modelling the impact of renewables’ integration in energy ... · modelling the impact of...

Modelling the impact of Renewables’ integration in energy systems and markets and the need for flexible

reserves and associated pricing

Dr Christos PapadopoulosRegional Director Europe

Energy Exemplar (Europe) Ltd 5th Annual European Ancillary Services & Balancing Forum

Energy Exemplar & PLEXOS® Integrated Energy Model

09-Sept-14

About Energy Exemplar PLEXOS® Integrated Energy Model - Released in 1999

Continuously Developed to meet Challenges of a Dynamic Environment

A Global Leader in Energy Market Simulation Software.

Offices in Adelaide, AUSTRALIA; London, UK; California, USA-WC; Connecticut, USA-EC,Johannesburg, SOUTH AFRICA.

High Growth Rate in Customers and Installations

30% staff with Ph.D. level qualifications spanning Operations Research, Electrical Engineering, Economics, Mathematics and Statistics

European Office:

Software Sales

Customer Support

Training

Consulting

European Systems/Markets &

Countries Datasets3Energy Exemplar- 5th Annual EEAS & BF

09-Sept-14 Energy Exemplar- 5th Annual EEAS & BF 4

Portfolio of clients in all five continents

Energy ExemplarEnergy Exemplar Europe

As of the end of July 2014, worldwide installations of PLEXOS have exceeded 850at over 145 sites in 35 countries.

09-Sept-14

PLEXOS® Integrated Energy Model for Energy (Power & Gas)Systems & Markets Simulation, Optimisation & Analysis.

Proven power market simulation tool & Integrated Energy Model

Uses cutting-edge Mathematical Programming based Constrained Optimisation techniques (LP/MILP/DP/SP),

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 systems’ models scalable to thousands of generators and transmission lines and nodes

5Energy Exemplar- 5th Annual EEAS & BF

PLEXOS® applications around the Globe

09-Sept-14

Commission for Energy Regulation (CER) - IRELAND Using PLEXOS® to benchmark Irish SEM dispatch engine for previous

years market outcome.

National Grid - U.K. Uses PLEXOS® to calculate how efficiently they balance the electricity

system. The results are used as a benchmark under a relatedbalancing incentives scheme.

Wärtsilä Corporation - FINLAND PLEXOS® is used to evaluate their smart power generation technology

concept and how their flexible power plants can operate moreefficiently, especially in power markets with high renewable sources’integration, highlighting their lower O&M costs/higher profitabilitybenefits.


Australian Electricity Market Operator (AEMO) - AUSTRALIA PLEXOS® is used in a joint feasibility study published yearly to determine

transmission requirements in the NEM using the LT capacity planning tools ofPLEXOS®.

California ISO (CAISO) - USA Utilises PLEXOS® in the Market Monitoring division of California ISO to

monitor electricity bidding, price manipulation and physical withholding in themarket.

US/DoE National Laboratories (LLNL & NREL/ANL) – USA Various Renewable Generation Integration Studies Improving Optimization Capabilities in Energy Modelling via High-

Performance Computing (Hyperion) and Industrial Collaboration.

Many of the biggest European Power Utilities but also variousTSOs/ISOs and Regulators.

09-Sept-14

PLEXOS® applications around the Globe



European Power Datasets


European Gas Datasets


Daily PLEXOS® v Real Energy Prices - Germany (2011)


Daily PLEXOS® v Real Energy Prices – France (2011)

The impact of Renewables’ integration in Energy Systems and Markets


The Rising RES share impose significant challenges:Long Term: To Systems’ Adequacy & Long Term Reliability (by worsening the already inplace “Missing Money Problem” through the “Merit Order Effect” that reducesWholesale Electricity prices and eliminates the peak/off peak premium, drivingmany Base load Plants but also some FLEX (e.g. Gas Plants) out of the money. To existing Markets’ “Adequacy” (Adequacy of the existing respective

pricing and associated Revenue Opportunities from Energy, AncillaryServices, Capacity Markets or need for other Markets and/or Services?).

