Market Structure - System Trends · Restricted © Siemens AG 20XX All rights reserved. Smart Grid Division Market Structure - System Trends Dr. Sankaran Rajagopal Siemens Smart Grid,

Restricted © Siemens AG 20XX All rights reserved. Smart Grid Division

Market Structure - System TrendsDr. Sankaran RajagopalSiemens Smart Grid, EA Solutions, Minnetonka, MN

Smart Grid Division

Restricted © Siemens AG 2013 All rights reserved.

Page 2 Smart Grid Division

• Significant General Industry Trends • Combined Cycle Usage • Fuel cost Trends • Renewable Outlook and Penetration

• Trend imposed impacts and Challenges• Overview of Siemens Security Constrained Unit

Commitment (SCUC) Configuration• Changes in Look Ahead Security Constrained

Dynamic Dispatch (SCDD)• System Ramping Constraint• Multi-Stage Generation (MSG) Models• Storage Models and Demand Response (DR)

Models• Market Operator Training Simulators• Review of Ancillary Service (AS) Procurement

• Improvements Needed and Conclusion

Content



Significant General Industry Trends

Low Gas prices as a long term trend • Increasing gains in production from domestic shale

formations

• Subsequent expansions of Gas pipeline network

• First time in April 2012 natural gas share of U.S. electric power sector was almost equal to the coal share [US Energy Information Administration, April 2013]

• Long term trend of lower gas prices is likely to stay based on forecasts from EIA in April 2013



Combined Cycle Usage – US eia.gov

• The combined cycle capacity utilization significantly increased beyond year 2010 due to lower gas prices



Fuel cost Trends – US eia.gov

• Trends also indicate Gas and Coal share in generation are comparably closing in

• Comparable prices also mean a challenge for SCUC solution performance for optimal solution with low MIP gaps



Significant General Industry Trends (contd..)

Increasing Renewable penetration in the grid

• Average renewable penetration is forecast as 15% of total power generation by year 2020 based on recent EIA forecast

• State of California Executive Order S-21-09: Directs CPUC, the California ISO, and the Energy Commission to adopt regulations for increasing California’s Renewable Penetration to 33 percent by year 2020

• Out of the US Average Renewable based power generation nearly 40 percent is of intermittent nature

• That implies as much as 6% to 13% of power generation (averaged generation and not installed capacity) can be intermittent by year 2020



Renewable Outlook 2013 – US eia.gov

Some states will have much higher penetration rate than the national average



Renewable Penetration by type US eia.gov

• ATRA case is forecast with Tax credit - signed bill of Jan. 2013 in effect

• Intermittent Renewable Growth is reaffirmed in this April 2013 forecast of US EIA.



Trend imposed Primary Impacts to consider

Combined Cycle Plants Modeling and SCUC• The built up capacity of Combined cycle plants of the early 2000’s are

now being utilized better nearly a decade later• Decade old implementation of CC Plant modeling and adaptation in

SCUC needs review and revamping to align with the trend• More emphasis needed in Market software for CC Plants• Configuration transitions are identified in sub-hourly intervals of

SCUC in Real-Time Market • Full utilization of Combined-cycle GTs configurations and capacity

in all Markets



Trend imposed Primary Impacts to consider (cont.)

Increasing Renewable penetration in the grid• ISO Dispatched Demand Response is growing• Uncertainty and interruptions due to wind and solar

penetration to be managed• Available Price responsive Demand not-visible-to-ISO

is growing and to be incented• To offset reliability impact of intermittency review

needed for• Faster resources and CC Plant

commitment/dispatch in Real-Time Market• Importantly Ramping capacity review and ability to

act when needed



Summary of Improvements made

• Larger number of intervals and reduced duration of intervals in Market Software, especially Real-Time Pre-Dispatch (Unit Commitment) and Real-Time Dispatch

• Enforcing the availability of Ramping capacity to manage intermittency

• Better modeling and optimization in SCUC to manage CC Plant configurations in Real-Time Markets for Energy and AS

• Modeling and Managing dispatch of Storage devices and DR • Drastic changes in commitment patterns pose a challenge for

Operators for post-contingency operations• Market Operator Training Simulators• Enforce procurement of AS from right locations



Overview of Siemens SCUC Configurations

Solver - MIP Engine with Separable Quadratic Interior Point Method, Co-optimization of Energy and AS, Dynamic Ramping

Security Constrained Unit Commitment with Full AC Power flow, Contingency Analysis, and AC Loss modeling

• Forward Market: Market Power Mitigation (MPM), Day Ahead Market (DAM), Reliability Unit Commitment (RUC). Configured between 24 to 72 intervals of 1h size at CAISO

• Real Time Pre Dispatch (RTPD): SCUC Configured between 4 to 18 intervals of 15 minute size. Being expanded to 24 intervals.

