Electrical Power and Energy Conference 2012 Resilient Green Energy Systems for a Sustainable Society Particle Swarm Optimization for Voltage Stability Analysis Dinesh Rangana Gurusinghe University of Manitoba, Canada Weerakorn Ongsakul Asian Institute of Technolgy, Thailand 1 October 12, 2012
Outline • Introduction • Objectives • Concept of Particle Swarm Optimization (PSO) • Methodology • Results and Discussion • Conclusion and Recommendations • Areas for Improvements 2
Introduction Voltage collapse point (VCP) : following a disturbance there is a • time where power system voltages become uncontrollable and it is known as VCP An effective approach to determine VCP greatly assists planning • and operation of power system Already establish methods, such as Multiple Power Flow (MPF) • and Continuation Power Flow (CPF) methods provides the accurate VCP but relatively more time consuming as they engaged with several power flow computations But effective optimization approaches can furnish the Optimal • Operating Condition (OOC) with adequate accuracy but less 3 computation effort
Objectives The primary objective of the research is to introduce accurate, but less time consuming PSO based novel approach to find VCP in power system. 1. To develop an effective PSO based approach for determining the VCP of power systems 2. To apply the proposed approach for analysing diverse applications of VSA 3. To compare the effectiveness of the proposed approach including different versions of PSO to CPF method and eigenvalue analysis 4
Concept of Particle Swarm Optimization (PSO) I III IV II 5
PSO Algorithm Initialize Particles Evaluate Particles’ Fitness iter=iter+1 Yes Update Particles iter<iter_max 6 Stop
Methodology – Outlined Flow Chart Determine the VCP point using different versions of PSO, namely, Basic PSO, TVIW and TVAC 7
Methodology – Problem Formulation Objective Function • At the VCP point, active and reactive power at all load buses are • maximized In the study, active power at a random load bus is selected as the • objective function 8
Methodology – Problem Formulation (Cont…) Constraints • The constraint related to the power factor at PQ buses • The constraint related to the definite direction of power increase at • PQ buses ( It is assumed that bus 1 is selected as the objective bus ) The constraint related to the constant active power generation at PV • buses 9
Methodology – Problem Formulation (Cont…) Constraints – Cont … • The constraint related to reactive power limit of the PV buses and • the slack bus The constraint related to active power limit of the PV buses and the • slack bus 10
Methodology – PSO Number of particles is set as d and each particle should have attributes • of voltage magnitudes of PQ buses and phase angles of both PQ and PV buses Phase angles are randomly initialized in such a way that initialized • values should be lied within ± 10 0 and voltage magnitudes for PQ buses are initialized according to the modified constraint equation, 11
Methodology – PSO (Cont…) Active power adjustments (PV buses PQ buses except selected load • bus) to satisfy equality constraints, For PV buses if • For PV buses if • In PQ buses, phase angle should be adjusted in opposite way • The phase angle adjustment process should be continued until the • residuals of active power differences within the specified accuracy limit. i.e. 12
Methodology – PSO (Cont…) Particles can be represented as, • or The velocity vectors corresponding to the particles are randomly • initiated as represented as Generator reactive power limits can be handled with a Penalty function • 13
Methodology – PSO Method (Cont…) Adjust voltage magnitudes of generation buses according to reactive • power injection, Adjust voltage magnitudes of voltage compensation buses according to • reactive power injection, 14