Short Term: To Systems’ Operations/Security of Supply & Short Term Reliability due to theincreased need for balancing with Faster (Flexible) Reserves To Markets’ Operations (Day Ahead & Intraday/ Balancing Markets)

Increased Wind Integration Impacts on both LT PowerSystems’ Adequacy and ST Balancing.

09-Sept-14 Energy Exemplar- 5th Annual EEAS & BF

So not only have average electricity prices fallen by half

since 2008 But

THE PEAK PREMIUM HAS

ALSO FALLEN BY ALMOST

80%!!

New Era in European Power Markets

However, that is only the half of it.

“Renewables have not just put pressure on margins. They have

already transformed the established

business model for utilities.”

BASIC MARKET RULE“Excess (Cheap) supply (RES) plus

Reduced demand equals lower prices”

15


Facts Increased planned Wind

generation in coming years Demand Forecast esp.

Domestic (???) Expensive European Gas &

Negative spark spreads leading to mothballing of even new gas plants

Merit order more coal driven

Impacts Standard Base load and Peak load

products are less of a fit with realconsumption profile

More wind generation leads tomore weather exposure inportfolios

More wind generation demandsmore flexibility from powersystems

More regulation & politicalintervention in marketsoperations

Summary Characteristics & Impacts of this Structural Change

16


Variable generation is not dispatchable Variable generation variability and forecast error Definition of variable generation perfect forecast?

Perfect forecast at what moment? How far into the future will the perfect forecasts be?

If the perfect forecast is too close to the dispatch interval, itwill be too late to revise the commitment or de‐commitmentdecisions or the commitment decision is too costly (expensiveunit will be committed and dispatched).

Short Term Challenges from the VariableGeneration Integration


Ramp Un-Constrained & Hourly ConstrainedFlexibility

How much ramp up and down capacity is on‐line (or can be committed in the system)?


ObservationsIf the perfect forecast comes in too late, it would not help too much.The range and the length into the future of the VG forecast moving trend willdetermine additional reserve requirements that will incur the additional cost in UC

Ramp Constrained 10-min Flex-up and down


The Questions How can we better reflect and assess these new risks which come with adifferent energy system?

a) that is based on more renewable and thus it is less manageableand b) on more distributed electricity production and

even more specifically What does that mean?

for uninterrupted/reliable electricity supply and system short &long term adequacy

for loop flows, for infrastructure investments and for the European Market Integration?

Increased Wind Integration Impacts on Power Systems’Adequacy and Balancing

Modelling of dynamics of power systems with PLEXOS® and the need for Flexible

Reserves


Recent studies with PLEXOS® in US and elsewhere have revealedthe Importance of Detailed Integrated Modelling that can alsotake also into account the Flexibility (Dynamic) Characteristics ofpower plants that are mostly related to Wind’s Intermittency:In high wind periods (and/or Low Demand) below are GenerationRamping Up/Down rates already observed in some EuropeanSystems:

> ~600MW per 10 minutes> ~2,500MW per hour> ~7,000 MW per day

Detailed Integrated Modelling of Dispatching

22


Operational Flexibility

The Rising RE share imposed significant systems’ reliability problems andassociated challenges on Power Systems, both short term (inadequate flexibility)& long term (falling capacity reserves). The integration of variable renewable resources such as wind power requiresincreased operational flexibility - capability to provide load-following andregulation in wider operating ranges and at ramp rates that are higher but alsoof a longer duration than are currently experienced. In providing these capabilities, existing and planned thermal generation unitsneed

to operate longer at lower minimum operating levels and To provide more frequent starts, stops and cycling over the operatingday

23


Many detail modelling results (PLEXOS®) have shownthat increased Systems’ & Markets’ Modelling temporalresolution can best capture variability in system load andrenewable generation, but also can capture theinflexibilities of thermal units thus, leading to morerealistic estimations in total generation costs.

Importance of detailed modelling of dynamic characteristicsof balancing plants

Significant cycling and ramping operation of units can becaptured in higher resolution modelling (5min) that hourlyresolution modelling is unable to capture. When dispatched atmore detailed resolution, power plants ramping constraintsbecome more important.

