Flexibility sales and the aggregator role

Transcription

1 Flexibility sales and the aggregator role CenSES energi- og klimakonferanse 2016 Stig Ødegaard Ottesen Head of R&D esmart Systems Stipendiat NTNU Industriell Økonomi og Teknologiledelse

2 Presentation outline What is flexibility in the electricity system? What kind of values can flexibility create? For whom? How can the flexibility be utilized? The aggregator role Example of a study of the aggregator s decision problem when participating in multiple markets

3 What is flexibility? The modification of generation injection and/or consumption patterns in reaction to an external price or activation signal in order to provide a service within the electrical system (Eurelectric) Two directions Up-regulation: Increased generation or reduced consumption Down-regulation: Reduced generation or increased consumption Old concept at TSO level Dispatchable power generators Large industrial consumers Several market arrangements

4 What is new? The potential for flexibility provision from the demand side is increasing due to technology developments Smart meters The Internet of Things (IoT) Batteries Electric vehicles ++

5 Increased need for flexibility - The TSO perspective I fremtiden er det ikke nok volum av kraft i løpet av året som blir utfordringen, men å møte samfunnets behov for effekt (olje- og energiminister Tord Lien) To maintain frequency and voltage quality To avoid congestion and reduce the need for reinforcements Why? More renewable, uncontrollable and unpredictable power generation Closer connection to the continent More power demanding appliances

6 Increased need for flexibility - The DSO perspective Increased dynamics Larger peaks Reverse flows Flexibility may relieve Voltage problems Congestions

7 Increased need for flexibility - The prosumer perspective Grid contract: Tariffs with power charges Supply/retail contract: Fluctuating prices Value of surplus sales < value of self consumption Norwegian regulation: Surplus sales must be < 100 kw to participate in plusskundeordningen Possible strategies for the prosumer Business as usual Simple controls (e.g. timer based) Advanced algorithms (optimization under uncertainty)

8 How to manage flexibility? The DSO perspective Install batteries Indirect control through grid tariffs Buy flexibility through disconnectable agreements directly with prosumers Buy flexibility through an aggregator An aggregator is a company who acts as an intermediary between electricity endusers and DER owners and the power system participants who wish to serve these end-users or exploit the services provided by these DERs (MIT, 2016) Small volumes aggregated to large (enough) to give market access Gives non-profession agents possibility to sell without daily involvement

9 Example from H2020 project The aggregator enters flexibility contracts With the DSO With prosumers (flexibility vendors) The contracts regulate compensations, flexibility volumes, time restrictions

10 Example from H2020 project The DSO requests flexibility activation when needed The flexibility aggregator plans activations and performs direct control

11 Example from H2020 project Contract based approach Possible to establish a market place for flexibility trading? Flex vendors bid their flexibility Aggregator clears the market at optimal price Or the DSO clears the market

12 Flexibility can be traded in (local) markets Flexibility sellers and buyers meet at a market place Advantages Free, competitive market cleard at optimal price Professional organizer Disadvantages/challenges Liquidity/market power Possible to define standardized products?

13 The aggregator can sell flexibility to multiple buyers

14 The aggregator s challenge Must predict available flexibility Must decide how to allocate flexibility between markets to maximize profit and minimize probability of non-compliance Paper: Multi market bidding strategies for flexibility aggregators in electricity markets. Ottesen, Tomasgard, Fleten. Case study in cooperation with Statkraft

15 The problem How to make optimal bid decisions for a flexibility aggregator in a sequence of markets given that information will be revealed successively and taking physical flexibility constraints into consideration Multi stage stochastic mixed integer linear program

16 Model Options market decision (in brief) Find optimal bid (χ) to the options market (market 1) γ χ + up up 1 1 1, ts, = 1, it,, P1, i< P1, ts, P1, i 1, i I, t T, s S, which max. sum expected profit from all markets P γ + P ( γ γ ) up up down 1 1,, ts 1,, ts 2,, ts 2,, ts 2,, ts max z = Rs. up down up down 1 s S t T + P3, ts, ( γ3, ts, γ3, ts, ) κts, + κts, taken into consideration that option market commitment must be bid to flex market (3) up up 3 χ γ 3, It, 1, t, t T. and that all solutions must be technically feasible From this model we only implement the Options market bid decision

17 How to model flexibility constraints? Regulation can only be done in periods where flexibility is available A regulation can have a maximum possible duration A regulation can have a minimum possible duration There can be a minimum rest time between two regulations We introduce binary variables to keep track of these rules: δ δ up t+ D max u 1 j= t δ δ up end up start u, js, uts,, up min t+ D u 2 up start up end uts,, + δuis,, 1 i= t up min t+ R u up end up start ut, + δui, 1 i= t In addition, we define a subset of regulation units where we can shift volumes, for instance: we can regulate up now, but then we must regulate down later, or vice versa

18 Case study: Aggregator flexibility portfolio overview

19 Case study market framework We use data from RKOM uke, Elspot and RK NO1 as markets We simulate using week 1 8 in 2016

20 The value of flexibility Table below shows revenues and costs summed for all days + January and February separated. Shows also each day for week 1 Net profit = the value of flexibility: 819 k Contribution from January 701 k, from February 118 k Contribution from OM: 168 k Net profit up-regulation: 805 k Net profit down-regulation: 14 k High prices SM + FM in January gives large revenues for up-regulation Low prices SM + FM in February gives larger revenues from OM and for down-regulation compared to January

21 The value of aggregation We run the stochastic model for each flexibility vendor separately (without aggregator) We compare the total results with aggregator The value of aggregation: 26 k January 25, February 1 Contribution: OM revenue: 10 k SM+FM up net profit: 16 k Why does aggregation add value? Can commit larger volumes to the market Easier to find feasible solutions for constrained flexibility units

22 Summary New technologies increase the need for flexibility at different levels New technologies increase the potential for flexibility provision from demand side Flexibility can create values at different levels (prosumer, DSO, TSO ) There are several ways that flexibility can be traded (contracts, market clearing solutions) Aggregation needed The aggregator s decision problem is a complex task

23 Thank you for your attention!