Modern Power Systems for Smart Energy Society Zhe CHEN Professor, PhD Email: zch@et.aau.dk Website: http://homes.et.aau.dk/zch http://www.et.aau.dk 1
Contents Energy background in Denmark Challenges to Danish Power Systems Some research activities at Energy Department, Aalborg University, Denmark 2
Danish Energy Industry Denmark currently produces more than 30% of electricity energy from wind sources Aims for a 50% wind share by 2020 Denmark also has large number of CHP installations which supply both heat and electricity load with a high efficiency. Future: A fossil fuel free energy society 3
Danish Energy Development Primary fuel consumption if Danish energy system is converted into 100 percent RES. Henrik Lund, Renewable energy strategies for sustainable development. 4
100 % Renewable Energy
Electric power infrastructure 1985 -> 2009
Wind Power in Denmark
8
Danish offshore wind farms Horns Rev I Middelgrunden Outside Copenhagen harbour Horns Rev II Offshore Wind Farm: 210 MW Anholt Offshore Wind Farm: 400 MW 9
North Sea Offshore Grid Study EU-Power Cluster Supergrid, VSC HVDC System stability Economics
Challenges to Power Systems Large scale wind power integration Large offshore wind farms High penetration of distributed CHP plants Reduced operational capacity of centralised power plants Power fluctuations and balance Electricity market and pricing effects System variations, (cables replace overhead lines) 11
Development of a Secure, Economic and Environmentally-friendly Modern Power System (DSF Project) Grid structural security assessment and improvement Optimal operation of electricity market Real time control strategy Advanced protection Intelligent control of distribution systems Interactive energy system with grid, heating and transportation system
Power grid complexity Vulnerability Assessment of Power System 13
G 1 Bid ($/MWh) G 2 Bid ($/MWh) System Average Price ($/MWh) Probability G 2 Bid ($/MWh) Optimal operation of electricity market Uniform pricing mechanism vs Pay-as-bid mechanism Pay-as-bid mechanism may reduce price volatility and also encourage investment in new generation capacities. 0.12 0.1 0.08 0.06 0.04 50 40 30 20 0.02 0 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 Loading Factor 10 0 MP - SC 1 DIS - SC 1 100 200 300 400 500 600 700 800 Number of Market Clearings 50 40 50 40 50 45 MP - SC 1 DIS - SC 1 30 30 40 35 20 20 30 10 0 MP - SC 1 DIS - SC 1 100 200 300 400 500 600 700 800 Number of Market Clearings 10 0 MP - SC 1 DIS - SC 1 100 200 300 400 500 600 700 800 Number of Market Clearings 25 20 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 Loading Factor
Voltage(PU) MVAr/MW Real time control strategy Real time intelligent operation and control of Modern Power System with large scale Renewable Energy penetration PMU-10 PMU-3 PMU-11 PMU-1 PMU-2 PMU-13 200 MW O/P from HRA MVAr O/P from HRA MVAr Injection at KAE-150N X: 88 Y: 175.3 PMU-8 PMU-9 150 100 X: 22 Y: 160 X: 103 Y: 67.81 PMU-14 50 1.15 X: 102 0 0 20 40 60 80 Y: 40 100 120 1.1 Voltage of HRA-150-S1 Voltage of KAE-150N X: 88 Y: 1.097 PMU-12 PMU-5 PMU-6 PMU-7 PMU-4 PMU Commissioned 1.05 X: 88 Y: 1.061 1 0 20 40 60 80 100 120 Operation States PMU Planned 15
Online Dynamic Security Assessment and Preventive Control Random Forest Mode Decision Tree Mode case n DT Model X n =[a 1,a 2,,a K ] a i >K? a i >K a i K a j ÎS a j ÎS? a j ÏS Secure Secure Insecure Procedures: A large number of Decision Trees (N DT = 500) Each node of DTs depends on a sub-vector randomly selected from the full-vector predictors. Bootstramp sampling better estimating the distribution of the original dataset
Hierarchical Voltage Control in WIPS Danish Power System DigSILENT DSL model of WAMS for Danish PS
Intelligent Protection Methods for Modern Power System based on WAMS Multi agent system based control layers Projection of cascading events Practical hardware-in-loop test bed Supervisory control layer Emergency control lever Physical power system model layers 18
