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Speeding up the energy transition in the European Union (EU) is a major task to quickly reduce harmful greenhouse gas emissions. Market design plays a crucial role in the decarbonization of the European energy system, driving the expansion of both Renewable Energy Sources (RES) and accompanying flexibility sources. In particular, demand flexibility by energy-intensive industrial companies can play a key role. By flexibilizing their production processes, industrial companies can contribute to an increased use of variable RES (in the following referred to as Variable Renewable Energy (VRE)) to lower the CO2 footprint of their products with positive effects on economic competitiveness. Together with other flexibility sources like electric vehicles, the EU can transition to a just, low-carbon society and economy with benefits for all. However, to actually realize these benefits, market design must account for the changing production and consumption characteristics, e.g., the intermittency of VRE. Starting with current challenges of the energy transition that need to be solved with a future market designin the EU, the whitepaper takes alternative market design options and recent technological developments into account, which are highly intertwined. The whitepaper elaborates on the role of, for instance, flexibility, digital technologies, market design with locational incentives, and possible transition pathways in a European context. The “Clean energy for all Europeans” package offers a new opportunity to deepen the integration of different national electricity systems, whereby Transmission System Operators (TSOs) are required to reserve at least 70% of transmission capacities for cross-border trades from 2025 onwards. The corresponding scarcity of transmission capacities on the national level, however, may aggravate congestion to a critical extent, calling for transformational changes in market design involving, e.g., a redefinition of bidding zones close to the network-node level. The present whitepaper can be seen as part of a series of whitepapers on electricity market design 2030 - 2050 [14, 15] and continues the analysis of regionally differentiated prices or Locational Marginal Pricing (LMP) as a means to address congestion problems in future VRE-based electricity systems. Thereby, the whitepaper extends the findings of the previous two whitepapers (where in the latter whitepapers, e.g., a detailed discussion of the pros and cons of LMP can be found) and elaborates on the question how LMP could be implemented in one or several European countries and how possible implementation pathways may look like in a coupled European system. Moreover, the whitepaper describes preparatory steps that are necessary for the introduction of LMP, and – at the same time – create advantages for countries under both, a nodal and zonal market design. All in all, the results and outcomes of the whitepaper shall support the market design transition in Europe and, thus, the integration and activation of flexibility potentials to foster a fast reduction of CO2 emissions through a better use of VRE. Therefore, the whitepaper contributes with concrete policy measures to the overarching vision of a future European electricity market design that bases on low-carbon technologies and enhances welfare and fairness, while ensuring economic competitiveness of Europe. We would like to thank all the partners and are grateful for the financial support from the Federal Ministry of Education and Research as well as the Project Management Jülich. Martin Bichler, Hans Ulrich Buhl, and Martin Weibelzahl (SynErgie) Antonello Monti (OneNet)

In May 2015, the Flow-Based Market Coupling (FBMC) model replaced the Available Transfer Capacity (ATC) model in Central Western Europe to determine the power transfer among bidding zones in the day-ahead market. It might be easier to change the bidding zone configuration in the FBMC model than in the ATC model as the FBMC model does not need to determine the maximum trading volume between two bidding zones. In our study, we run a simulation in the IEEE RTS 24-bus test system and examine how the bidding zone configurations affect the performance of both the FBMC and ATC models. We show that by improving the zone configuration, the FBMC model outperform the ATC in terms of reducing the re-dispatching cost only when the systems operators have a higher level of cooperation in the real-time market. Our results also indicate that better cooperation among the system operators would help to reduce the need for load shedding.

In May 2015, the Flow-Based Market Coupling (FBMC) model replaced the Available Transfer Capacity (ATC) model in Central Western Europe to determine the power transfers between countries or price areas. The FBMC model aims to enhance market integration and to better monitor the physical power flows. The FBMC model is expected to lead to increased social welfare in the day-ahead market and more frequent price convergence between different market areas. This paper gives a discussion of the procedures of market clearing and a mathematical formulation of the FBMC model. Moreover, we discuss the relationships between the nodal pricing, ATC, and FBMC models. In addition to an illustrative 3-node example, we examine the FBMC model in two test systems and show the difficulties in implementing the model in practice. We find that a higher social surplus in the day-ahead market may come at the cost of more re-dispatching in real time. We also find that the FBMC model might fail to relieve network congestion and better utilize the power resources, even when compared to the ATC model.