Ramping constraints will also bind on reserve provision


In general, any planned balancing capacity will need not only to have true dynamiccharacteristics to maintain system frequency levels but also at the same time to supportEU Decarbonisation and Renewable goals:

Some of the “flexibility” characteristics needed are: Fast loading: ramp up / down and the capability for continuous cyclic operation The wider possible loading ranges at the highest possible related efficiencies Fast starting and stopping (for Non-Spinning), without impacting on productreliability and operating costs, Low carbon and other emissions Optimal Size and Location and For fuel plants - Flexibility in fuel supplies

Importance of detailed modelling of dynamic characteristicsof balancing plants

Ancillary Services & Balancing

Utilities and grid operators must be prepared to account for powerplants or transmission lines that unexpectedly go out of service, or forunforeseen increases or decreases in electric demand. In addition, asutilities and grid operators increase their reliance on intermittentrenewable generation capacity like wind and solar power, additionalbalancing resources are required to address any inconsistencies ingeneration, for example when sufficient wind and sun are notavailable. Some of the existing Ancillary Services’ products address theseshort-term imbalances in electricity markets by dispatching resourceswithin seconds or minutes of an unexpected imbalance, but thequestion is how this is best valued in this new environment?


System Reserves include among others, coordinated system operation,frequency regulation, energy balance, voltage support and generationreserves.

Using the Ancillary Services features of PLEXOS® we can:

Optimise the uptake of renewables given this additional burden

Ensure provision of reserves in dispatch and expansion planning

Calculate the cost to the system and effect on energy prices of theadditional reserve requirements

Calculate expected ancillary service prices and test any new ancillaryservices provisions.

This analysis takes advantage of PLEXOS® ability to set dynamic reserverequirements based on generators’, loads’ or lines’ contingencies.


Ancillary Services & Balancing

Pricing Flexibility with PLEXOS®


It is now well recognised that the power systems of the future will bemore complex and diverse than ever before. Existing power market offerings and operating rules likewise will needto evolve with power system requirements. For these reasons, proper incentives should be provided to marketparticipants to encourage them in modifying operations and in investing inmore flexible resources.

Today's markets pricing structures are not so effective in providing thenecessary incentives and the proper price signals for investment neither: in More Flexible resources for better system balancing, nor in New Capacity for enhanced system adequacy.

In the end, can these two needs be the two phases of the same coin?

Flexibility - Pricing & Incentives

29


A nodal price represents the cost to the system as a whole of a unit change inload at the node.In the absence of either constraints or losses all nodal (markets’) prices will beequal.This uniform (unconstrained) price is referred to as the system lambda ornetwork energy charge.No matter where we perturb load in the network, the marginal impact on totalsystem cost would be the same.As we introduce constraints on the transmission flows (either on individualbranches or combinations of flows), the nodal prices diverge.

Congestions and Losses are reflected by the separation/differences of nodal (LM) prices across the network.

30

Locational Marginal Pricing (LMP) in PLEXOS®


LMP

Marginal Cost of Generation at reference

bus

Marginal Cost of Losses

Marginal Cost of

Transmission Congestion

= + +


λ is the system “lambda”αι is the node’s congestion charge βι is the node’s marginal loss charge

αι : is the congestion charge at node iωj: is the shadow price on the thermal limit constraints for path j Xi,k: is the angle reference matrix elementωκ: is the shadow price on the node phase angle constraints for node k

βi: is the marginal loss charge at node irj: is the resistance on line j fj’: is the flow on the line j at the optimal solution

λ ι = λ + αι + βι

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The congestion charge is computed by considering all activetransmission constraints and propagating their shadow prices to thenodes using the shift-factors (PTDFs). Note that the congestion charge does not need to be positive. Forexample if the slack bus(es) are located on the high price side of atransmission constraint, the nodes on the low priced side have negativecongestion charges. Also, 2 x rj x fj

' is the marginal loss on line j and is reported as LineMarginal Loss. Although it seems intuitive that these charges shouldalways be positive, they can be positive or negative. For example, ifinjection at a bus reduces loop flow in the AC network, or providesgeneration closer to the loads than the optimal solution, then the MLCwill be negative.


