1. ENERGY MANAGEMENT SYSTEM Overview November 18, 2015 Dr Shekhar KELAPURE PSTI, Bangalore

2. What we cover Load Dispatch Why EMS What is EMS Components of EMS Network Applications Framework State Estimator Power Flow & Optimal Power Flow Contingency Analysis Load Forecast Dr Shekhar Kelapure 2 What we do NOT cover Generation Applications Fault Analysis

3. Load Dispatch Objective -> Operate/Drive the Power System so that it is Stable Reliable Secure OPTIMAL Operate Power System “Efficiently” What’s so big 3 Dr Shekhar Kelapure

4. Why Energy Management System (EMS)? What is expected from the “Dispatcher”? Stable/reliable/secure and optimal “Operation” What the “Dispatcher” need to know? Complete knowledge about the system (Parameters and models of the System components) And Knowledge of the Situation – “Situation Awareness” (Real – Time data of the system) EMS – Mechanism to capture “system knowledge” and “situation awareness” And provide key indicators 4 Dr Shekhar Kelapure

5. Mechanism to hold the system knowledge Mechanism to capture real time data (meas) Analog measurements (P, Q, V, F, “  ”  Digital measurements (Status - CBs etc) Validate the measurements Analyze system performance using software programs and provide “key indicators” Display data/measurements on “meaningful” displays Send control commands to operate the system “efficiently” What is Energy Management System? 5 Dr Shekhar Kelapure

6. Databases Components of EMS Presentation Layer (DISPLAYS) Presentation Layer (DISPLAYS) Automatic Generation Control Economic Dispatch Reserve/Cost Monitoring Unit Commitment/ Scheduling Data Validation (State estimator) Power Flow Optimal Power Flow Contingency Analysis Fault Analysis Data Acquisition (SCADA) Load Forecast 6 Network ApplicationGeneration Application Data Layer

7. Network Application Functions Objective – Analyze Power System performance from network (transmission and generation) perspective To check Base case violations Optimal performance (Loss Minimization etc.) Security Assessment & Enhancement Fault Analysis What we need – “GOOD” measurements – Load, Gen, Flows info. Transmission System Data – Capacities, R, X, B, Tap etc Generation Data – Ratings & other parameters 7 Dr Shekhar Kelapure

8. NA Functions – used in EMS State Estimator To identify Anomalies Power Flow & Optimal Power Flow To carry out simulations To get optimal set-points Contingency Analysis What if Analysis (N-1, N-2 etc) Security Assessment and Enhancement Assessment and corrective actions Load Forecast – Input to Simulations (NA functions) 8 Dr Shekhar Kelapure

9. Objective : Filter out Dead system components Establish connectivity information and Define the LIVE(Energized) network with Inputs : System Components Details, Switch Statuses and the Measurements (V, Power Flows, injections etc) Output : Live(energized) network details Formation of networks (Island wise) Mark viable islands (with Generation) Network Topology 9 Dr Shekhar Kelapure

10. COMPONENT DETAILS GEN1 BUS1 GEN2 BUS2 GEN3 BUS3 SYNCON1 BUS6 SYNCON2 BUS8 TRANS1 BUS5 BUS6 TRANS2 BUS4 BUS9 LINE1 BUS1 BUS2 LINE2 BUS1 BUS5 LINE3 BUS2 BUS3 Network Topology Formation SWITCH DETAILS BUS1CB1 BUS1CB2 BUS1CB3 BUS1CB4 BUS2CB1 BUS2CB2 BUS2CB3 10 Dr Shekhar Kelapure

11. Network Topology – Node Terminology Secondary bus Primary bus Bus Couplers Incomer #2 Incomer #1 Outgoing #1 Outgoing #2 Nodes with Unique ID 11 Dr Shekhar Kelapure

12. 1.06  0.00 2.32 - j 0.17 1.045  -4.98 0.183 + j 0.295 1.055  -15.67 -0.061 - j 0.016 1.05  -15.73 -0.135 - j 0.058 1.035  -16.47 -0.149 - j 0.056 1.057  -15.3 -0.035 - j 0.018 1.052  -15.51 -0.09 - j 0.058 1.01  -12.73 -0.942 + j 0.44 1.021  -8.77 -0.076 - j 0.018 1.07  -14.83 -0.112 + j 0.068 1.09  -13.66 00 + j.172 1.02  -10.34 -0.478 + j 0.039 1.057  -15.3 -0.295 - j 0.166 1.57-j0.17 -1.53+j0.31 0.56-j0.003 0.73+j0.06 0.42+j0.02 -0.40+j0.003 -0.73+j0.053 0.63-j0.14 0.75+j0.06 -0.62+j0.16 -0.55+j0.054 0.24-j0.36 -0.23+j0.045 -0.71+j0.038 0.16-j0.003 -0.17+j0.017 0.077-j0.026 -0.076-j0.025 0.015+j0.01 0.17+j0.075 -0.17-j0.08 -0.015-j0.01 0.051+ j0.02 0.065+j0.038 DIGITAL DATA BUS1CB1 CLOSE BUS1CB2 OPEN BUS1CB3 CLOSE BUS1CB4 CLOSE BUS2CB1 CLOSE BUS2CB2 CLOSE BUS2CB3 OPEN BUS2CB4 CLOSE BUS2CB5 CLOSE BUS2CB6 CLOSE BUS2CB7 OPEN BUS3CB1 OPEN ANALOG DATA P, Q FLOWS GENERATIONS VOLTAGES (ANGLES?) FREQUENCY Real-Time Data superimposed on Line Network 12 Dr Shekhar Kelapure