Contrary to the common thought that nodal pricing provides more opportunities for a strategic player to exert market power than the zonal model, we show that in the latter one because of the need for re-dispatch or counter-trading, another extra place is created letting more gaming possibilities. Therefore, if proper market power mitigation approaches are not utilized in both day-ahead and re-dispatch markets, then zonal pricing may be more susceptible to market power, especially in zonal model which is based on available transfer capacity (ATC), strategic player's profit and social welfare can be very volatile. In general, the more network constraints are incorporated in day-ahead market (100% in nodal and almost zero in ATC), the more social welfare is attainable. Hence, nodal model is acquitted from the more market power denunciation.

With greater penetration of renewable generation, the uncertainty faced in electricity markets has increased substantially. Conventionally, generators are assigned a pre-dispatch quantity in advance of real time, based on estimates of uncertain quantities. Expensive real time adjustments then need to be made to ensure demand is met, as uncertainty takes on a realization. We propose a new stochastic-programming market clearing mechanism to optimize pre-dispatch quantities, given the uncertainties’ probability distribution and the costs of real-time deviation. This model differs from similar mechanisms previously proposed in that pre-dispatch quantities are not subject to any network or other physical constraints; nor do they play a role in financial settlement. We establish revenue adequacy in each scenario (as opposed to “in expectation”), welfare enhancement and expected cost recovery (including deviation costs), for this market clearing mechanism. We also establish that this market clearing mechanism is social welfare optimizing.

We consider an electricity market organized with two settlements: one for a pre-delivery (day-ahead) market and one for real time, where uncertainty regarding production from non-dispatchable energy sources as well as variable load is resolved in the latter stage. We formulate two models to study the efficiency of this market design. In the myopic model, the day-ahead market is cleared independently of the real-time market, while in the integrated stochastic dispatch model the possible outcomes of the real-time market clearing are considered when the day-ahead market is cleared. We focus on how changes in the design of the electricity market influence the efficiency of the dispatch, measured by expected total cost or social welfare. In particular, we examine how relaxing network flow constraints and, for the stochastic dispatch model, even the balancing constraints in the day-ahead part of the dispatch models affects the overall efficiency of the system. This allows the dispatch to be infeasible day-ahead, while these infeasibilities will be handled in the real-time market. For the stochastic dispatch model we find that relaxing the network flows and balancing constraints in the dayahead part of the market provides additional flexibility that can be valuable to the system. In our examples with high up-regulation cost we find a value of "overbooking" that lead to lower total costs. In the myopic model the results are more ambiguous, however, leaving too many constraints to be resolved in the real-time market only, can lead to infeasibilities or high regulation cost.

Electricity distribution often exhibits economies of scale. In Norway, a number of smaller distribution system operators exist and thus there is potential to restructure the industry, possibly through mergers. However, the revenue cap regulatory model in Norway does not incentivize firms to merge as merging leads to a stricter revenue cap for the merged company. Thus the regulator compensates the firms in order to create such incentives. The amount of compensation is based on the potential gains of the merger estimated using a data envelopment analysis (DEA) based frontier approach introduced by Bogetoft and Wang (Journal of Productivity Analysis, 23, 145–171, 2005). DEA is however only one of many possible frontier estimators that can be used in estimation. Furthermore, the returns to scale assumption, the operating environment of firms and the presence of stochastic noise and outlier observations are all known to affect to the estimation of production technology. In this paper we explore how varying assumption under two alternate frontier estimators shape the distribution of merger gains within the Norwegian distribution industry. Our results reveal that the restructuring policies of the industry may be significantly altered depending how potential gains from the mergers are estimated.

