gas and power assets: management and portfolio optimisation with plexos® dr christos papadopoulos...
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2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
Gas and Power Assets:Management and Portfolio Optimisation with PLEXOS®
Dr Christos PapadopoulosRegional Manager Europe
Energy Exemplar (Europe) Ltd
18/04/2013
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
1. Introducing Energy Exemplar and PLEXOS®2. Integration of the physical and financial markets
in PLEXOS3. Long term co-optimisation of power and gas
assets4. Exploring different modelling approaches for
medium to long term hedging decisions
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Content
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Energy Exemplar®Commercial since 1999Focused on PLEXOS® for Power Systems softwareGlobal client base served from three locations:
Adelaide, Australia London, UK California, USA
20% staff with Ph.D. level qualifications spanning Operations Research, Electrical Engineering, Economics, Mathematics and Statistics
By the beginning of 2013, worldwide installations of PLEXOS exceeded 700 at over 135 sites worldwide, in 32 countries.
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What is PLEXOS®?
Proven power market simulation tool
Uses mathematical programming, optimisation and stochastic techniques
Robust analytical framework, used by: Energy Producers, Traders and Retailers
Transmission System /Market Operators
Energy Regulators/Commissions
Consultants, Analysts and Research Institutions
Power Plant Manufacturers and Construction companies
Power system model scalable to thousands of generators and transmission lines and nodes
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PLEXOS® is a MILP-based next-generation Energy Markets/Systems simulation and optimization software.
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
Power Market Modelling, Simulation and Analysis - Short & Long term:
Price Forecasts based on power system operational constraints and market fundamentals, at nodal and regional level.
Detailed operational planning and dispatch optimization while modelling complex renewable-hydro-thermal and transmission
Renewable integration analysis
Investment planning and analysis Valuate and Optimise new generation and transmission builds and
retirements – what, when, where? Assessing the effectiveness of investment decisions and policies
Portfolio Optimization and Valuation 518/04/2013
What can be achieved with PLEXOS® (1)
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
Risk management via scenario analysis, stochastic modelling and optimization: Optimal resource allocation decisions (fuel, heat, capacity) over the
long or short term subject to uncertainty (e.g. volatility in fuel prices, wind, hydro inflows, demand)
Fuel, Emissions and hedge contract evaluation and analysis Transmission and Ancillary Services/Balancing Analysis
Regional, Zonal or Nodal Congestion Forecast and Management Security Constrained Dispatch (N-x) Optimal power flow modelling Interconnector Modelling
Co-optimization of Energy/Ancillary Services and Gas Markets and Energy dispatch
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What can be achieved with PLEXOS® (2)
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
1. Introducing Energy Exemplar and PLEXOS®2. Integration of the physical and financial markets
in PLEXOS®3. Long term co-optimisation of power and gas
assets4. Exploring different modelling approaches for
medium to long term hedging decisions
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Content
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What is an Energy Portfolio?Within the energy industry a portfolio can be divided into two distinct parts:
Physical Portfolio: represented by physical assets - Power Plants, Gas Fields, flow (power/gas) lines, Storages etc.
Contracts Portfolio: consisting of contract assets - Financial and Physical contracts such as futures, forwards, swaps, options and FTRs but also PTRs contracts for electricity and FTS for gas.
While the optimisation of a contract portfolio in a traditional financial market has been well debated, problems can arise when optimising the entire power portfolio.
PLEXOS® “emulates” how the market operates but more importantly the real electricity price formulation mechanism.
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Energy Assets Portfolio Optimisation
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In PLEXOS®, Portfolio Optimisation accounts for both Physical and Financial Assets.