13. CONNECTIVITY INFO ISLAND #1 GEN1 BUS1 GEN2 BUS2 GEN3 BUS3 SYNCON2 BUS8 TRANS1 BUS5 BUS6 TRANS2 BUS4 BUS9 LINE1 BUS1 BUS2 LINE2 BUS1 BUS5 LINE3 BUS2 BUS4 ISLAND #2 LOAD12 BUS12 Network Topology - Output 13 Dr Shekhar Kelapure

14. Objective : Identify and correct Anomalies, Suppress Bad data Refine the measurement set to form the State of the system Inputs : Energized System Components Details (Connectivity + Parameters) Switch Statuses (CBs, ISOs) Measurements (V, Power Flows, Loads, Generations) Tuning Parameters (Tolerances, Statistical Info etc) Output : Estimated complex voltages, Estimated P and Q injections and flows Error Analysis, List of Bad Data Methodology : Weighted Least Square (WLS) State Estimation 14 Dr Shekhar Kelapure

15. State Estimator Refine Measurements System Info, Measurements and switch statuses Network Topology NO Observable? Add Pseudo Measurements Print results Voltage profile Loads and Generations Real/ reactive flows Meas Vs Estimates Bad Data Processing Identify/suppress bad data  acceptable? YES NO State Estimator (SE) – Data Flow 15 Dr Shekhar Kelapure

16. Measurements Bus Voltages Magnitudes (V) and Angles Generations (P gen and Q gen ) and Loads (P L and Q L ) Flows(real and reactive) at either end of lines/ transformer Size – 4 x Nlines(Flows) + Nbus (V) + Ngen (Gen) Output State variables (complex voltages at all buses – 2 x NBUS) ? How many measurements are required? More measurements – slower the estimation process Less Measurements – erroneous results (poor estimation) Optimum - 1.5 to 2.8 times the state variables Measurements 16 Dr Shekhar Kelapure

17. 1.06 2.32 - j 0.17 1.045 0.183 + j 0.295 1.055 -0.061 - j 0.016 1.05 -0.135 - j 0.058 1.035 -0.149 - j 0.056 1.057 -0.035 - j 0.018 1.052 -0.09 - j 0.058 1.01 -0.942 + j 0.44 1.021 -0.076 - j 0.018 1.07 -0.112 + j 0.068 1.09 00 + j.172 1.02 -0.478 + j 0.039 1.057 -0.295 - j 0.166 1.57-j0.17 -1.53+j0.31 0.56-j0.003 0.73+j0.06 0.42+j0.02 -0.40+j0.003 -0.43+j0.053 0.63-j0.14 0.75+j0.06 -0.62+j0.16 -0.55+j0.054 0.24-j0.360 0.23+j0.045 0+j0 0.16-j0.003 -0.17+j0.017 0+-j0 0+j0 0.0+j0.0 0.17+j0.075 -0.17-j0.08 2.32 - j 0.17 0.0+j0.0 0.051+ j0.02 0.065+j0.038 INCONSISTANCIES FLOWS P15 AND P51 P23 AND P32 Q34 AND Q43 LOADS P12 Q12 V12 Identify Measurement Errors 17 Dr Shekhar Kelapure

18. 1.06 2.32 - j 0.17 1.045 0.183 + j 0.295 0.0 -0.0 - j 0.0 1.05 -0.135 - j 0.058 1.035 -0.149 - j 0.056 1.057 -0.035 - j 0.018 1.052 -0.09 - j 0.058 1.01 -0.942 + j 0.44 1.021 -0.076 - j 0.018 1.07 -0.112 + j 0.068 1.09 00 + j.172 1.02 -0.478 + j 0.039 1.057 -0.295 - j 0.166 1.57-j0.17 -1.53+j0.31 0.56-j0.003 0.+j0.0 0.42+j0.02 -0.40+j0.003 -0.43+j0.053 0.63-j0.14 0.75+j0.06 -0.62+j0.16 -0.55+j0.054 0.24-j0.360 0.23+j0.045 0+j0 0.16-j0.003 -0.17+j0.017 0+-j0 0+j0 0.0+j0.0 0.17+j0.075 -0.17-j0.08 2.32 - j 0.17 0.0+j0.0 0.051+ j0.02 0.065+j0.038 Suppress Erroneous Measurements REMOVE INCONSISTANCIES SUPRESS P51 P23 Q34 LOADS P12 = 0.0 Q12 = 0.0 V12 = 0.0 IGNORE OR REPLACE WITH APPROPRIATE VALUES 18 Dr Shekhar Kelapure

