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Task 2111.002. Towards Sustainable Intra-Dispatch Power Balancing. Nipun Popli [email protected] Marija Ilić [email protected] System Balancing. A Two-Step Approach. Scheduling Unit Commitment Economic Dispatch. Error Balancing Stabilization Tracking.

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Towards sustainable intra dispatch power balancing

Task 2111.002

Towards Sustainable Intra-Dispatch Power Balancing

Nipun Popli [email protected]

Marija Ilić [email protected]


System balancing
System Balancing

A Two-Step Approach

Scheduling

Unit Commitment

Economic Dispatch

Error Balancing

Stabilization

Tracking


Intra dispatch real power balancing
Intra-Dispatch Real Power Balancing

  • Need for Tracking

  • Prediction Error in Load

  • Intra-Dispatch Variationsin Load

  • Conventional Approach

  • Hour Ahead Load Curve projected- Data-History

  • Generators are Ramped Up

  • Average Ramp-Rates- MW/5-minute

  • Remaining Error picked-up by AGC


Renewable portfolio std expected scenario
Renewable Portfolio Std. : Expected Scenario

  • Tehachapi Wind Generation in April ‘05

  • NYISO-17% Projected Increase in Load Following Requirements[1] (2009-2020)

Picture: D. Hawkins & C. Loutan, Integration of Renewable Resources, PSERC Tele-Seminar-Webinar Presentation,, October 2007

[1] Growing Wind- Final Report of the New York ISO 2010 Wind Generation Study, September 2010 ISO New York


How wind affects intra dispatch tracking
How Wind affects Intra-Dispatch Tracking?

  • Tracking System Imbalances under Wind Penetration

  • Increased Variability in 5-minute time-frame

  • Wind Speed: Lack of Rich Data History

  • Short-Term Forecasting Error Prone

  • Inconsistent Correlation with Load Swings

  • Consequences

  • Increase in Load/Wind following Requirements

  • Hard-to-define Ramp Rates for Wind

  • Law of Averages MW/5-minute may not hold good

  • Large Error left-over for AGC


Typical intra dispatch balancing by utilities
Typical Intra-Dispatch Balancing by Utilities

SOURCE: Y. Makarov, C.Loutan, J. Ma, P. Mello, S. Lu ‘Impacts of Wind Generation on Regulation and Load Following Requirements in the California System’ PES General Meeting-Conversion & Delivery of Electrical Energy in 21st Century 2008 IEEE


Renewable portfolio std violation of cps
Renewable Portfolio Std. : Violation of CPS

  • NERC’s Control Performance Standards not met

Non-Zero Mean ACE

Frequency Offsets Out of Bound

M. Ili ́c , N. Popli, J. Y. Joo, and Y. Hou, A Possible Engineering and Economic Framework for Implementing Demand Side Participation in Frequency Regulation at Value, IEEE Power Engineering Society General Meeting, July 2011


Intra dispatch real power balancing1
Intra-Dispatch Real Power Balancing

Managing System’s Heterogeneity


Sources sinks of energy
Sources & Sinks of Energy

  • Sources

  • Sinks

  • Controllable

  • Dispatchable

  • Time-Scale of Technology (Combustion/Steam/Hydro/Nuclear/Storage)

  • Controllable

  • Responsive

  • Size & Time-Scale Type (Inductive or Resistive)

  • Residential/Commercial/Industrial


Intra dispatch power balancing
Intra-Dispatch Power Balancing

  • Proposed Approach

  • Automated Feedback Control

  • Based on Quasi Stationary Concept

  • Formal Mathematical Model forPower Balancing

  • Power Imbalance: Feedback Signal

  • AGC responds to Frequency Offsets


Generation resources
Generation Resources

Sustainable Intra-Dispatch Real Power Balancing

Case Study for Flores, Azores Island

N. Popli, M. Ili ́c, Modeling & Control Framework to Ensure Intra-Dispatch Regulation Reserves, Book-Chapter, The Case of Low-Cost Green Azores Islands


Flores island network
Flores Island Network

Network

  • 45-Bus Radial

  • 2 MW Demand

  • Mix of Generation: 4-Hydro (1.7 MW), 4-Diesel (2.5 MW), 2-Wind (0.66 MW)

    Wind

  • Wind ~ 14% Installed Capacity

  • Scheduled Wind ~ 21% Total Demand


Flores wind forecast measurements
Flores: Wind Forecast & Measurements

Challenges & Issues

  • Prediction Error over 10-minutes

  • Lack of Intra-10 minutes Wind Speed Data

  • 10% decrease in Load (i.e. Increase in Wind) within an hour

  • Hard-to-define Wind Ramps

  • Not enough Primary Reserves for Stability

Noha A Karim, M. Ili ́c , Multi-temporal Wind Power Forecasting Models for Operations and Planning, , Book-Chapter, The Case of Low-Cost Green Azores Islands