• Real Time Dispatch (RTD): SCUC Configured as Security Constrained Dynamic Dispatch (SCDD) mode used in 8 to 13 intervals of 5 minute size. Being expanded to 21 intervals.



Changes in Look Ahead Real Time Dispatch - SCDD

Look Ahead SCDD with longer horizons• Configurable parameters set at 13 intervals now (to be changed to have

21 intervals)• Twenty one intervals cover the duration of bids available and provides

nearly a two hour horizon• Variable horizon from 12 - 21 intervals covering full range of available

bidsBenefits

• Lowers over all cost of Load following• Utilizes the Load Forecast improvements (errors in next two hours as

0.4% and 0.75% as typical experience)• Advisory interval Locational prices available for up to two hours • Advisory Price signals for non-ISO-participating DR is made possible

Future Plans• Commitment of Fast-start resources during RTD



Advisory Intervals of RTPD - 7interval run

Advisory Intervals of an Hour Ahead Scheduling Process - Published



Advisory Intervals of RTD

Advisory Intervals of RTD - Market clearing result



System Ramping Constraint

• DAM and RTPD provide a basis for commitment and dispatch against current load forecast at that time

• RTD further provides a basis for dispatch against very short term load forecast

• Intermittent renewables pose a challenge in Real Time Dispatch for finding sufficient ramping capacity for load following

• Regulation and Spin capacity made available by RTPD provides the basis

• An additional safeguard by means of System Ramping constraint is introduced for ensuring reliability in real-time operation to safeguard against intermittency

• Plan in progress for the future at CAISO: Flexible Ramping as a commodity in the Markets



Multi-Stage Generating (MSG) Resource Model

Generic Formulation of MSG to account for Combined Cycle Gas Turbines

• One or more GT combined with HRSG (ST) to capture heat from GT exhaust

• Different combination of GT and ST are called as 1x1, 2x1, 2x2

• The plant can use after burners (duct firing) to enhance the operating range of the CC Plant

• At any configuration, a transition to any possible another configuration is fully considered in optimization in both DAM and RTM

• Each combination can have minimum on /off time and its own static ramp rate or dynamic ramp rate



Technical FeaturesMulti-Stage Generator – Configuration Model

• Models all possible configurations

• A 2 CT and 1 ST Configuration Content Comment

0 0 CT-O ST OFFLINE

1 1 CT-0 ST StartupShutdown

2 1 CT – 1 ST Shutdown

4 2CT – 0 ST

5 2 CT – 1 ST




Modeling Capability• Physical limits and price curve for each configuration • Overlapping or Non-Overlapping Operating Range • Transition Matrix

• MUT, MDT for each plant and configuration• Transition times • Limit for # of transitions • Startup, shutdown, transition costs• Reserve capability of configuration• Startup, Shutdown, transition profiles for proper

accounting of energy in SCUC • Modeling to account for physical constraints of

configuration and individual plants




Example: 5-state resource modelT is the state transition time and C the state transition cost. Permissible state transition paths are 0↔1↔3↔4, 0↔2→3↔4, and 0↔2→4, …there is not transition from state 4 or 3 to state 2.