Revenue cap regulation is often combined with systematic benchmarking to reveal the managerial inefficiencies when regulating natural monopolies. One example is the European energy sector, where benchmarking methods are based on actual cost data, which are influenced by managerial inefficiency as well as operational heterogeneity. This paper demonstrates how a conditional nonparametric method, which allows the comparison of firms operating under heterogeneous technologies, can be used to estimate managerial inefficiency. A dataset of 123 distribution firms in Norway is used to show aggregate and firm-specific effects of conditioning. By comparing the unconditional model to our proposed conditional model and the model presently used by the Norwegian regulator, we see that the use of conditional benchmarking methods in revenue cap regulation may effectively distinguish between managerial inefficiency and operational heterogeneity. This distinction leads first to a decrease in aggregate efficient costs and second to a reallocation effect that affects the relative profitability of firms and relative customer prices, thus providing a fairer basis for setting revenue caps.

We consider an electricity market with two sequential market clearings, for instance representing a day-ahead and a real-time market. When the first market is cleared, there is uncertainty with respect to generation and/or load, while this uncertainty is resolved when the second market is cleared. We compare the outcomes of a stochastic market clearing model, i.e. a market clearing model taking into account both markets and the uncertainty, to a myopic market model where the first market is cleared based only on given bids, and not taking into account neither the uncertainty nor the bids in the second market. While the stochastic market clearing gives a solution with a higher total social welfare, it poses several challenges for market design. The stochastic dispatch may lead to a dispatch where the prices deviate from the bid curves in the first market. This can lead to incentives for selfscheduling, require producers to produce above marginal cost and consumers to pay above their marginal value in the first market. Our analysis show that the wind producer has an incentive to deviate from the system optimal plan in both the myopic and stochastic model, and this incentive is particularly strong under the myopic model. We also discuss how the total social welfare of the market outcome under stochastic market clearing depends on the quality of the information that the system operator will base the market clearing on. In particular, we show that the wind producer has an incentive to misreport the probability distribution for wind.

Norwegian distribution companies have been subjected to an incentive regulation scheme from 1997, and the efficiency incentives were further strengthened with the introduction of yardstick regulation in 2007. We examine the productivity development for these companies in the period from 2004 to 2013. Using three benchmarking methods, DEA, SFA, and StoNED, we examine productivity change, with the usual decompositions into efficiency change, technical change, and scale efficiency change. Increasing investments and use of accounting-based capital costs in our analysis may lead to a negative bias in the productivity change estimates, and we therefore perform our analysis with and without capital costs. Our results indicate a negative productivity development for the whole period from 2004 to 2013, and we do not observe a positive effect of the change in regulation regime from 2007.

We construct a Malmquist productivity index based on stochastic non-parametric envelopment of data (StoNED) method, and we study how the distributional assumptions in the second StoNED stage affect productivity change and its decompositions. Our discussion show that the distributional assumptions do not affect the estimates of overall productivity change and scale efficiency change, but that estimates of efficiency change and technical change are affected. Data on Norwegian electricity distribution companies is used to illustrate our discussion.

We study returns to scale in Norwegian electricity distribution companies. The scale issue of this sector has become an important political question, and it was for instance discussed by the Reiten commission (OED, 2014) in a study about the future structure and organization of the Norwegian electricity network industry. We use panel data from the Norwegian Water Resources and Energy Directorate (NVE) for the period from 2004 to 2010. The Data Envelopment Analysis (DEA) method and the Stochastic Nonparametric Envelopment of Data (StoNED) approach are applied to examine the scale issue. We show that a majority of the companies are smaller than the optimal size, in line with Kumbhakar et al. (2014). The performance of Norwegian distribution companies are influenced by a number of environmental factors, and some of these factors are negatively correlated with company size. However, our results show that controlling for environmental factors when estimating returns to scale does not have a big effect on the estimated optimal sizes.