Assessing the value of the available balancing mechanisms and related technologies with PLEXOS® - Co-optimization

Finding the integrated optimal solution may involve multiplemutually exclusive opportunities: Generator can sell either in energy market or AS market

Gas can be sold back to a gas market, burned or stored using “cheap”electricity

Carbon Offsets can be used for generation or sold

The primary optimization is to find the least cost solution given all of theconstraints

Markets provide alternatives to self use (i.e. Reserves) by settingavailability and price

Once set-up, Co-optimized Energy and Reserves LMPs are a naturaloutcome of the PLEXOS® solution



Co-optimisation in Integrated Markets/Systems

Market products are procured simultaneously through central auctions

Advantages from tight coordination in daily operations, whilestrengthening system reliability

Co-optimization is necessary to minimize the total costs of coordinatinggeneration, transmission and reserves to meet demand and ensure reliability

Shadow prices derived from the constrained co-optimization accurately reflect the system-wide opportunity costs of scarce resources, both inter-

temporally and spatially.

Assessing the value of the available balancing mechanisms and related technologies with PLEXOS® - Co-optimization


Formulation of Energy-AS Co-optimization

Limits) Rate Ramp AS and n(Generatio k t, urampasgg

Limits)Capacity AS and n(Generatio kt, ugasgug

Limits)Capacity AS n(Generatio mk,t, uasasuas

m) AS for constraint (AS mt, asas

Balance)Energy (System t losslg

to subject

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sConstraintEmission

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sConstraintEnergy Generator

sConstraint Timen Min Up/DowGenerator

Flexible Reserves Pricing

When requirements for reserves are considered, the optimal trade-offbetween energy and reserve provision must be determined.

The marginal price for a Reserve in a region is the incremental cost formeeting an additional MW of the requirement for the Reserve in the region.

If no additional compensation were required to cover the cost of operating atlower efficiency to provide reserves, the required compensation is given bythe opportunity cost of backing off generation to provide reserves.

In PLEXOS® this compensation will be automatically embodied in the energyand reserves prices, which are provided by the dual variable (Shadow Prices)associated with the related constraints defining the required quantities ofenergy and reserves.


Energy, Spinning (Raise) Reserve and Regulation (Raise) Reserve prices


Opportunity Costs


Under the Co-optimisation of Energy and multiple AS, the market clearing prices for the multipleproducts have the following characteristics:

LMP for energy give precise representation of the cause-effect relationship that is consistentwith grid reliability management

Higher Prices for higher quality (more Flexible) Ancillary Services.

Spinning Raise Prices = Shadow Price (Clearing Price) of Spinning Reserve requirement constraint +Shadow Price (Clearing Price) of Regulation Raise requirement constraint

There is Marginal Equity between Energy and Reserves Prices:

Energy LMP - Shadow Price (Clearing Price) of Regulation Raise requirement constraint =Marginal Cost (Shadow Price) of combined Energy and Regulation Reserves provision atthe node, when SR=0 and RR>0.

Energy LMP - Shadow Price (Clearing Price) of Regulation Raise requirement constraint -Shadow Price (Clearing Price) of Spinning Reserve requirement constraint = Marginal Cost(Shadow Price) of combined Energy, Spinning and Regulation Reserves provision at thenode, when SR>0.


So, in effect, LMPs for Energy are always higher than market clearing prices forancillary services except that there exists ancillary service capacity shortage (this canbe seen from the previous relationships) priced then at the value of reserve shortfall(VORS) similar to the VOLL for Energy shortage (Unserved Energy). These price relationships are essential to encouraging rational marketparticipants responses to market signals. Therefore adopting a formal optimisationtechnology in market clearing with the proper Flexibility and Scarcity Pricing Signalsis vital both to Market Efficiency and Grid Reliability.Market Clearing prices for Energy and Multiple Ancillary services based on Co-optimisation technology of PLEXOS®, reflecting product substitution costs (betweenenergy and multiple AS) also creates price equity among the multiple products. Priceequity refers to the fact the a market participant can expect to receive equivalentamount of profits no matter which kind of service it is assigned to provide...

More importantly, this price equity is a real incentive for participants to follow dispatch instructions!!

Energy & AS Market Clearing Prices based on Co-optimisation


Thank you for your time,

attention and the

opportunity.

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