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Flexible international exchanges: a possible solution for large – scale wind power integration within the future power system

Flexible international exchanges: a possible solution for large – scale wind power integration within the future power system

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  • Flexible international exchanges: a possible solution for large – scale wind power integration within the future power system Author: Kostantinos Ntotas Supervisor: Willhelmus Kling EPS Department TU Delft
    • Table of Contents
    • 1. Introduction
    • 2. Model Development
    • 3. Simulation Set-Up
    • 4. Simulation Results
    • 5. Conclusions
    • 6. Recommendations
    Flexible international exchanges: a possible solution for large – scale wind power integration within the future power system Nordel Power System
  • 1. Introduction
    • Power System Operating Principle => Generation = (Demand + Imbalances ) / hour / day / year => f = 50Hz
    • The price of electricity is dependent on generation-mix, energy-demand and weather conditions varies / hour / day / year
    • Automatic Generation Control (AGC) + Unit Commitment and Economic dispatch (UC-ED) important for: safe, reliable, economic operation
  • 1. Introduction L I B E R A L I Z A T I O N
    • Power System Operating Principle => Generation = (Demand + Imbalances ) / hour / day / year => f = 50Hz
    • The price of electricity is dependent on generation-mix, energy-demand and weather conditions varies / hour / day / year
    • Automatic Generation Control (AGC) + Unit Commitment and Economic dispatch (UC-ED) important for: safe, reliable, economic operation
    • Significant Challenges for the Planning and Operation of the future
    • Power System:
    • Renewable energy integration => Stochastic Generation
    • Challenges: Power Balancing, Unused Renewable Energy
    • Liberalization of power markets => Market Competition
    • Challenges: Regulation Penalties, Reduced Profitability
    • Environmental limitations => Need for Efficient Operation
    • Challenges: Emission Penalties, Global Warming
    1. Introduction Possible Large-Scale Solutions Electrical & Heat Energy Storage Flexible Market Design International Energy Exchange
    • Unit Commitment (UC) : the computational procedure, which combines regularly updated data
    • of the generation portfolio state for making decisions in advance, upon:
      • Which generators to start up
      • When to connect them to the grid
      • In which sequence the operating units should be shut down
      • For how long
    1. Introduction Hours MW Economic Dispatch (ED): The actual dispatch of electricity with a view to minimize the total system costs => by aggregating the output of the various generation technologies prioritized from lower to higher Marginal Cost (MC) Must run 0-cost resources Base load plants Flexible plant Peakers
    • Installed wind power capacity worldwide (2008) => 100 GW => almost 75 GW installed
    • in Europe => 4% of total generation serves well enough 90 million residents
    1. Introduction Global Installed Wind Capacity (GW) On-shore European Installed Wind Capacity (MW), 2007
    • However, the large-scale wind integration within the power system affects Power System operation and consequently UC-ED:
    • Technical Impacts (minimum-load problems, power balancing etc)
    • Economic Impacts (increases the operational cost of conventional generation)
    • Environmental Impacts (emission increase of conventional generation)
    • Local impacts of large-scale wind integration => less noticeable when the electrical distance from the source increases => For investigation of system-wide impacts =>a global view is required
    • Main Research Objective
    • Development of a multi-area model that can simulate the physical and market
    • coupling between the systems of W-UCTE and Nordel such that the impacts
    • of international exchange in the large-scale wind power integration will be
    • investigated
    • Sub-objectives
      • Extension of the W-UCTE simulation model with Nordel
      • Development of annual hydro allocation method for reservoir scheduling, specific for PowrSym3
      • Various scenarios simulations with PowrSym3
      • Analysis
    1. Introduction
  • 2. Model Development W-UCTE Existing Model Generation Mix 2014
    • The studied year is 2014, 6 years ahead horizon. The existing model comprises:
    • Validated models of 70 largest generation units in the Netherlands
    • Representative models of generation plants in neighboring power systems for 2014
    • Load data for the W-UCTE operating areas (NL, DE, FR, BE, GB)
    • Correlated Wind power data for the areas of NL (0-12 GW) and DE (32GW)
  • 2. Model Development Nordic Power System NORNED Sub-marine HVDC cable
    • Nordic Power System => Norway (NO), Sweden (SV), Finland (FI), Denmark-East (DKW). Denmark West (DKW) belongs to W-UCTE. The Transmission System Operator (TSO) is named Nordel. Its main tasks:
    • To ensure the operational security of the power system and to maintain the power balance between supply demand
    • To ensure the long term adequacy of the transmission system and to enhance the efficient functioning of the electricity market.