19. 1.06 2.32 - j 0.17 1.045 0.183 + j 0.295 0.0 -0.0 - j 0.0 1.05 -0.135 - j 0.058 1.035 -0.149 - j 0.056 1.01 -0.942 + j 0.44 1.021 -0.076 - j 0.018 1.07 -0.112 + j 0.068 1.09 00 + j.172 1.02 -0.478 + j 0.039 1.057 -0.295 - j 0.166 1.57-j0.17 -1.53+j0.31 0.56-j0.003 0.+j0.0 0.42+j0.02 -0.40+j0.003 -0.43+j0.053 0.63-j0.14 0.75+j0.06 -0.62+j0.16 -0.55+j0.054 0.24-j0.360 0.23+j0.045 0+j0 0.16-j0.003 -0.17+j0.017 0+-j0 0+j0 0.0+j0.0 0.17+j0.075 -0.17-j0.08 0.0+j0.0 0.051+ j0.02 0.065+j0.038 1.057 -0.035 - j 0.018 1.052 -0.09 - j 0.058 Check Observability UNOBSERVABLE - Enable to estimate due to insufficient measurements “Calculations beyond the reach of available measurements” OBSERVABILITY Insufficient Measurements @ BUS10 and BUS11 ??WHAT TO DO??- - - - - - - - - - - - - - - - - - - - ADD PSUEDO MEASUREMENTS 19 Dr Shekhar Kelapure

20. 1.06  0.00 2.32 - j 0.17 1.044  -4.98 0.183 + j 0.295 0.0 -0.0 - j 0.0 1.05  -15.73 -0.135 - j 0.058 1.035  -16.47 -0.149 - j 0.056 1.057  -15.3 -0.035 - j 0.018 1.052  -15.51 -0.09 - j 0.058 1.012  -12.73 -0.942 + j 0.44 1.023  -8.77 -0.076 - j 0.018 1.07  -14.83 -0.112 + j 0.068 1.09  -13.66 00 + j.172 1.02  -10.34 -0.478 + j 0.039 1.057  -15.3 -0.295 - j 0.166 1.56-j0.17 -1.52+j0.31 0.56-j0.003 0.+j0.0 0.41+j0.02 -0.38+j0.003 -0.63+j0.053 0.61-j0.14 0.65+j0.06 -0.59+j0.16 -0.55+j0.054 0.18-j0.360 -0.17+j0.045 0+j0 0.18-j0.003 -0.17+j0.017 0+-j0 0+j0 0.0+j0.0 0.17+j0.075 -0.17-j0.08 0.0+j0.0 0.051+ j0.02 0.065+j0.038 ESTIMATES : Voltages 1 1.060  0.00 1 1.044  -4.980 1 1.012  -12.73 1 1.020  -10.34 Power Flows 1 2 1.56 –0.170 1 5 0.65 +0.060 2 1 –1.52 +0.31 2 4 0.55 –0.003 2 5 0.41 +0.020 Estimation Output 20 Dr Shekhar Kelapure

21. IDENTIFY BAD DATA Voltages Measu Estimat 1 1.060 1.060 2 1.045 1.044 3 1.010 1.012 4 1.020 1.0204 Power Flows Meas Estimat 1 2 1.57 1.56 1 5 0.75 0.65 2 1 –1.53 –1.52 2 4 0.56 0.55 2 5 0.42 0.41 1.06  0.00 2.32 - j 0.17 1.044  -4.98 0.183 + j 0.295 0.0 -0.0 - j 0.0 1.05  -15.73 -0.135 - j 0.058 1.035  -16.47 -0.149 - j 0.056 1.057  -15.3 -0.035 - j 0.018 1.052  -15.51 -0.09 - j 0.058 1.012  -12.73 -0.942 + j 0.44 1.023  -8.77 -0.076 - j 0.018 1.07  -14.83 -0.112 + j 0.068 1.09  -13.66 00 + j.172 1.02  -10.34 -0.478 + j 0.039 1.057  -15.3 -0.295 - j 0.166 1.56-j0.17 -1.52+j0.31 0.56-j0.003 0.+j0.0 0.41+j0.02 -0.38+j0.003 -0.63+j0.053 0.61-j0.14 0.65+j0.06 -0.59+j0.16 -0.55+j0.054 0.18-j0.360 -0.17+j0.045 0+j0 0.18-j0.003 -0.17+j0.017 0+-j0 0+j0 0.0+j0.0 0.17+j0.075 -0.17-j0.08 0.0+j0.0 0.051+ j0.02 0.065+j0.038 Bad Data Identification 21 Dr Shekhar Kelapure

22. 1.06  0.00 2.32 - j 0.17 1.045  -4.98 0.183 + j 0.295 1.055  -15.67 -0.061 - j 0.016 1.05  -15.73 -0.135 - j 0.058 1.035  -16.47 -0.149 - j 0.056 1.057  -15.3 -0.035 - j 0.018 1.052  -15.51 -0.09 - j 0.058 1.01  -12.73 -0.942 + j 0.44 1.021  -8.77 -0.076 - j 0.018 1.07  -14.83 -0.112 + j 0.068 1.09  -13.66 00 + j.172 1.02  -10.34 -0.478 + j 0.039 1.057  -15.3 -0.295 - j 0.166 1.57-j0.17 -1.53+j0.31 0.56-j0.003 0.73+j0.06 0.42+j0.02 -0.40+j0.003 -0.73+j0.053 0.63-j0.14 0.75+j0.06 -0.62+j0.16 -0.55+j0.054 0.24-j0.36 -0.23+j0.045 -0.71+j0.038 0.16-j0.003 -0.17+j0.017 0.077-j0.026 -0.076-j0.025 0.015+j0.01 0.17+j0.075 -0.17-j0.08 -0.015-j0.01 0.051+ j0.02 0.065+j0.038 OMIT BAD MEAS Power Flows Meas Estimat 1 5 0.75 0.65 5 1 –0.43 -0.63 Bad Data Suppression 22 Dr Shekhar Kelapure