0

2

3 4 1 T01, C01

T02, C02

T23, C23

T13, C13 T34, C34

T24, C24

T31, C31 T43, C43 T10, C10

T20, C20




• Model example• Plant capacity 253MW to 880MW

• Transition model

Mode Lo Limit

Hi Limit Ramp Up

Ramp Dn

Start-Up Time

Start-Up Shutdown

1x1 253 261 6.0 6.0 120 Yes Yes

2x1 380 580 15 15 YES

3x1 600 880 12 12 YES

ID FROM TO Cost ($) Fuel Energy Time Notification

100 2x1 1x1 0.0 0 0 30 min 60 min

101 2x1 3x1 100.0 900.00 0 60 min 60 min

102 1x1 2x1 150 900.0 0 60 60

103 3x1 2x1 0 0 0 30 60



Limited Energy System Resource (Storage) Models

Highlights of functionality of Storage Models• Available for both DAM and RTM• Both Regulation and Non-Regulation roles• Max and Min charge limits in MWh• Positive Pmax to Negative Pmin range• Scheduled Outages and derates modeled• Time varying Modeling for

• State of Charging: SOC (t) • SOC(t) is utilized in AS Award determination• Distinct charging and discharging (ramp) rates• Seamless transition from charge to discharge state



Storage Model Operating and Bid Range



Example Use of DR Model using a Storage Model

RUC

Energy Bid

Regulation Up

MW

$/MWh

Pmin PmaxReg min

Reg max

Regulation Dn

SpinNon Spin

Eco min

Eco max

MW

$/MWh

Pmin Pmax

Reg min

Reg max

Eco min

Eco max

Min Charge Min

Discharge

00



Market Operator Training Simulators

• Used for training the Market Operator (Similar to OTS in EMS) inReal-Time Market operation

• Uses the same code base as Operational System• Additional components for Instructor and Scenario management• Ability to Create training Scenarios from actual operating

conditions (PRODUCTION save cases) for a duration of 24 hours – 48 hours continuous RTM simulation capability

• Ability to create Market type events (lack of AS bids, late arrival of bids or interface data, Forecast errors, etc., Transmission derates) in addition to traditional OTS type events for Transmission and Generation

• Ability to pause, run and rerun scenarios in simulated time • Ability to run in Stand alone or closed loop with EMS simulator



MOTS Component Overview

Market Execution

Component

Enterprise Bus

ScenarioLibrary

Market EventsLibrary

ExternalProviders

Market operating Simulator

Component

InstructionComponent

EMMDatabase

Production Save CasesCopy save cases from

mounted directoryUpdated save case

information table from PROD Actors: Trainer, Trainees

Page 26 September 2012



Review of Procurement of AS in Progress

• Currently, AS is procured in Regional level• Certain post-contingency state may not allow utilization of available

reserves of SPIN and REG, where it is needed• Simulate the impact of dispatching reserves in post-contingency on

Transmission grid to verify deliverability of Reserves • Ensuring the procurement is not from wrong locations is beneficial• SCUC with Full AC Network Analysis capability is utilized• Avoidance of expensive Exception dispatches for Preventive

scheduling• Modeling of Generator outage as a part of Market Software

Contingency analysis to verify Deliverability of AS • Locational Procurement of AS also leads to Locational AS prices

similar to Energy



Improvements Needed

• Increased importance of Forecast for: Renewables, Ramping and AS• DR as a control variable in load-following and Commitment of Fast-

Resources• Energy Imbalance Market problem formulation and solution• Effective use of RTM Look Ahead and DAM results of PSS/E cases

• VSA and DSA for Real Time operations situation awareness• Compute Nomogram limits as dynamic limits reflecting current

status of system• VSA and DSA for the next day from DAM results• Improved optimization algorithms to handle uncertainties• Modeling and managing contingencies in fuel supply (gas, hydro,

wind, solar) within market software• Situation Awareness improvements

• Focus on Situation or Trend Prediction



Conclusion

• Optimization and Modeling for better utilization to face Trends in Gas industry (CC Plants – MSG Modeling)

• Intermittent Renewables impact and solutions are reviewed:• Look Ahead SCDD – Scale up number of intervals• System Level Ramping constraints• Lowering the cost of Load following• Storage Modeling• Price signals for non-ISO-participating DR

• Changing commitment patterns and intermittency requires additional support to Market Operators

• Market Operator Simulator solution• Ensuring post-contingency state is managed better with AS

procurement at right locations



Acknowledgement

• Siemens team gratefully acknowledges the contributions made by the California Independent System Operator Subject-matter-experts in efforts related to the design, implementation and validation of the discussed topics.



Questions/Answers

Market Structure - System Trends · Restricted © Siemens AG 20XX All rights reserved. Smart Grid Division Market Structure - System Trends Dr. Sankaran Rajagopal Siemens Smart Grid,

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