    Norway - The Netherlands linked through NORNED Start Operation: 08/05/08 Capacity: 700 MW Technology: HVDC Voltage: ± 450 kV Distance: 580 km Start Operation: 08/05/08 Capacity: 700 MW Technology: HVDC Voltage: ± 450 kV Distance: 580 km
  • 2. Model Development Generation Mix Nordel, 2014 Installed Capacities, 2014 The final model configuration is presented here: 14.4 21.2 88.9 144.5 124.3 Total Demand (TWh/y) 2.6 3.7 14.8 26.5 21.6 Maximum Load 1.4 2.6 0.22 2.1 0.8 Wind Power 6.5 17.0 21.0 36.2 31.0 Total - - 1.9 2.7 - Other - - 3.4 18.5 30 Hydro 0.3 1.0 1.0 1.3 1.0 CCGT 4.3 14.1 8.1 1.2 - CCGT CHP 1.9 1.9 2.5 - - Coal - - 4.0 12.5 - Nuclear GW GW GW GW GW Denmark-E Denmark-W Finland Sweden Norway Technology
  • 2. Model Development The modeling approach resulted in an extended model of the European Power System, appropriate for large-scale PS studies + W-UCTE Model Nordel Model West-European Model
  • 3. Simulation Set-Up
    • Simulation objective: To present an annual optimized UC-ED schedule, for a given scenario in 2014
    • Objective function: To minimize the total system operating costs and emission, while respecting the constraints
    • PowrSym3 optimizes international exchange volumes of the respective power system configuration for the hour / week / annual horizon
    • The results are reported into weekly and annually output files in a concentrated fashion, whereas the optimization has hourly resolution
    • The simulation parameters are divided into technical and economic dimension:
    • Technical Dimension
    • ENS (Energy-Not-Served)
    • SR Violations (SR: Spinning Reserves)
    • Wasted Wind Energy (minimum-load)
    • Energy exchange volumes
    • Emission levels (ton/GJ)
    • Economic Dimension
    • Total operating costs (M€/year) per area and for the whole system
    • Utilization factors of generation units
    • Emission savings
  • Fixed import (TenneT QCP) Flexible International Exchange
    • Wind and hydro have both zero-marginal cost => implicit competition during their integration within the power system
    • Improvement of the model’s response from fixed import case (Quality Capacity Plan TenneT 2006-2012) to flexible international exchange in the simulations results
    4. Simulation Results – Technical Dimension
    • The system has clearly large amounts of zero-cost energy (wind & hydro) => capacity factors of conventional generation (especially base load) in all areas are decreased
    • The links between all areas are highly utilized =>Imports = Exports (no losses included – International exchange scheduling until moment of operation)
    4. Simulation Results – Technical Dimension
  • 4. Simulation Results – Economic Dimension
    • The savings from wind power are much higher for isolated power systems
    • Approximately 35% of the total costs savings realized in the Netherlands
    • NORNED is a socio-economic factor of welfare
    • The marginal cost (MC) differences between neighboring power systems decrease with increasing transmission capacity
    • Increased transmission capacities cannot offer proportionally higher economic benefits (operational cost savings)
    4. Simulation Results – Economic Dimension
    • Implementation of reservoir optimization strategy benefits both Norway and the Netherlands
    • The cost savings seems to increase if the price difference is taken into account when hydro energy is scheduled
  • 4. Simulation Results – Economic Dimension
    • Wind power and NorNed lead to saving of significant amounts of CO2 Mtones
    • The decrease from 04-08 GW is due to the higher capacity factor of off-shore
    • Similar patterns are reported for SO2 and NOx
  • 5. Conclusions (1) Regarding the modeling approach:
    • +
    • Reasonable first order representation of the power system under study
    • Useful model for further development, valid approach
    • Capable of producing optimum UC-ED schedules with various inputs of: inflow variation, reservoir optimization strategies, interconnection scenarios, wind power penetrations
    • Simulation results explained well, show the correct operation of the power system
    • -
    • The hydro allocation is not optimized stochastically
    • For now the simulation results may be used only in a comparative basis and not in absolute values
    • The model cannot be validated
  • 5. Conclusions (2)
    • Regarding the large-scale integration of wind power in the Netherlands:
    • Minimum-load situations during high wind – low load periods are expected to present the first technical integration limit for wind power
    • The high correlation between Germany and Dutch wind will pose one more limitation (0.73)
    • Wind power variations => integrated within the power system effectively => sufficient ramping capacity at all times
    • An implicit competition between wind power from the Netherlands and specifically hydro power from Norway may be observed
    • Wind and hydro resources are competing in the transmission level and the availability period of the resource
    • Hydro reservoir optimization strategies, favor the system in terms of operational cost and emission savings
    • Flexible international exchanges => flexible market design =>energy scheduled until the moment of operation => augments the integration of wind power => maximizes the link utilization
  • 6. Recommendations
    • Herewith are presented the recommendations for further research:
    • For more accurate results => wind power of the Nordic countries for the future horizon should be estimated => taking into account correlations in time and space
    • Replace technology specific records included in the database, if generation unit specific data are available
    • Further model extension to include other important areas of the European power system such as Italy, Spain, Switzerland, Austria, Poland etc
    • For a more realistic model, reservoir optimization logic to all modelled areas having hydro power in their generation portfolio
    • For the decisions upon weekly hydro energy allocation in each area, a preprocessing tool should be developed
    • The validity of the modelled system may increase if transmission bottlenecks present in each operating area are effectively included
    • Validation of the total system => time-consuming / strenuous / necessary task; This research took some first steps on that direction => Validation should be furthermore continued
    • Thank you!
    • Questions???
    Flexible international exchanges: a possible solution for large – scale wind power integration within the future power system