23. 1.06  0.00 2.32 - j 0.17 1.045  -4.98 0.183 + j 0.295 1.055  -15.67 -0.061 - j 0.016 1.05  -15.73 -0.135 - j 0.058 1.035  -16.47 -0.149 - j 0.056 1.057  -15.3 -0.035 - j 0.018 1.052  -15.51 -0.09 - j 0.058 1.01  -12.73 -0.942 + j 0.44 1.021  -8.77 -0.076 - j 0.018 1.07  -14.83 -0.112 + j 0.068 1.09  -13.66 00 + j.172 1.02  -10.34 -0.478 + j 0.039 1.057  -15.3 -0.295 - j 0.166 1.57-j0.17 -1.53+j0.31 0.56-j0.003 0.73+j0.06 0.42+j0.02 -0.40+j0.003 -0.73+j0.053 0.63-j0.14 0.75+j0.06 -0.62+j0.16 -0.55+j0.054 0.24-j0.36 -0.23+j0.045 -0.71+j0.038 0.16-j0.003 -0.17+j0.017 0.077-j0.026 -0.076-j0.025 0.015+j0.01 0.17+j0.075 -0.17-j0.08 -0.015-j0.01 0.051+ j0.02 0.065+j0.038 Final Estimation This becomes the “base case” for the remaining Network Analysis Functions 23 Dr Shekhar Kelapure

24. Objective : To compute the power flow in the branches thru the complex voltages for given load/ generation profile Inputs : system information component parameters and connectivity load and generation profile, voltage set-points output : voltage profile (voltage magnitude and angles) power flow calculations loss calculation violations (voltage magnitude and power flows) “MODELLING IS CRUCIAL” Power Flow 24 Dr Shekhar Kelapure

25. Kirchhoff’s current Law Power Injection at i th bus S i = V i x I i * ?? Set of Simultaneous Non-linear equations ?? Gauss Seidel (only for very small systems) Newton Raphson (Normally used) Fast Decoupled (Modified Newton Raphson) ViVi i th bus To bus 1 V 1 To bus j V j To bus k V k Y ii Y ij Y i1 Y ik Power Flow – Basic equations 25 Dr Shekhar Kelapure

26. Non-linear eqns Linearize & solve Iteratively Characteristics Quadratic Convergence Normally 3-5 iterations Reliable Difficulty - Handling Large Matrices Newton Raphson based Power Flow What’s way out?Try de-coupling ?FDLF? Assumptions 1. |V| ~ 1.0 p.u. Bus angle  ) very small 2. Sin(  )=0 3. Cos(  )=1 4. R << X 26 Dr Shekhar Kelapure

27. OUTPUT SLK – P gen, Q gen PV - δ, Qgen PQ - δ, |V| In addition Branch P flow, Q flow LOSSES P L, Q L SHUNT POWER Power Flow, Inputs and Output INPUTS System DATA LINE DETAILS(RXB) XMER DETAILS(RXT) GENERATOR DATA(QLT) SHUNT DATA(B) LOAD/GEN DATA LOAD DATA GENERATION DATA(PV) TUNING PARAMETERS 27 Dr Shekhar Kelapure

28. 08/19/93 UW ARCHIVE 100.0 1962 W IEEE 14 Bus Test Case BUS DATA FOLLOWS 14 ITEMS 1 Bus 1 HV 1 1 3 1.060 0.0 0.0 0.0 232.4 -16.9 0.0 1.060 0.0 0.0 0.0 0.0 0 2 Bus 2 HV 1 1 2 1.045 -4.98 21.7 12.7 40.0 42.4 0.0 1.045 50.0 -40.0 0.0 0.0 0 3 Bus 3 HV 1 1 2 1.010 -12.72 94.2 19.0 0.0 23.4 0.0 1.010 40.0 0.0 0.0 0.0 0 4 Bus 4 HV 1 1 0 1.019 -10.33 47.8 -3.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 5 Bus 5 HV 1 1 0 1.020 -8.78 7.6 1.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 6 Bus 6 LV 1 1 2 1.070 -14.22 11.2 7.5 0.0 12.2 0.0 1.070 24.0 -6.0 0.0 0.0 0 7 Bus 7 ZV 1 1 0 1.062 -13.37 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 8 Bus 8 TV 1 1 2 1.090 -13.36 0.0 0.0 0.0 17.4 0.0 1.090 24.0 -6.0 0.0 0.0 0 9 Bus 9 LV 1 1 0 1.056 -14.94 29.5 16.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.19 0 10 Bus 10 LV 1 1 0 1.051 -15.10 9.0 5.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0 -999 BRANCH DATA FOLLOWS 20 ITEMS 1 2 1 1 1 0 0.01938 0.05917 0.0528 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1 5 1 1 1 0 0.05403 0.22304 0.0492 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2 3 1 1 1 0 0.04699 0.19797 0.0438 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2 4 1 1 1 0 0.05811 0.17632 0.0340 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2 5 1 1 1 0 0.05695 0.17388 0.0346 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3 4 1 1 1 0 0.06701 0.17103 0.0128 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4 5 1 1 1 0 0.01335 0.04211 0.0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4 7 1 1 1 0 0.0 0.20912 0.0 0 0 0 0 0 0.978 0.0 0.0 0.0 0.0 0.0 0.0 4 9 1 1 1 0 0.0 0.55618 0.0 0 0 0 0 0 0.969 0.0 0.0 0.0 0.0 0.0 0.0 5 6 1 1 1 0 0.0 0.25202 0.0 0 0 0 0 0 0.932 0.0 0.0 0.0 0.0 0.0 0.0 6 11 1 1 1 0 0.09498 0.19890 0.0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6 12 1 1 1 0 0.12291 0.25581 0.0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6 13 1 1 1 0 0.06615 0.13027 0.0 0 0 0 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -999 END OF DATA IEEE Format 28 Dr Shekhar Kelapure

