Reserve and congestion management using wind power probabilistic forecast a real case study
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2011 MAR 17. Reserve and Congestion Management Using Wind Power Probabilistic Forecast: A Real Case-Study. Ricardo Bessa 1 ( [email protected] ) Leonardo Bremermann 1 , Manuel Matos 1 Rui Pestana 2 , Nélio Machado 2 Hans-Peter Waldl 3 , Christian Wichmann 3

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Reserve and Congestion Management Using Wind Power Probabilistic Forecast: A Real Case-Study

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Reserve and congestion management using wind power probabilistic forecast a real case study

2011 MAR 17

Reserve and Congestion Management Using Wind Power Probabilistic Forecast: A Real Case-Study

Ricardo Bessa1 ([email protected])

Leonardo Bremermann1, Manuel Matos1

Rui Pestana2, Nélio Machado2

Hans-Peter Waldl3, Christian Wichmann3

1 INESC Porto, Portugal

2 REN, Portugal

3 Overspeed GmbH & Co. KG, Germany

+


Introduction

Introduction

EWEA Annual Conference, 14-17 March 2011

  • In the ANEMOS.plusEuropean project power system management tools were developed, and are now being demonstrated at several end-users

  • Two of these management tools will be presented (on-going demonstration for REN)

  • Robust Reserve Setting (RRS) tool

    • Objectives: estimation of the operational reserve needs to account for units outages, wind power and load uncertainty

    • Output: reserve levels for each hour of a predefined period (i.e. day-ahead, intraday) obtained with different decision-aid methods

  • Fuzzy Power Flow (FPF) tool

    • Objectives: identify possible voltage violations and branch congestions

    • Output: list of nodes with possible voltage limits violations and branches with possible congestions


  • Reserve and congestion management using wind power probabilistic forecast a real case study

    EWEA Annual Conference, 14-17 March 2011

    Robust Reserve Setting Tool


    Robust reserve setting rrs tool

    Robust Reserve Setting (RRS) Tool

    L: Uncertain Load

    Decision-aid Phase

    (risk vs reserve cost)

    System Gen. Margin Model

    SM=G-L

    Deterministic Multicriteria Problem

    Preferred Operating Reserve Level

    Decision Methods

    Risk Indices

    G: Uncertain Generation

    Probabilistic Model

    Decision Maker

    (REN)

    Demonstration at the Portuguese SO (REN)

    Evaluation

    EWEA Annual Conference, 14-17 March 2011


    Uncertainty modeling

    Uncertainty Modeling

    EWEA Annual Conference, 14-17 March 2011

    • Conventional generation:discrete probability distribution of the possible capacity states (capacity outage probability table, COPT)

    • Load: Gaussian distribution with a given standard deviation and zero mean

    • Wind generation:set of quantiles forecasted by the ANEMOS platform


    System generation margin distribution probabilistic model

    System Generation Margin Distribution (Probabilistic Model)

    upward reserve

    + 700 MW

    LOLP=0.036

    EPNS=5.4 MW

    risk of loss ofload

    LOLP=0.49

    EPNS=157.1 MW

    PWRE=0.037

    EWRE=4.13 MW

    risk of generationsurplus

    PWRE=0.51

    EWRE=129.1 MW

    downward reserve

    - 600 MW

    EWEA Annual Conference, 14-17 March 2011


    Risk reserve or cost curves and decision aid

    Risk/(Reserve or Cost) Curves and Decision-aid

    • Recommended downward reserve

    • Recommended upward reserve

    • max

    • accepted

    • LOLP

    • max

    • accepted

    • PWRE

    EWEA Annual Conference, 14-17 March 2011


    Demonstration case design

    Demonstration Case Design

    Running since 28 Sept 2010

    Hourly Upward and Downward

    Reserve Needs

    Load and

    Special Regime Generation (e.g. mini-hydro, CHP) Forecasts

    7 times per day

    Daily, 6 Intraday Markets

    7 times per day

    Sequential Market

    RRS

    (ANEMOS.plus)

    Upscaled Probabilistic WPF

    Market Dispatch and

    Interconnection Levels

    4 GW

    4 times per day

    (ANEMOS)

    7 times per day

    Daily, 6 Intraday Markets

    EWEA Annual Conference, 14-17 March 2011


    Output results upward reserve

    Output Results (Upward Reserve)

    LOLP=0.1%

    EWEA Annual Conference, 14-17 March 2011


    Upward reserve results oct feb 4 months

    Upward Reserve Results (Oct-Feb, 4 Months)

    Reliability (or calibration) of probabilistic forecasts is the key requirement

    Sharpness is important, but it is not the critical factor

    EWEA Annual Conference, 14-17 March 2011


    Reserve and congestion management using wind power probabilistic forecast a real case study

    EWEA Annual Conference, 14-17 March 2011

    Fuzzy Power Flow Tool


    Fuzzy power flow fpf

    Fuzzy Power Flow (FPF)

    Load about 50 MW

    Load more or less between 30 and 40 MW

    Load between 15 and 30 MW

    EWEA Annual Conference, 14-17 March 2011

    • Fuzzy numbers for generation and load (active and reactive)

    • The midpoint is computed by the deterministic AC power flow

    • The FPF consists of a linearization step and a non-iterative algorithm to deal with uncertainties

    • Output data

      • e.g. fuzzy node voltages’ magnitudes and angles; fuzzy active and reactive power flows; fuzzy active and reactive losses and currents


    Demonstration case design1

    Demonstration Case Design

    Running since 25 Oct 2010

    Deterministic AC Power

    Flow

    Network physical

    data

    Transmission Network of Portugal

    1 time per day and for 24 hours

    AC Fuzzy Power

    Flow (ANEMOS.plus)

    Conventional generation

    and load for day D+1

    1 time per day and for 24 hours of the next day

    Fuzzy sets

    Voltage module and phase

    P and Q power flows

    Active losses

    1 time per day and for 24 hours

    Transformation of

    WPF uncertainty

    into fuzzy sets

    Deterministic and

    probabilistic WPF for D+1

    (ANEMOS)

    forecast launched at 6AM

    38 Wind farms

    6 network nodes

    ~2 GW

    Q5%

    Q95%

    Point Forecast

    EWEA Annual Conference, 14-17 March 2011


    Output information

    Output Information

    Severity of the congestion

    EWEA Annual Conference, 14-17 March 2011

    List of possible bus voltage violations and branch congestion

    Voltage violation: >1.05 pu and <0.95 pu

    Congestion: greater than line limit power

    Severity index of the congestion and voltage violation (in %)


    Output results

    Output Results

    EWEA Annual Conference, 14-17 March 2011

    • Possibility of overvoltage situations in two nodes at 9PM 31 Oct

      • Possibility of network congestions in two lines on 31 Oct at 9PM


    Output results1

    Output Results

    31 Oct 2010

    31 network congestion along this day

    EWEA Annual Conference, 14-17 March 2011

    27 Oct 2010

    0 network congestion along this day


    Conclusions

    Conclusions

    EWEA Annual Conference, 14-17 March 2011

    • The tools were developed according to the end-users prerequisites and necessities

  • Robust reserve setting tool

    • avoids making assumptions on the errors distributions

    • defines the reserve dynamically

    • models different attitudes and values of the decision-maker

  • Fuzzy power flow tool

    • allows the inclusion of probabilistic WPF in day-ahead security evaluation

    • contribute to identify weak points of the transmission network during operational phases

    • Next step: quantitative and qualitative evaluation results for the whole demonstration period (until June 2011)


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