Dynamic pricing
Transcription
Dynamic pricing
Thanks to technology and institutions, Electricity demand could become active ! Workshop « Smart grids » Chaire développement durable-X, 21 October 2010 Dominique FINON Directeur de recherche CNRS, Cired Introduction Demand activation : a needed complement to smarting grid&meters for the cost-benefit of smart meters roll-out results from Faruqui, Harris and Hledik on Europe , published in J. Energy Policy (2010) Vol.38 • Costs: Indicative cost of smart meters roll-out in EU: 51 B € • Benefits 1. Operational savings for DSO: 26 B€ (estimation deduced from some US experiences) 2. But ….gap of 25 B€: To be gained by improvement of the surplus of the consumers, and suppliers (LES) If improvement of tariffs by default suppliers: 1. 2. With simple time of use tarif : 14 B€ of benefits With dynamic pricing: 68 B€ of benefits (better correspondence of tariffs with time variation of wholesale price To be gained by savings on capacity adequacy Introduction • Smart metering/ grid needs dynamic pricing to be cost effective – Improvement of social efficiency of the system by activation of demand – by information on price , quantity and expense – By dynamic pricing i.e. retail price related to wholesale price – Many coutries with smart meters have no dynamic pricing – Caution from regulators to be faced to consumers backlash if dynamic pricing Content • • • • 1.The ways of activation of demand 2. Contracts in dynamic pricing 3. Experiment in dynamic pricing 4. Where gains of surplus by demand activation are located? 1.The ways of activation of demand 1.1. The very specificity of electricity demand function • Electricity non storable – Need of semi hourly markets with weak intertemporal relations at the wholesale level) • Electricity consumer is blind – No price information transfer to consumers: – No pass-through of wholesale price in real time – No possibility of revelation of WTP concerning reliability • No information on consumed quantity transmitted to suppliers in real time • For a supplier/retailer , selling a contract : – similar to a call option contract on unlimited quantity – making risk management quite complex for retailer • Consumers could consume the same quantity of electricity when the price on the hourly market could be as much as 1000 times off-peak price • If price-quantity information transmission to consumer in a timely way, consumers will react to price signal. • So two successive & complementary processes of demand activation: – Information acquisition by the consumer: effects on his behaviour – Demand becomes reactive to a menu of price /quantity contracts • Experiments in the US and in Europe – On information acquisition – On dynamic pricing 1.2. Importance of the information acquisition • Les “display devices” : rôle fondamental dans l’”éducation” du consommateur et sa réponse aux signaux prix. • Ils font varier favorablement les élasticités prix. • Un grand nombre d’objets communicants ont été testés (Orb, Flower lamp, Aware cord…). • Certains objets ont fait leur preuve sur le terrain (Orb, thermostat communicant, …). • Peu de données. • L’hétérogénéité des modes expérimentaux ne permet pas de relier un display en particulier à une réponse “moyenne” du consommateur. • US Experiments Faruqui (2009) : effects on 6% max on the energy consumption • UK (Sarah Sharby) on info feed back : 11% as an effect on consumption • OFGEM much more skeptical: effect of 1% with the display on smart meters 1.3. Dynamic pricing price Solution 1: dynamic/real time pricing • Smart meter & Activation of demand: the key of market normality –If the demand will be price responsive, –price variablity decreases –Market power decreases price 2. Dynamic pricing and contractualization Time of use pricing (TOU ): – Retail price that vary with time of day – But regardless of system conditions – Does not require hourly meter Dynamic pricing : • retail price that vary with real time system and market conditions • Requires hourly meters to be implemented Load shaving contracts: (outside demand function (price quantity) The customer delegates to a supplier or another player the management of his demand during variable peak period (implicit payment by savings) Possiblity of delegation: • to aggregator of load shaving services, • to distributors ( more and more interesting for DSO if intermittent sources) Dynamic pricing versus Time of use pricing Dynamic pricing • • Time of use pricing No incentive to to reduce demand during periods with high wholesale price and stressed system Incentive to reduce demand during periods with high wholesale prices and stressed system Reduces price volatility and increase system reliability • Perfectly inelastic hourly demand for electricity • This solution improves partly collective surplus on long term: Partial reduction of peak demand on long term adequate capacity • • This solution improves collective surplus on short term and long term • Predictable and easy to understand Different types of dynamic pricing • Purest form : Real time pricing (RTP) – Elec prices linked to the wholesale price (day ahead basis to reduce uncertainty) – Only for industrial consumers able to manage their risks • Critical peak pricing (CPP) to reflect the true cost during a small period (12 days) – Very high prices (Times 5) – Small Discount for the remaining hours – Incentives to decrease conumption in peak hours or to shift to less expensive hours Different types of dynamic pricing (following) • Flexible critical peak pricing – Designation the day before (in sime case few hours before) – More efficient than fixed CPP • A variant : Peak time rebate (PTR): – Cash rebate for each kWh of load below a baseline – To establish a baseline – Payment to the wholesale price (or whlesale price minus retail price) – Eventually remote control on heating/ air-conditoning devices Economic problems in implementing dynamic pricing (Chao, 2010; Bushnell, Hobbs, Wolak, 2009)) • Establishing a baseline for each consumer for the CPP and for the Peak time rebate: – Assymetry information between the supplier and the customer – Credibility of demand reduction under the peak price signal which is a problem for the supplier’s risk management • Economic problems in implementing dynamic pricing (Chao, 2010; Bushnell, Hobbs, Wolak, 2009)) • The solution is demand subscription: « buying your baseline approach » – Identical treatment of the supply and the demand – Baseline is contractualised with an exogenous formula (proper incentive rathe than the ) – Consumers « may sell energy » on which they have made a firm commitment to purchase – One example : a specific load profile contract/Nominal quantity bis indexed (with a formula to total demand of the class) 3.2. Experimentation on dynamic pricing Programs on pilots of dynamic pricing in USA, Australia, Canada Programs DOE Utilities 5 Etats, volontaire, obligatoire DOE Utilities dans 3 Etats, volontaire PG&E, volontaire Midwest power system of Iowa, volontaire The Gulf Power Selec Program, Floride 2000-2001 Puget sound Energy (Seattle) 2001-2002 Ameren UE- (2004, 2006) California Statewide Pricing Pilot (SPP) 2003-04 volontaire California Public Utilities Comission Community Energy Cooperative’s energy-Smart Pricing Plan (ESPP) 2003-2005 – Illinois, volontaire Anaheim Critical Peak Pricing experiment, 2005 Tariffs refereneces TOU TOU TOU TOU TOU, CPP TOU TOU, CPP TOU CPP-fixe CPP var RTP Kohler and Michell (1984) Caves et al. (1984) Caves et al (1989) Baladi et Herriges (1998) Borenstein, et al (2002) Faruqui et George (2003) RLW Analytics AmerenUE Charles River Assoc (2005) Energy Australia’s Network Tariff Reform 2006, volontaire Idaho Residential Pilot Program, Idaho Power Cie, volontaire, 2006 TOU TOU, CPP Daniel Violette Summit Blue (2006) University of California Energy Institute, F. Wolak Harry Colebourn (2006) Sanem Sergici (2006) Olympic Peninsula Project, 2005-2007 TOU, CPP, RTP Pacific Northwest National Lab du DOE (2007) Ontario Pricing Pilot, 2006-2007 CPP TOU Ontario Energy Board 16 Main results • Incentives by contracts and by tariffs Faruqui (2009) • With variables prices related to the wholesale prices and the load demand on the system, • lowering of consumption and load is estimated between 10% and 15% during peak hours. • Addition of automatic control on some electrical uses inside home Increase of reduction effect by a factor 2 if possibility to connect advanced metering devices to different appliances and heating, air-conditioning (with automatic control) NB Experiments has been made on ToU and on CPP Results : heterogeneity of Price Elasticity Exemple of California SPP CPP days CAC Electricity Price Elasticity Estimates - Range and Mass Central Points ( Absolute Values) for 15 Studies Points are mass center, lines the values range (where appropriate) 0.45 Estimated Elasticity - Absolute Value Réduction des pointes : 2 à 25% Own-price elasticity (all others substitution) 0.4 0.35 0.3 0.25 Large plage de valeurs de la 0.2 réaction du consommateur (mesurée par l’élasticité prix) 0.15 0.1 0.05 0 1 2 3 Household TOU 4 5 6 7 8 9 10 11 Study Num ber (Table 4) Business HH B CPP 12 13 14 15 17 18 HH Business RTP 11 et 12 SPP 28 octobre 2010 16 17 Illinois Entité d'appartenance Consommateurs hétérogènes => large dispersion des valeurs 18 4. Where gains of surplus by demand activation are located? Where possible gains of surplus by demand activation are located? • For the consumers: – Reduction of expenses on energy during peak and eventually during all the year • For the suppliers: – risk management – Increase of the competitive intensiveness by new opportunities of offering a wider set of offers (It favors « switching ») • For the TSO and the DSO: – economic saving on capacity adequacy and program of reliability – increasing stakes of dynamic pricing /smarting DSO grids with deployment of intermittent sources in windpower and PV • And again for the consumers – Reduction of the need of capacity adequacy with the help of peak shaving – Reduction of market power during peak and extreme peak One aspect of surplus sharing by market rules: How to give a value to demand repsonse program via dynamic pricing? – Contracts of load shifting with DSO, TSO, aggregators, suppliers – Integration in load management resources inside capacity mechanism (East coast • NB : 10% in New England and PJM , in the next future France with the obligation of capacity credit, etc.) • Direct load control. Load serving entity (LSE) initiates load reduction by remotely cycling end user equipment. • Firm service level. End user reduces load to a predetermined level based on notification from LSE. • Possibility d’intégrer les effets probabilisés de dynamic pricing