Methodology – PSO Method (Cont…) The best previous position of a particle is recorded and represented as, • The best among all particles in the group so far, it is represented as, • The particle positions are updated according to the velocity equation as, • The new position of the particle can be obtained as, • 15
Methodology – PSO Method (Cont…) In Basic PSO, all four parameters of the velocity equation are fixed • In TVIW PSO, • In TVAC PSO, • 16
Test Results Values for Tuning Parameters of Proposed PSO Versions 17
Test Results There are four test cases , specifically, Determination the SNB point • • considering reactive power limits of generators • optimal operating condition (OOC) considering both active and reactive power limits of generators Diverse applications of voltage stability analysis under optimal • operating condition • OOC under (N-1) contingency criterion • OOC with a voltage compensation devices 18
Test Results : Power System of Sri Lanka (182 buses) 220kV Line 132kV : Underground Cable 132kV : Line 220/132 kV Sub Station 132kV GS Hydro Power Station CHUNNAKAM Thermal Power Station KILINOCHCHI KOTUGODA VAVUNIA ANIYAKANDA TRINCOMALEE KERAWALAPITIYA KAPPALTURAI TRINCOMALEE PS KADAWATHA ANURADHAPURA BIYAGAMA KELANIYA S'KANDA NEW ANURADHAPURA KHD KELANITISSA COL-C LAKDANAWI NEW HABARANA COL-F KOLONNAWA COL-B PUTTALAM HABARANA COL-E NOROCHCHOLAI COL-K ATURUGIRIYA POLONNARUWA COL-I ARANGALA MAHO VALACHCHANAI SRI J'PURA COL-A ORUWALA NAULA PANNIPITIYA DEHIWALA BOWATENNA PADDIRIPPU NEW CHILAW KURUNEGALA MADAMPE RATMALANA UKUWELA PANNALA AMPARA MAHIYANGANA BOLAWATTA PALLEKELE VEYANGODA KATUNAYAKE KIRIBATHKUMBURA RANDENIGALA INGINIYAGALA KOTUGODA THULHIRIYA RANTEMBE KEGALLE VICTORIA KERAWALAPITIYA BIYAGAMA ANIYAKANDA KOTMALE UPPER KOTMALE KELANITISSA KIRINDIWELA LAXAPANA POLPITIYA WIMALASURENDRA KOLONNAWA SAPUGASKANDA BADULLA ATURUGIRIYA NEW MONARAGALA SRI J'PURA N'ELIYA ORUWALA SEETHAWAKA LAXAPANA DEHIWALA PANNIPITIYA KOSGAMA RATMALANA CANYON MORATUWA PILIYANDALA PANADURA BALANGODA HORANA RATNAPURA SAMANALAWEWA MATUGAMA KUKULE DENIYAYA AMBALANGODA BEDDEGAMA HAMBANTOTA 19 BELIATTA GALLE WELIGAMA MATARA
Test Results : Power System of SL (Cont…) 1 : Considering Reactive Power Limit of Generators • 20
Test Results : Power System of SL (Cont…) 2 : Optimal Operating Condition with Generator Limits • 21
Test Results : Power System of SL (Cont…) 3 : OOC under (N-1) Contingency Criterion • 22
Test Results : Power System of SL (Cont…) 3 : OOC under (N-1) Contingency Criterion (Cont … ) • 0.68 0.66 0.64 Loading Factor, λ c 0.62 0.60 0.58 0.56 0.54 Base 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 23 Contingency
Test Results : Power System of SL (Cont…) 4 : OOC with an installation of 100MVar SVC at bus 45 (JPURA_3) • 24
Test Results : Power System of SL (Cont…) Summary results of Test System • 25
Conclusion and Recommendations The study introduces a new optimization approach, which • directly calculates the VCP without several power flow computations by PSO The effectiveness of the proposed approach has been tested on • the power system of Sri Lanka. Test results are evaluated with the CPF method and the optimality is verified by eigenvalue analysis Results confirms that the proposed PSO based approach is very • valuable as it produces accurate, technically feasible, optimal solution for the 182-bus power system of Sri Lanka It is recommended to install sufficient reactive power resources • to most critical buses identified in (N-1) contingency criterion to enhance the VCP of the power system of Sri Lanka 26
Areas for Improvements It is important to study the behaviour of OLTC and the optimal • tap setting, which furnishes the OOC It is better to check the performance of the proposed PSO based • approach with different types of voltage compensators other than capacitors and SVC The study is limited to Basic PSO, TVIW PSO, and TVAC PSO • and they do not show a significant difference. However, it is vital to consider other types of PSO versions 27
Thank You and Questions? Acknowledgement The Royal Thai Government (HM Queen Scholarship Program) 28
Recommend
More recommend