Automation and control of generation units for the overall grid stability and security 50kW Wind Turbine Variable resistive load VSC for interfacing to the AC grid Battery units 19 25kW PV unit 40kW simplified Gas Engine model
An Interactive Energy System With Electrical Grid, Heating and Transportation Systems System Balancing Peak Shifting Project Objectives Designing, based on Smart Grid concept (Danish case), intelligent strategies of DSM to optimize the interaction of the Electrical Grid, Heating and Transport Systems. 20
An Interactive Energy System With Electrical Grid, Heating and Transportation Systems 21
Systems with High Level Integration of Renewable Generation Unit (DSF Project) Wind power: limited autoregressive integrated moving average (LARIMA) model CHP generation: discrete Markov model with multiple transition matrices Load seasonal autoregressive moving average (ARMA) model 1) WT power factor setting for minimizing losses, 2) short-term distribution system planning, 3) cable selection for wind farm network, 4) wind turbine capacity and energy curtailment, 5) frequency deviation analysis. City loads Domestic loads Industrial loads CHP plant Wind farms
Operation and Control of Modern Distribution Systems (PSO Project) A. Control Strategies in Normal Operation Situations Study the characteristics of a distribution system under a dynamic electricitypricing, load management system and a large number of DGs. Propose an optimal operation strategy for a battery energy storage system
Optimal Operation Strategies for PEVs
Communication system in modern power system Central management system CB Transformer IED CB Control Center Synchronization Control CB DES WT WT Controller Local controller Local controller e.g.substation control center SCADA system Control center Local controller e.g.substation control center CB Controller CB CB Energy Storage CHP Controller Controller Controller e.g. WT controller Controller e.g. WT controller Controller e.g. WT controller Controller e.g. CHP controller CB: Circuit breaker Load Controller IED e.g.bus IED IED e.g.feeder IED IED e.g.transformer IED IED e.g.bus IED
Current in ka Operation and Control of Modern Distribution Systems (PSO Project) B. Control Strategies in Abnormal Operation Situations Control strategy of DG governor Control strategy of DG exciter Load shedding strategy Adaptive protection set points 5 With grid 4.5 Without grid Control and Protection of Islanding Systems 4 3.5 3 2.5 2 1.5 1 0.5 0 Z5-6 Z5-7 Z7-8 Z8-9 Z9-10 Z10-11 Z11-12 Z12-13 Z13-14 Feeders
Oscillation Performance and Wide-area Coordination Control of Power System with Large-scale Wind Farms Study the influence of wind farm integration on power system oscillation Design a wide-area damping control strategy, coordinating PSS, FACTS damping controller and wind farm damping controller Area 2 Gen 10 Bus 30 Bus 2 Bus 1 Gen 1 Bus 39 Line 9 Load 39 Line 0 Gen 8 Load 26 Line 27 Load 29 Line 25 Line 26 Bus 37 Bus 26 Bus 28 Bus 29 Bus 25 Load 28 Line 24 Bus 27 Bus 38 Load 25 Gen 9 Bus 18 Line 20 Load 27 Bus 24 Bus 17 Gen 6 Load 24 Load 18 Bus 16 Bus 35 Bus 3 Load 3 Bus 15 Load 16 Line 31 Bus 21 Bus 22 Load 4 Load 15 Line 15 Load 21 Bus 8 Bus 5 Line 21 Line 2 Line 1 Line 10 Line 7 Line 6 Line 5 Line 4 Line 8 Line 3 Line 19 Bus 4 Bus 6 Bus 7 Load 7 Bus 31 Line 11 Load 31 Gen 2 Load 8 Bus 11 Bus 14 Load 12 Line 12 Bus 10 Bus 9 Bus 32 Bus 12 Bus 13 Area 1 Gen 5 Area 3 Gen 3 Line 22 Line 23 Line 16 Line 17 Line 18 Line 14 Line 13 Line 28 Line 30 Line 29 Load 23 Bus 19 Bus 23 Bus 36 Load 19 Bus 33 Gen 4 Gen 7 Bus 20 Bus 34 Line 32 Line 33
Research on hybrid multi-in feed HVDC system with large scale offshore wind farms Norway AC system LCC HVDC link DC breaker1 Shunt capacitors BUS1 CB1 Tie line Load1 Grid side CB2 BUS3 Gen1 G Load2 Back to Back CB3 CB4 Gen2 G Wind Farm DC breaker2 VSC HVDC link BUS2 Load3 BUS4 Load4 Danish Power system Hybrid Dual-infeed HVDC system model
Conclusions Power System is a key component in Smart Energy Systems. Many challenges in modern power systems with large scale renewable We are actively working to address these challenges