29. BUS WISE RESULTS IN TABULATED FORM sr_no bus_no v_mag v_angle(rad) p_inj q_inj 1 1 1.0600.0000 2.3238 -.1707 2 2 1.0450 -.0870.1830.2950 3 3 1.0100 -.2221 -.9420.0440 4 4 1.0700 -.2589 -.1120.0682 5 5 1.0900 -.2385.0000.1716 6 6 1.0186 -.1805 -.4780.0390 7 7 1.0623 -.2385.0000.0000 8 8 1.0207 -.1532 -.0760 -.0180 9 9 1.0567 -.2673 -.2950 -.1660 10 10 1.0517 -.2708 -.0900 -.0580 11 11 1.0573 -.2671 -.0350 -.0180 12 12 1.0551 -.2735 -.0610 -.0160 13 13 1.0503 -.2745 -.1350 -.0580 14 14 1.0351 -.2875 -.1490 -.0560 ********************************************************** BUS WISE DETAILED RESULTS results for bus number 1 voltage(pu) 1.0600 angle(deg) -.0001 flow to (MW/MVAr) 2 1.5689 -.1744 flow to (MW/MVAr) 8.7549.0610 line charging (MVAr) -.0573 shunt injection (MVAr).0000 Injections P/Q (MW/MVAr) 2.3238 -.1707 **************************************************************** results for bus number 2 voltage(pu) 1.0450 angle(deg) -4.9830 flow to (MW/MVAr) 1 -1.5259.3056 flow to (MW/MVAr) 3.7325.0595 flow to (MW/MVAr) 6.5629 -.0027 flow to (MW/MVAr) 8.4136.0243 line charging (MVAr) -.0917 shunt injection (MVAr).0000 Injections P/Q (MW/MVAr).1830.2950 **************************************************************** Power Flow Results SUMMARY ******************************************************** total generation P/Q (MW/MVAr) 2.5068.4081 total load P/Q (MW/MVAr) -2.3730 -.3510 system losses P/Q (MW/MVAr) -.1339 -.5522 total charging (MVAr).2830 total shunt power (MVAr).2122 ******************************************************** OR You can print them in “IEEE Format” exactly same as input So that other programs can read it easily 29 Dr Shekhar Kelapure

30. Objective : Optimize the system parameters for better performance Inputs : System information (parameters & connectivity) load and generation profile, set-points(V, t, MW) component modeling and constraints Output : Voltage profile (voltage magnitude and angles) Optimized power flow calculations Violations (V, MW, MVAr) – remaining Major difficulty : Getting well-behaved objective function and constraints as function of control variables Optimal Power Flow 30 Dr Shekhar Kelapure

31. Objective : Minimize P LOSS or Overload Alleviations Subject to : Satisfaction of load flow equations (Power Balance) Limits on the control variables (set-points) Limits on line/transformer loading Maintain Load Generation Balance Control Variables : Real Power Controls : MW Gen, Tie-Line Flows, HVDC/FACTS set-points Reactive Power Controls Generator voltage set-points VAr resources (Capacitors, Reactors, SVCs, Syn. condensers) Transformer taps HIGHLY NON-LINEAR PROBLEM – Solved using Gradient, SLP or any other method Problem Formulation 31 Dr Shekhar Kelapure

32. LOSS REDUCTION REAL POWER LOSSES (UNOPTIMISED) BSH_14=0.0 0.2893 p.u. 1.06  0.00 3.36 + j 0.41 1.015  -6.99 0.256 + j 0.322 0.98  -23.6 -0.085 - j 0.022 0.97  -23.7 -0.189 - j 0.0812 0.94  -24.88 -0.209 - j 0.078 0.983  -23.0 -0.049 - j 0.025 0.97  -23.3 -0.126 - j 0.0812 0.96  -18.88 -1.319 + j 0.134 0.97  -12.67 -0.106 - j 0.025 1.0  -22.27 -0.15 + j 0.13 1.037  -20.28 00 + j.24 0.96  -15.03 -0.67 + j 0.054 1.057  -15.3 -0.295 - j 0.166 2.28+j0.19 -2.18+j0.08 0.80+j0.08 1.05+j0.15 0.59+j0.09 -0.57-j0.03 -1.02-j0.03 0.88-j0.10 1.08+j0.27 -0.87+j0.14 -0.77+j0.028 0.33-j0.08 -0.32+j0.10 -0.99+j0.065 0.226+j0.041 -0.23-j0.01 0.11+j0.039 -0.107-j0.036 0.022+j0.013 0.247+j0.11 -0.24-j0.104 -0.07 - j 0.03 -0.022-j0.013 0.073+ j0.036 0.091+j0.062 BSH_14 = 0.00 C Power Flow Base case 32 Dr Shekhar Kelapure

