1 Session 15 Module E.4 Electricity transmission: Pricing Prof. Ignacio J. Pérez-Arriaga Engineering, Economics & Regulation of the Electric Power Sector ESD.934, 6.974 2 Study material  L. Olmos, I.J. Pérez-Arriaga, “A comprehensive approach for computation and implementation of efficient electricity transmission network charges”, MIT-CEEPR-09-010, July 2009. Readings  PJM, “A survey of transmission cost allocation issues, methods and practices”, March 20102 3 4 Regulation of transmission services PRICING 5 Pricing What is the objective?  To ensure that the energy prices & the transmission network charges that are levied to the network users  send efficient economic signals  in the short-term (for operation decisions)  in the long-term (for investment & location decisions)  recover the complete regulated costs of the transmission network  are non discriminatory  are easy to understand & implement, & perceived as fair4 7 Pricing Principles (1 of 2)  Efficient transmission charges should be based on “cost causality”  This translates (remember the rational for justification of transmission investment) into  allocation to economic beneficiaries of the network or  allocation to those users who could be considered responsible for the network investment which are really equivalent criteria (& both difficult to apply in practice)  But this criterion is difficult to apply in practice 8 Pricing Principles (2 of 2)  A proxy: some measure of “physical network utilization” could be used instead (where, when & how much energy is injected or withdrawn, whether actual, potential or estimated)  & never related to the particular commercial transaction established by the network users since, with well informed & rational agents, network utilization does not depend on commercial transactions  Unfortunately there is no indisputable procedure to measure “physical network utilization”5 9 Pricing Short-term signals  Nodal prices  are energy prices that internalize the network effects: losses & congestions  provide correct economic signals for system operation  result in a net surplus, which in practice happens to be insufficient to recover total network costs 10 Pricing Long-term signals  They are meant to recover the total network costs (either jointly with nodal prices or, if nodal pricing is not used, by themselves)  transmission tariffs  based on cost causality of network costs as much as possible, or network utilization otherwise  these charges should not be transaction-based  long-term charges (transmission tariffs) should try to avoid interference with (distortion of) short-term signals (nodal prices)6 11 Pricing Other network-related signals  Network-related locational signals can be also sent in other ways  Information on estimated future network conditions (congestions, loss factors, transmission charges)  Location dependent capacity mechanisms  Definition of firm capacity may depend on location 12 PRICING Location signals in energy prices7 13 Location signals in energy prices Option 1: Nodal prices Examples: Argentina, New Zealand, most ISOs in the US  Losses & network constraints are implicitly taken care of  this is very convenient in non well meshed networks, with systematic network constraints  an algorithm is needed  loss of transparency  bilateral physical contracts need some ad hoc solution  Nodal prices result in a net revenue (≈ 20%) that can be used to partly offset transmission costs   need for a complementary charge (≈ 80%)  as the complementary charge is so large, the basic network cost allocation problem still remains unsolved 14 Location signals in energy prices Option 2: Zonal prices  Examples: California & Texas (both have moved to nodal pricing), NordPool, Italy  By default there is a single market price, except when any systematic inter-zone restriction becomes active  zonal prices  Revenues from application of “zonal prices” should be used to partly remunerate network costs  Sporadic network constraints can be solved via redispatch8 15 Location signals in energy prices Option 3: Single energy market price  Examples: England & Wales, Colombia, Sweden, Spain  Coexistence of a single energy market price & separate short-term signals for losses & constraints  Separate treatment for these concepts:  energy market price  network cost recovery  transmission tariffs  management of network constraints  network losses where any net revenues from the schemes that are used to deal with losses or constraints may be applied for partial network cost recovery 16 Single energy market price Dealing with losses (1)  Losses can be allocated among generators (Lg) and demand (Ld) so that their respective outputs & loads are modified according to their respective loss factors  Example: Consumers in mostly importing areas will be charged for more energy than what they consumed: d’=d+Ld.  Example: Generators in mostly exporting areas will be paid for less energy than what they produced: g’=g-Lg.  This scheme should influence the market bids: generator bid price = original bid price x g/g’ consumer bid price = original bid price x d/d’9 17 Single energy market price Dealing with losses (2)  Bidding process:  Loss factors can be estimated by the ISO  Participants use their best information to construct bid prices  Market clearing  Final settlements are made using ex-post penalty factors based on the resulting dispatch. Previous estimations are ignored  Some risk associated to errors in the prediction of the network conditions (usually not very relevant) 18 Single energy market price Network congestion management  Several congestion management methods are applicable (see the slides on “access”)  Redispatch  Countertrade10 19 PRICING Transmission tariffs (Allocation of network costs: the complementary charge) 20 Allocation of network costs Basic guidelines  Network costs should be fully recovered from charges applied to the network users  Any network costs that are not recovered via nodal prices or equivalent signals must be assigned via transmission tariffs so that  long-term location signals