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Minnesota Renewable Energy Integration and Transmission

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Presentation on theme: "Minnesota Renewable Energy Integration and Transmission"— Presentation transcript:

1 Minnesota Renewable Energy Integration and Transmission
Prepared for: The Minnesota Utilities and Prepared by: GE Energy Consulting, with contributions by: Transmission Companies , –The Minnesota Utilities and Transmission Companies The Minnesota Department of Commerce –Excel Engineering, Inc. –MISO MRITS builds upon prior wind integration studies and related technical work and is coordinated with recent and current regional power system study work. Study period: 11.13’ – 10.14’.

2 The Target Increase Renewable Energy Standard to 40% by 2030
More Increment afterwards Still maintain System Reliability Identification and development of options for managing the impacts of the resources and its cost were also considered during this study.

3 Study Tasks.

4 Study Tasks Develop Study Scenarios; Site Wind and Solar Generation
Perform Production Simulation Analysis Perform Power Flow Analysis; Develop Transmission Conceptual Evaluate Operational Performance Evaluate stability related issues Identify and Develop Mitigations and Solutions Power flow analysis for development of a conceptual transmission plan, which includes transmission necessary for generation interconnection and delivery and for access to regional geographic diversity and system flexibility; 2) Production simulation analysis which evaluates hour-by-hour operational performance for an entire year, including reserve violations, unserved load, wind / solar curtailments, thermal cycling, and ramp rate and ramp range, and, to screen for challenging time periods; and 3) Dynamics analysis, which includes transient stability analysis and weak system strength analysis. The broad study scope and the aggressive schedule have been very significant challenges. Evaluate stability related issues, including transient stability performance, voltage regulation performance, adequacy of dynamic reactive support, and weak system strength

5 Scenarios Study Scenarios
Wind and Solar Resource Allocations for Study Scenarios

6 Scenarios Major Assumptions for Production Simulation Analysis of Study Scenarios

7 Wind Plant Siting Minnesota region
Wind plant siting was based on MISO Transmission Expansion plan 2013 (MTEP13) siting principles in the baseline model scenario, addition of 1931 MW into the Minnesota-centric area in scenario 1 and increasing by 610MW above Scenario 1 in Scenario 2. The siting locations (Minnesota-centric area) includes all of Minnesota, parts of North Dakota and South Dakota as well as northern Iowa. MISO (non-MN) Wind Siting for the baseline Scenario 6900MW was added beyond the wind included in the MTEP13, no addition of wind capacity was included for Scenario 1 and beyond the baseline 13,026MW was added for Scenario 2 Siting locations includes all MISO states other than the Minnesota-centric area.

8 Transmission System Study.
Simulation program: Siemens Power Technology PSS/E. Steady state thermal analysis. Method of Modeling: Generation to Generation. This method involves adding new generation and simultaeously turning off an equal amount of existing generation to keep the system balanced where generation equals load (plus system losses)

9 Scenario 1 / Transmission Mitigation

10 Scenario 2 /Transmission Expansion /Transmission Mitigation

11 Study Findings. Total Costs.

12 Production Simulation Process
Model Used:PLEXOS This model captures the forecast uncertainties realized between a Day-Ahead and Real- Time Markets Baseline Scenario: Generation, transmission and market system in 2028 if current industry and economics trends continue. Scenario 1 (S1): Baseline conditions continue, and additional 40% of renewable penetration. Scenario 2 (S2): Baseline trends continue, increasing renewables penetration to 50%.

13 Study footprint / MISO Market footprint
Data about wind energy profile was given by the National Renewable Energy Lab (NREL)

14 WIND ENERGY Data Two different Wind forecast (ND and 4 hours ahead). The 4 Hour wind forecast was used as this more accurately approximates the final generation commitment MISO would have going into the Real time market.

15 LOAD (Day Ahead load forecast)

16 Dinamic Performace. On line generation (MW).
All scenarios produce stable response and voltage recovery. All studies consider a wide range of contingences.

17 Dynamics Analysis Analysis data obtained from the MTEP13 data set and
converted to GE PSLF format Benchmark contingencies simulation for dynamic data Dynamic load Model (GE PSLF Composite model CMPLDW) - added at all loads greater than 5 MW - all loads classified in their service territory - modelling based on WECC parameters

18 Dynamic Models for Renewables
Interconnection between new wind plants, utility-scale PV plants and distributed PV Utility PV and Wind plants both modelled with ±0.9 power factor but at inverter transformer and 690V bus respectively Wind and Utility PV both set to regulate the 690V bus Distributed PV modelled with no voltage regulation capability but as lumped generation in central locations. Inertial and frequency response controls considered inactive Renewable generation topology in Powerflow Model

19 Operation Performance
Annual Energy Annual generation in TWh by unit type for Minnesota-Centric region Annual Load, Wind and Solar Energy for Minnesota-Centric Region

20 Annual Committed Capacity and Dispatch Energy for Coal and Combined-Cycle Units in the Minnesota-Centric Region

21 Operation Performance
Wind and Solar Curtailment. WHY? - Local Congestion - Minimum Generation In all scenarios curtailment happens mostly at nighttime hours as a result of Minimum generation Curtailment reduction by decommiting some baseload generation via economic signals.

22 Operation Performance
Cycling Coal Units Most plants were designated as “must run” - Scenario 1 & 2 Scenarios 1a & 2a assumed coal plants as “not must run” (economically dispatch/committed) Utilization of a day ahead forecast instead of longer term forward market No examination of wear and tear impacts of plant cycling Cycling Combined-Cycle Units Better cycling capabilities than coal plants About 200 start/stop cycles per year Cycling decreases as wind and solar increases

23 System stability and related issues
No angular stability, oscillatory stability or wide-spread voltage recovery issues were observed over the range of tested study conditions. Overall dynamic reactive reserves are sufficient and all disturbances examined for Scenarios 1 and 1a show acceptable voltage recovery. Weak system (low CSCR) issues assessed: - Local pockets of a few wind and solar plants in regions with limited transmission and no nearby synchronous generation (e.g. plants in North Dakota fed from Pillsbury 230 kV near Fargo) - Larger areas such as Southwest Minnesota (Buffalo Ridge area) with a very high concentration of wind and solar plants and no nearby synchronous generation

24 System stability and related issues
Mitigations for Weak System Issues Improve the inverter controls, either by carefully tuning the equipment control functions or modifying the control functions to be more compatible with weak system conditions. Strengthen the ac system, resulting in increased short-circuit MVA at the locations of the wind/solar plants. This approach increases CSCR. A combination of both works best!

25 Conclusions With wind and solar resources increased, production simulation and transient/dynamic stability analysis results indicate that the system can be successfully operated for all hours of the year with no unserved load and minimal curtailment of renewable energy. Stability simulations evaluated using different criteria (first swing and angular stability, separation and cascading outage conditions) Dynamic simulation results indicate that there are no fundamental system-wide dynamic stability or voltage regulation issues introduced by the renewable generation assumed in Scenario 1 and 1a. No dynamic analysis was performed for the study scenarios with 50% renewable energy for Minnesota (Scenarios 2 and 2a) due to study schedule limitations and this analysis is necessary to ensure system reliability.

26 Thank You!


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