33. LOSS REDUCTION REAL POWER LOSSES (UNOPTIMISED) BSH_14=0.0 0.2893 p.u. REAL POWER LOSSES (OPTIMISED) BSH_14=0.05 0.2854 p.u. Loss Reduction 1.35% 1.06  0.00 3.35 + j 0.34 1.018  -7.01 0.256 + j 0.322 0.995  -23.42 -0.085 - j 0.022 0.99  -23.54 -0.189 - j 0.0812 0.97  -24.86 -0.209 - j 0.078 0.997  -22.8 -0.049 - j 0.025 0.99  -23.1 -0.126 - j 0.0812 0.96  -18.82 -1.319 + j 0.134 0.98  -12.68 -0.106 - j 0.025 1.02  -22.09 -0.16 + j 0.13 1.048  -20.18 00 + j.24 0.97  -15.02 -0.67 + j 0.054 1.057  -15.3 -0.295 - j 0.166 2.27+j0.15 -2.18+j0.13 0.80+j0.07 1.04+j0.14 0.59+j0.08 -0.57-j0.018 -1.02-j0.006 0.88-j0.12 1.08+j0.25 -0.87+j0.14 -0.77+j0.045 0.33-j0.08 -0.32+j0.10 -0.99+j0.073 0.226+j0.028 -0.23-j0.003 0.10+j0.035 -0.106-j0.032 0.021+j0.009 0.244+j0.098 -0.24-j0.09 -0.07 - j 0.03 -0.021-j0.009 0.072+ j0.017 0.091+j0.061 C BSH_14 = 0.05 OPF – Loss Minimization 33 Dr Shekhar Kelapure

34. 1.06  0.00 2.90 + j 0.28 1.025  -5.82 0.68 + j 0.322 0.992  -22.42 -0.085 - j 0.022 0.98  -22.5 -0.189 - j 0.0812 0.97  -24.86 -0.209 - j 0.078 0.994  -21.8 -0.049 - j 0.025 0.98  -22.1 -0.126 - j 0.0812 0.97  -17.61 -1.319 + j 0.134 0.98  -11.72 -0.106 - j 0.025 1.014  -21.11 -0.16 + j 0.13 1.048  -19.12 00 + j.24 0.97  -13.95 -0.67 + j 0.054 1.00  -21.73 -0.413 - j 0.232 1.897+j0.104 -1.835+j0.086 0.83+j0.083 1.059+j0.148 0.62+j0.09 -0.60-j0.027 -0.952-j0.026 0.85-j0.11 1.00+j0.24 -0.84+j0.14 -0.79+j0.033 0.32-j0.08 -0.31+j0.10 -1.01+j0.068 0.23+j0.039 -0.23-j0.008 0.11+j0.039 -0.107-j0.036 0.022+j0.013 0.244+j0.113 -0.24-j0.10 -0.07 - j 0.03 -0.021-j0.013 0.072+ j0.036 0.090+j0.062 Overload Min REAL POWER FLOWS (UNOPTIMISED) 1 2 2.27 1 5 1.08 G1 = 3.35 G2 = 0.256 REAL POWER FLOWS (OPTIMISED) 1 2 1.897 1 5 1.00 G1 = 2.90 G2 = 0.68 OPF – Overload Alleviation 34 Dr Shekhar Kelapure

35. 1.06  0.00 3.35 + j 0.34 1.018  -7.01 0.256 + j 0.322 0.995  -23.42 -0.085 - j 0.022 0.99  -23.54 -0.189 - j 0.0812 0.97  -24.86 -0.209 - j 0.078 0.997  -22.8 -0.049 - j 0.025 0.99  -23.1 -0.126 - j 0.0812 0.96  -18.82 -1.319 + j 0.134 0.98  -12.68 -0.106 - j 0.025 1.02  -22.09 -0.16 + j 0.13 1.048  -20.18 00 + j.24 0.97  -15.02 -0.67 + j 0.054 1.057  -15.3 -0.295 - j 0.166 2.27+j0.15 -2.18+j0.13 0.80+j0.07 1.04+j0.14 0.59+j0.08 -0.57-j0.018 -1.02-j0.006 0.88-j0.12 1.08+j0.25 -0.87+j0.14 -0.77+j0.045 0.33-j0.08 -0.32+j0.10 -0.99+j0.073 0.226+j0.028 -0.23-j0.003 0.10+j0.035 -0.106-j0.032 0.021+j0.009 0.244+j0.098 -0.24-j0.09 -0.07 - j 0.03 -0.021-j0.009 0.072+ j0.017 0.091+j0.061 C BSH_14 = 0.05 Voltage Alleviation Voltage V_14 (UNOPTIMISED) BSH_14=0.0 0.94 p.u. Voltage V_14 (OPTIMISED) BSH_14=0.05 0.97 p.u. OPF – Voltage Alleviation 35 Dr Shekhar Kelapure