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Generator Class Thermal generators
polynomial heat rate modelling Start costs vary by fuel state Energy Ramp constraints
CCGT operation GT & steam turbine optimisation
Combined heat and power Plants Heat production from a boiler Heat Storage option
Hydro & pumped storages allow long-term decomposition via
targets or water values to shorter more detailed phases
Wind, Solar, Geo-thermal & others
How can the physical market be represented in PLEXOS? (1)
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FuelAbility to model price to be a variableMin and Max off-take quantities
Transmission LinesNet Transfer CapacitiesWheeling ChargesLine Ramp Rates
Nodes, Regions & ZonesDemand ScenariosDemand Side Participation
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How can the physical market be represented in PLEXOS? (2)
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Integration of the Contracts Portfolio (1)• Physical Contracts
• Multi-step Price/Quantity• Min/Max Generation
• Financial Contracts• CFDs• Caps• Floors• Collars
• Fuel Contracts• Multi-step Price/Quantity• Take-or-Pay
• Transmission Rights Contracts• Financial Transmission Rights (FTRs)• Settlements Residue Auctions (SRAs)
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Markets Class Can be used to model not only forward & futures
(financial) markets but also capacity, fuel, ancillary services (physical) markets.
Optimisation of sales and/or purchases to/from Companies
Forward Markets can be optimised first in a two-stage optimisation process ,then the physical market is solved
Company Class Allows the ‘bundling’ of physical and financial assets Various company wide reporting options available
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Integration of the Contract Portfolio (2)
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
• Setting up the forward market in PLEXOS• A market must be linked to a node.• Companies can be linked to report revenue/costs back to each
portfolio owner.
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– Forward markets are solved first to determine sales/purchases then these levels are fixed while the physical markets are solved.
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2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
1. Introducing Energy Exemplar and PLEXOS®2. Integration of the physical and financial markets
in PLEXOS3. Long term co-optimisation of power and gas
assets4. Exploring different modelling approaches for
medium to long term hedging decisions
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Content
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
PLEXOS® Gas Modelling (2013)
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Icon Class Description
Gas Field field from which gas is extracted
Gas Storage storage where gas can be injected and extracted
Gas Pipeline pipeline for transporting gas
Gas Node connection point in gas network
Gas Demand Demand for gas covering one or more nodes
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PLEXOS® - Co-optimisation of both Power and Gas Portfolio Assets.
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• Goal is to provide modellers an integrated gas and electricity model that is straight-forward for power market modellers to understand and use.
• Short and long term simulations• Both system-planner (cost minimisation) and strategic
(maximise profit) solutions• Investment planning: Gas field, storage, and pipeline potential
candidates defined with:• Capital cost of construction (builds cost, WACC, economic
life, project start date, min/max build constraints)• Operating costs (fixed and variable)
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
Simulation Phases in PLEXOS®
LT Plan – Optimal investmentLT Plan – Optimal investment
PASA – Optimal reserve sharePASA – Optimal reserve share
MT – Resource AllocationMT – Resource Allocation
ST – Chronological Unit CommitmentST – Chronological Unit Commitment
New Builds/retirements
Maintenance Schedule
Operating Policies
Detailed by-period results
1 year 4 years 30 years
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LT Plan - Long Term Capacity Expansion Planning
Finds the optimal combination of generation and transmission new builds and retirements that minimizes the net present value of the total costs (incl. fixed and variable operating costs) of the system over a long-term planning horizon. The following types of expansion/retirements and features are
supported:• Building and retiring generating plants and transmission lines• Multi-stage build projects• Expanding the capacity on existing transmission interfaces• Taking up new physical load /generation contracts• Deterministic or stochastic optimization
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PASA - Projected Assessment of System Adequacy
PASA is a simulation that focuses on the balance of supply and demand in the medium term. • When used in combination with MT Schedule and/or ST
Schedule, the primary purpose of the PASA is to determine, where and when maintenance outages should occur.
• It can model planned and random outages of generation plants and transmission lines, and its severity
• In multi-region models PASA calculates the optimal amount of reserve that should be shared between regions using the transmission network. (Equalizing regional capacity reserves done using quadratic programming formulation.)
