electricity demand growth and were

not actively pursuing intermittent renewable generation growth. This made base load capacity –

focused expansion a valid approach. However, this is changing.

First of all, as the electricity demand growth rate slows down in many Asian single-buyer mar-

kets (see Figure 12), the focus of capacity addition shifts from base load to intermediate and

peaking requirements.

Figure 12.Average annual electricity demand growth rate (CAGR) in selected Asian countries4

Secondly, there’s an increasing interest towards renewable energy in the Asian countries, espe-

cially towards wind and solar PV plants. As an example, Japan introduced an attractive feed-in

tariff (FiT) scheme in 2012, which has lead to significant interest in solar PV, wind and liquid

bio fuel generation. Based on its Power Development Plan 2010 Rev 3, Thailand plans to install

5GW of new renewable generation by 2020, mainly from solar, wind and biomass sources. Also

Malaysia has introduced a FiT scheme for solar plants and announced the signing of a PPA for

the country’s largest, 50MW solar power plant in April 20145. Finally, as income levels rise,

households across developing Asia are consuming increasing amounts of electricity during peak

periods. More pronounced peaks in daily load curves require additional flexibility in power gen-

eration. We are already seeing some single-buyers and the market regulators, including TNB of

Malaysia, increasingly using dispatch software such as PLEXOS for power plant scheduling and

dispatching in order to optimize operational costs6. They are also exploring its use for dynamic

power system planning.

Thus, with the arrival of new more powerful computers and software and increased requirement

for system flexibility, the time seems to be right for implementation of new, more accurate

4 BP Statistical Review of World Energy June 2013 (http://www.bp.com/statisticalreview) 5 Reuters: Malaysia's 1MDB wins solar power plant project (http://www.reuters.com/article/2014/04/14/malaysia-1mdb-solar-idUSnL3N0N62120140414) 6 TNB Single-buyer department: Malaysian Grid Code - Part VII: Scheduling & Dispatch Code (Presentation held as part of Malaysian Grid Code Awareness Program January 22nd, 2014)

0.0%2.0%4.0%

6.0%8.0%

10.0%12.0%

14.0%16.0%

1990's

2000's

methodologies for power system planning. However, to confirm the relevance of dynamic in-

vestment plan assessment in Asian single-buyer market context, we will conduct dynamic power

system simulation for one or several Asian single-buyer markets using our in-house PLEXOS

software in the future.

4 CONCLUSION AND NEXT STEPS

This paper introduced the dynamic investment plan assessment process, which is widely in use in

single-buyer markets of the USA. This accurate investment planning process has gained popular-

ity there due to increase in computing power, availability of complicated dispatch software pack-

ages and increased focus by regulators on accurate forecasting of total system costs. We dis-

cussed its differences and benefits in comparison to traditional load duration curve -based model-

ling and identified factors that support the need for implementation of dynamic investment plan-

ning also in Asian single-buyer markets. However, the relevance of dynamic investment plan

assessment for Asian single-buyer markets should be confirmed through case studies computed

with one of the dynamic dispatch tools commercially available.