36. Objective : Evaluation of the system performance under outages Inputs : System information (Parameters and connectivity info) Load and generation profile, voltage set-points Component modeling, Rating of the equipment Output : List of CRITICAL contingencies leading to violations Approach : Approximate simulation Contingency Analysis 36 Dr Shekhar Kelapure

37. Ranking (Based on Per. Indices) System Information and Base Case State Estimator Print results Ranking List Power Flow results for Top ranked outages Analysis Full Evaluation of Severe Outages List of credible outages (having more probability of occurrence) Efficient Screening Contingency Analysis – Flow Chart 37 Dr Shekhar Kelapure

38. Possible outages : All lines, transformers, generators, shunts, loads For 14 bus sample system, Total number of single component outages 17 lines + 3 transformers + 2 generators + 3 shunts TOTAL = 25 + (?multiple outages?) WHAT IF the System size is 1000 buses? Challenge : 1500 AC load flow simulations of 1000 bus system Take considerable time Contingency Analysis – possible contingencies 38 Dr Shekhar Kelapure

39. Filtering/Screening Criteria 1. Probability of occurrence 2. Use of approx. analysis like Power flow with less tolerance Power flow – 1 iteration, esp. for overload analysis Network equivalents (outage impact - local) Ranking SEVERE contingencies based on performance indices - overload index - voltage index Full AC power flow analysis for top ranked contingencies Processing Approach 1500 150 15 Possible CTGs Credible CTGs Severe CTGs 39 Dr Shekhar Kelapure

40. Normally used performance Indices - overload index - voltage index - Based on Type of limit violated and % violations Index = 1000 x Type of limit violated + (100 + %violation) e.g. Emergency limit violated by 12% Index = 2112 Severity Indices Limits Type 1 – Normal 2 – Emergency 3 – LoadShed 40 Dr Shekhar Kelapure

41. 1.06  0.00 2.32 - j 0.17 1.045  -4.98 0.183 + j 0.295 1.055  -15.67 -0.061 - j 0.016 1.05  -15.73 -0.135 - j 0.058 1.035  -16.47 -0.149 - j 0.056 1.057  -15.3 -0.035 - j 0.018 1.052  -15.51 -0.09 - j 0.058 1.01  -12.73 -0.942 + j 0.44 1.021  -8.77 -0.076 - j 0.018 1.07  -14.83 -0.112 + j 0.068 1.09  -13.66 00 + j.172 1.02  -10.34 -0.478 + j 0.039 1.057  -15.3 -0.295 - j 0.166 1.57-j0.17 -1.53+j0.31 0.56-j0.003 0.73+j0.06 0.42+j0.02 -0.40+j0.003 -0.73+j0.053 0.63-j0.14 0.75+j0.06 -0.62+j0.16 -0.55+j0.054 0.24-j0.36 -0.23+j0.045 -0.71+j0.038 0.16-j0.003 -0.17+j0.017 0.077-j0.026 -0.076-j0.025 0.015+j0.01 0.17+j0.075 -0.17-j0.08 -0.015-j0.01 0.051+ j0.02 0.065+j0.038 Base Case Power Flow Results 41 Dr Shekhar Kelapure

42. 1.06  0.00 2.75 - j 0.13 1.025  -5.91 -0.217 - j 0.127 1.055  -16.67 -0.061 - j 0.016 1.05  -16.73 -0.135 - j 0.058 1.033  -17.47 -0.149 - j 0.056 1.056  -16.3 -0.035 - j 0.018 1.05  -16.51 -0.09 - j 0.058 1.01  -14.00 -0.942 + j 0.20 1.012  -9.66 -0.076 - j 0.018 1.07  -15.84 -0.112 + j 0.113 1.09  -14.67 00 + j.194 1.01  -11.34 -0.478 + j 0.039 1.053  -16.3 -0.295 - j 0.166 1.92+j0.09 -1.86+j0.10 0.53-j0.065 0.726-j0.04 0.38-j0.036 -0.37+j0.06 -0.80+j0.045 0.66-j0.16 0.83+j0.09 -0.65+j0.18 -0.52+j0.114 0.24-j0.085 -0.24+j0.097 -0.70+j0.14 0.16-j0.011 -0.17+j0.026 0.077+j0.076 -0.0767-j0.025 0.016+j0.01 0.17+j0.078 -0.17-j0.07 -0.016-j0.01 0.053+ j0.03 0.067+j0.044 Example - Generator Outage Dr Shekhar Kelapure

43. 1.06  0.00 2.33 - j 0.10 1.045  -4.49 0.183 + j 0.219 1.055  -17.4 -0.061 - j 0.016 1.05  -17.45 -0.135 - j 0.058 1.034  -18.06 -0.149 - j 0.056 1.056  -16.9 -0.035 - j 0.018 1.05  -17.05 -0.09 - j 0.058 1.01  -13.25 -0.942 + j 0.078 1.011  -10.66 -0.076 - j 0.018 1.07  -16.6 -0.112 + j 0.117 1.09  -15.1 00 + j.187 1.012  -11.66 -0.478 + j 0.039 1.055  -16.8 -0.295 - j 0.166 1.42-j0.14 -1.38+j0.25 0.75-j0.006 0.82+j0.05 0.0+j0.0 -0.87+j0.074 0.38-j0.14 0.91+j0.09 -0.38+j0.15 -0.72+j0.096 0.149-j0.42 -0.148+j0.046 -0.79+j0.072 0.16-j0.003 -0.17+j0.025 0.076-j0.027 -0.0754-j0.026 0.014+j0.01 0.17+j0.079 -0.17-j0.08 -0.046 - j 0.026 -0.014-j0.01 0.046+ j0.03 0.057+j0.046 Example – Line outage 43 Dr Shekhar Kelapure