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MT Schedule - Medium Term Scheduling and Simulation
MT Schedule is used to give fast results for medium to long-term studies. The MT Schedule handles all user-defined constraints including those that span several weeks, months, or years. This might include: • Fuel off-take commitments e.g. gas take-or-pay contracts• Energy limits, Emission quotas• Long-term storage management taking into account inflow uncertaintyMT Schedule:• Gives the option of Load Duration Curves or Chronological modelling
approach, similar to that in LT Plan. Each constraint is optimised over its original timeframe and the MT Schedule to ST Schedule Bridge algorithm converts the solution obtained, e.g. a storage trajectory, to targets or allocations for use in the shorter step of ST Schedule
• Can model competitive behaviour of portfolios over the medium term. (Sophisticated game-theoretic behaviours like Nash-Cournot competition or ‘simply’ recovery of fixed costs.)
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ST ScheduleST Schedule is mixed-integer programming (MIP) based chronological optimization. It can emulate the dispatch and pricing of real market-clearing engines, but it provides a wealth of additional functionality to deal with: • unit commitment; • constraint modelling; • financial/portfolio optimization; and • Monte Carlo simulation. ST Schedule provides two methods for modelling the chronology: • Full Chronology Every trading period (interval) inside the ST
Schedule horizon is modelled explicitly. (Interval can be 1min to 24hrs in length.)
• Typical Week One week is modelled each per month in the horizon and results are applied to the other weeks.
18/04/2013
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
1. Introducing Energy Exemplar and PLEXOS®2. Integration of the physical and financial markets
in PLEXOS3. Long term co-optimisation of power and gas
assets4. Exploring different modelling approaches for
medium to long term hedging decisions
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Content
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Energy Portfolio Optimisation with PLEXOS®
• The return of an energy portfolio is affected by four major sources of uncertainty;• Power Spot Prices• Demand (Power/Fuel)• Inflows• Fuel Prices
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A hedge is a fixed price instrument (physical or financial) whose value moves opposite the market movement and thereby mitigates the risk of the market moving against you, at the cost of the lost benefit when the market moves to you. Hedges can include e.g.:• Financial gas contracts• Fixed price coal contracts• Generator tolling agreements • etc.
• Finding the appropriate hedge strategy is a process of measuring the “unhedged” risk, and finding a portfolio of hedges that constraints the risk to a desired level, i.e.:• 5% of total generation cost
Hedge Planning
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
Spot Prices Use the Scenario Class in PLEXOS to adjust out input
parametersDemand, Fuels & Inflows
Represent inputs using stochastic modelling via the Variable Class
Provided with user-defined samples with an assigned probability for each sample (exogenous) or we can create a endogenous sample using an expected profile that can be scaled up or down a specified distribution (endogenous).
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
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Example of a user-defined endogenous profile entered in PLEXOS® to model the forward power price stochastically.
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
Demand Profile for fictional region ‘R1’ for 2011
Generators sorted by technology
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COMPANY A COMPANY B
COMPANY C
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
• Including the Financial Contract Class• Used to represent CfDs in a Gross Pool or Forward Contracts in a
Net Pool• CfDs can be either one-way (e.g Company and exchange) or two-
way contracts (Between two participating companies – Generator and Retailer)
• A financial contract can be linked to generators so that contract quantity is dependent on one or more generators generation levels.
• PLEXOS® can stochastically model either contract quantity and/or price as a variable so we can model different mix of contract quantities and prices to determine the most profitable result for our 3 companies.
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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Financial Contract Property Value Units Timeslice
RETAIL #1 Quantity 700 MW PEAK
RETAIL #1 Quantity 550 MW OFF-PEAK
RETAIL #1 Floor Price $55 $/MWh
RETAIL #1 Cap Price $55 $/MWh
CfD Example:
In a Gross Pool this example defines a contract-for-difference (CfD), or two-way contract, with a strike (floor=cap) price of $55/MWh. The contract guarantees the generator receives at least this price for generation, and at the same time it guarantees that the load will pay no more than this price for the quantities shown.
How can PLEXOS® be used in Portfolio Optimisation & Hedging?
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
• Lets assume each company has 10 different contracting quantity levels available to them.
• Starting from 0MW up to 1,000MW increasing in 100MW increments. Each 100MW increment will be a separate Profile in PLEXOS.