Mechanical dynamics of energy resources
Mechanical Dynamics of Energy Resources

A Three-Way Relation

Generators Steady State Droop

  • Hydro

0

Challenges & Issues

  • Prediction Error over 10-minutes

  • Lack of Intra-0 minutes Wind Speed Data

  • 10% decrease in Load (i.e. Increase in Wind) within an hour

  • Hard-to-define Wind Ramps

  • Not enough Primary Reserves for Stability

  • Diesel

0

N. Popli, M. Ili ́c, Modeling & Control Framework to Ensure Intra-Dispatch Regulation Reserves, Book-Chapter, The Case of Low-Cost Green Azores Islands


Generator s steady state droop
Generator’s Steady State Droop

Steady State Droop/Steady State Gain

Gain

Droop

  • Hydro

  • Diesel

N. Popli, M. Ili ́c, Modeling & Control Framework to Ensure Intra-Dispatch Regulation Reserves, Book-Chapter, The Case of Low-Cost Green Azores Islands


Wind loss case of higher intra dispatch variability
Wind Loss: Case of Higher Intra-Dispatch Variability

Rate of Energy Produced=Rate of Energy Consumed

+ Rate of Wind Energy Loss

Align Time-Scales of Generation Resources with

Time-Scale of Power Imbalances


Tracking real power imbalances
Tracking Real Power Imbalances

  • Power Model

Measured Imbalance

Can’t be Predicted

  • Delayed Response: Feedback Approach

  • Correction Error: Picked by AGC


Flores tracking quasi stationary wind variations
Flores: Tracking Quasi-Stationary Wind Variations

Balancing Flores Island

  • Steady-State Droop subjected to Network Constraints

  • Generator respond to Quasi-Stationary Wind Variations

  • Feedback Response to Sustained Deviations

  • Set Points Updated 30-seconds

  • Error/Residual Imbalance picked-up by AGC/Slack

N. Popli, M. Ili ́c, Modeling & Control Framework to Ensure Intra-Dispatch Regulation Reserves, Book-Chapter, The Case of Low-Cost Green Azores Islands


Conventional modeling approach
Conventional Modeling Approach

A Better Modeling Approach ?

Mechanical

Sub-System

Electrical

Sub-System

Energy

Dynamics ?


Mapping energy dynamics
Mapping Energy Dynamics

Typical Wind Ramps

Source: Caiso.com Renewable Profile for 20th February 2012


Mapping energy dynamics1
Mapping Energy Dynamics

Stand-Alone Steam Power Plant

Mechanical

?

Steam Power Plant: Ion Boldea, Synchronous Generators, CRC Press, 2006


Mapping energy dynamics2
Mapping Energy Dynamics

Stand-Alone Hydro Power Plant

Head ?

Surge Tank?

Mechanical

&

Penstock


Intra dispatch demand response
Intra-Dispatch Demand Response

  • Sources(Dispatch able/Controllable) & Sinks of Energy

  • What we need to balance ?Load (history known), wind (predicted-based on wind speed information)

  • High Degree of Heterogeneity in System?

  • HOW TO BALANCE IT SUSTAINABLY? (Ostrom, simplistic approach for balancing)

  • Secondary Control (ACE based, CPS criteria, no well defined control protocols for load following at system level )

  • Cradle to Grave analysis of how the energy is produced and consumed ?

  • Align time scales of generation with that of imbalances or change system condition

  • Real Life System (Azores Island) Hydro vs Diesel

  • Conventional thinking in terms of Mechanical/Electrical sub-systems (Mechanical for SSSA and Electrical mainly for Transient). These involves dynamics. On a longer time scale the operator worries about ED and UC. Since the load pattern is known in advance due to past operating experience. Ramp rate is just being used as a steady state constraint so far in optimal scheduling of system resources , which we call as economic dispatch.

  • Fluctuations vs Sustained Deviations (later becoming more of a problem as wind percentage increase (CAISO). Problem will move from present stabilization to tracking in the future (just think of it as an hard-to-predict negative load). Need more stand-by reserves or ramp-up online energy resources

  • What do we mean time scale alignment ??? Rate of Consumption of Energy = Rate of Production of Energy – Rate of Production of Wind Energy (at nominal frequency i.e. 60 Hz)

  • LOOK AT MONOGRAPH CHAPTER FOR SUBSECTIONS (wind info, feed fwd/back, savings on regulation reserves, violation of CPS criteria, Detailed Governor Model (primary source))



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