44. Objective : Evaluate optimal set-points to bring the system back to normal state in post contingency scenario Inputs : System information (Parameters and connectivity info) Load and generation profile, voltage set-points Component modeling and constraints List of severe contingencies output : Post Contingency complex voltage profile (V,  ) Power flow calculations (after implementing optimized controls) Two Approaches: Preventive Action Corrective Action Security Constrained Optimization 44 Dr Shekhar Kelapure

45. Objective : min Overloads OR Voltage excursions subject to :Satisfaction of load flow equations Limits on the control variables (set-points) Maintain Load Generation Balance Minimum deviation in set-points Pre and post outage(each severe outage) constraints Control Variables : 1.Generator voltage setpoints 2.VAr resources (capacitors, reactors, SVCs, syn. condensers) 3.Transformer Taps 4.Generations (MW) 5.Tie-Line Flows, HVDC/FACTs controllers SCO – Preventive Action (PA) 45 Dr Shekhar Kelapure

46. Challenges : Single Big problem Large number of constraints (considering all outages together) Conflicts between constraints May lead to infeasible solution Costly (Contingency may not happen at all) Then WHY? For some severe contingencies, post-outage controls rescheduling may not be possible due to time limitations Preventive Action - Challenges 46 Dr Shekhar Kelapure

47. Objective : min Overloads OR Voltage excursions subject to :Satisfaction of load flow equations Limits on the control variables (set-points) Maintain Load Generation Balance Minimum deviation in set-points Only Post outage constraints for specific contingency Control Variables : 1.Generator voltage setpoints 2.VAr resources (capacitors, reactors, SVCs, syn. condensers) 3.Transformer Taps 4.Generations 5.Tie-Line Flows, HVDC/FACTs controllers SCO – Corrective Action 47 Dr Shekhar Kelapure

48. Advantages : Since occurrence of contingency is NOT certain, keeping post contingency plans ready is better (Preparedness) Separate optimization problem for each outage case Sometimes it may NOT be possible to make changes after outage Challenges : Post contingency scenario – Time is crucial Whether to go for PA/CA? For severe contingencies where the execution of CA is not possible, then check the probability and consequences and implement PA Corrective Action 48 Dr Shekhar Kelapure

49. Load Forecast Objective : To get the accurate forecast of system/ area loads Inputs : Load History (Normally stored from actual SCADA data) Loads are function Weather data Effective weather forecast Weather history data Formula to get derived forecast variable Planning Inputs 49 Dr Shekhar Kelapure

50. Load Forecast Types Short Term: Forecast Load for next hour (for every 5 mins) Forecasting Emergencies in Operations (Real Time) Medium Term Forecast Load for a week (hourly forecast) Normally used in operations (daily planning) Long Term Forecast Load for “>” 1 Year (monthly forecast) Normally used in Planning 50 Dr Shekhar Kelapure

51. Load Forecast Methodologies Regression Technique: Based on Historical load data and weather forecast Similar day forecast Based on the similar weather day in history Load Patterns (Save cases) Saved Load curved in history can be used to forecast With appropriate scaling/shifting etc 51 Dr Shekhar Kelapure

52. Regression Analysis Daily Load Curve : Weekly Load Curve : 52 Dr Shekhar Kelapure

53. Regression Technique Important to Note : Load curved are cyclic in nature over the week (e.g. Load pattern is similar on all Mondays) With appropriate Load growth (say 12% over year) Thus Regression Technique can effectively be used Challenges : Loads are highly dependent on weather (Rains?) Special days (festivals have different load patterns) Planning impact can not be handled 53 Dr Shekhar Kelapure

54. Similar Day Forecast Advantage : Takes care of weather dependencies Procedure : - Get the weather forecast for the selected day - Identify similar weather day in history (closest match) - take it as base load and apply load growth Easy and more accurate for the weather sensitive loads 54 Dr Shekhar Kelapure

55. Load Patterns Advantage : This can handle exceptions i.e. special days like festivals Procedure : - Save the load patterns for the special days - take it as base load and apply load growth Easy and more accurate for the special days loads 55 Dr Shekhar Kelapure

56. Load Forecast Applications Power System Planning As Pseudo Measurements in State Estimator Power Flow Simulation Studies Generation Applications Unit Commitment Hydrothermal Scheduling Maintenance Scheduling Awareness of worst situations and Readiness 56 Dr Shekhar Kelapure

57. Load Forecast - Summary Load Forecast highly dependent on Historical Data Weather Data/ forecast Types of Load Forecast All techniques (regression + similar day + load patterns) need to be effectively used to get better results Other techniques : Artificial Neural Network etc. For Long terms Load Forecasting – Appropriate Load growth and the planning indices are crucial 57 Dr Shekhar Kelapure