Gross PoolIf Region Price is below the Floor Price then: • Settlement = (Floor Price – Region Price) x Settlement
Quantity If Region Price is above the Cap Price then: • Settlement = (Region Price - Cap Price) x Settlement Quantity
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
CFD Strike price modelled with samples using base profile with 20% error Std Dev and 50% Auto Correlation
Case 2: Physical market and allow hedging with Financial Contracts
Contract Quantity modelled using set profile in bands of 100MW blocks representing each sample
Endogenous Profile
Exogenous Profile
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
Case 2: Physical market and allow hedging with Financial Contracts – COMPANY A
Sample Contract Amount (MW) Generation (GWh) Pool Revenue
($000)Net Contract Settlement ($000)
Net Pool Revenue ($000)
Sample 1 100 2,847 70,049 906 70,955
Sample 2 200 2,846 70,023 1,636 71,659
Sample 3 300 2,849 70,093 2,930 73,023
Sample 4 400 2,848 70,060 2,630 72,690
Sample 5 500 2,857 70,292 4,816 75,108
Sample 6 600 2,842 69,917 4,080 73,998
Sample 7 700 2,847 70,027 6,196 76,223
Sample 8 800 2,852 70,155 7,052 77,207
Sample 9 900 2,856 70,256 9,165 79,420
Sample 10 1000 2,847 70,029 12,415 82,444
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
Case 2: Physical market and allow hedging with Financial Contracts – COMPANY B
Sample Contract Amount (MW) Generation (GWh) Pool Revenue
($000)Net Contract Settlement ($000)
Net Pool Revenue ($000)
Sample 1 100 837 21,438 906 22,344
Sample 2 200 837 21,455 1,636 23,091
Sample 3 300 835 21,397 2,930 24,327
Sample 4 400 837 21,438 2,630 24,068
Sample 5 500 828 21,234 4,816 26,050
Sample 6 600 843 21,588 4,080 25,668
Sample 7 700 838 21,464 6,196 27,660
Sample 8 800 832 21,322 7,052 28,374
Sample 9 900 828 21,237 9,165 30,402
Sample 10 1000 838 21,482 12,415 33,898
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
Case 2: Physical market and allow hedging with Financial Contracts – COMPANY C
Sample Contract Amount (MW) Generation (GWh) Pool Revenue
($000)Net Contract Settlement ($000)
Net Pool Revenue ($000)
Sample 1 100 2,981 71,836 906 72,742
Sample 2 200 2,982 71,844 1,636 73,480
Sample 3 300 2,981 71,832 2,930 74,762
Sample 4 400 2,981 71,824 2,630 74,454
Sample 5 500 2,980 71,794 4,816 76,610
Sample 6 600 2,981 71,817 4,080 75,898
Sample 7 700 2,981 71,831 6,196 78,027
Sample 8 800 2,982 71,845 7,052 78,897
Sample 9 900 2,981 71,827 9,165 80,991
Sample 10 1000 2,980 71,811 12,415 84,226
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
Physical market and allow hedging with Financial Contracts (Mean of 10 samples)
Pool Revenue ($)
Generation (GWh)
Net Contract Settlement($)
Net Pool Revenue ($)
Company A 69,494,000 2,789 25,034,000 94,528,000
Company B 22,542,000 883 3,959,000 26,501,000
Company C 71,218,000 2,953 18,032,000 84,250,000
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
Recognises that Financial Contracts can effect the bidding behaviour of generators e.g. the higher the generating company’s contract cover the more likely they are to bid close to marginal cost.
When the property is enabled additional constraints are added to ensure that the company generates to meet contract level if economic to do so.
This in turn has the effect of moving the pool price back towards the contract prices over the duration of the simulation.
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How can PLEXOS® be used in Portfolio Optimisation & Hedging?
Including the Competition Object in PLEXOS®
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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EE European Datasets (CWE Market)
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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EE European Datasets (CWE Market)
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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EE European Datasets (CWE Market)
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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EE European Datasets (CWE Market)
2nd Intelligent Hedging & Portfolio Optimisation for the Energy Markets
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Thank you for your time,
attention and the
opportunity.