In the European market, the promotion of wind power leads to more network congestion. Zonal pricing (market coupling), which does not take the physical characteristics of transmission into account, is the most commonly used method to relieve congestion in Europe. Zonal pricing fails to provide adequate locational price signals regarding the energy resource scarcity and thus creates a large amount of unscheduled cross-border flows originating from wind-generated power, making the interconnected grid less secure. Prior studies show that full nodal pricing works better in integrating wind power into the grid. In this paper we investigate the effects of applying a hybrid congestion management model, i.e. nodal pricing model for one country embedded in a zonal pricing system for the rest of the market. We test how nodal pricing works in such a hybrid context with more wind power. We find that, compared to full nodal pricing, hybrid pricing fails to fully utilize all the resources in the network and some wrong price signals might be given. However, hybrid pricing still performs better than zonal pricing. The results from the hybrid pricing model of Poland, Germany, Slovakia and the Czech Republic show that, within the area applying nodal pricing (Poland), better price signals are given; the need for re-dispatching reduces; more congestion rent is collected and the unit cost of power is reduced. The results also show that international power exchange increases between the nodal pricing area and the zonal pricing areas, especially on windy days. Moreover, the nodal pricing area has less unscheduled crossborder power flow from the zonal pricing area entering its network and collects more cross-border congestion rent.

In the Nordic day-ahead electricity market zonal pricing or market splitting is used for relieving congestion between a predetermined set of bidding areas. This congestion management method represents an aggregation of individual connection points into bidding areas, and flows from the actual electricity network are only partly represented in the market clearing. Because of several strained situations in the power system during 2009 and 2010, changes in the congestion management method have been considered by the Norwegian regulator. In this paper we discuss nodal pricing in the Nordic power market, and compare it to optimal and simplified zonal pricing, the latter being used in today’s market. A model of the Nordic electricity market is presented together with a discussion of the calibration of actual market data for four hourly case studies with different load and import/exports to the Nordic area. The market clearing optimization model incorporates thermal and security flow constraints. We analyze the effects on prices and grid constraints and quantify the benefits and inefficiencies of the different methods. We find that the price changes with nodal pricing may not be dramatic, although in cases where intra-zonal constraints are badly represented by the aggregate transfer capacities in the simplified zonal model the nodal prices may be considerably higher on average and vary more than the simplified zonal prices. On the other hand nodal prices may vary less than the simplified zonal prices if aggregate transfer capacities are set too tightly. Allowing for more prices in the Nordic power market would make dealing with capacity limits easier and more transparent.

I denne rapporten foretar vi en evaluering av energileddet i sentralnettstariffen og bruken av marginaltapssatser. Vi går først gjennom teorien for optimale overføringstariffer og beskriver hvordan marginaltapssatser beregnes og hvordan disse benyttes i kombinasjon med systempris i dagens nettariff. Vi beskriver også utviklingen i den svenske marginaltaps-tariffen, og vi refererer helt kort utviklingen i PJM-området (USAs østkyst). Ettersom det svenske og det norske systemet tilsynelatende er basert på samme prinsipper, problematiserer vi mangelen på harmonisering, ettersom systemene rent faktisk nå er svært forskjellige. Det er liten tvil om at Statnett har forfinet og forbedret metodene for å beregne marginaltapssatser, samtidig som at flaskehalser fremdeles håndteres ganske forenklet gjennom få og store prisområder på Nord Pool Spot. Vi diskuterer sammenhengen mellom tapstariffen og flaskehalshåndtering, og vi anbefaler at Statnett vurderer å bruke områdepris som avregningspris. Dette vil gjøre det mye enklere for aktørene å ta hensyn til tapskostnadene.

We have previously, in report 33/08, looked at possible weight restrictions for the so-called “geography” variables in the DEA model for the distribution networks. In this report we consider weight restrictions for the remaining output variables. Because some cost drivers are represented by proxy variables, in some cases endogenous input variables, the resulting shadow prices are difficult to interpret. Weight restrictions that rely on detailed assumptions about individual prices, such as the proposal in NVE (2008), are therefore problematic. We suggest instead virtual weight restrictions with respect to groups of variables, thereby eliminating the need for detailed assumptions. The virtual restrictions were introduced in report 33/08, and we discuss here how to set the restriction limits. Since one of the main motivations for considering weight restrictions is to limit the effect of the geography variables, we compare the weight restricted model to a two-stage DEA approach where the geography variables are included in the second stage. We also make comparisons with the procedure used by NVE to limit super efficiency.

We examine weight restrictions in the DEA model for distribution networks, taking as the starting point the NVE model with one input, total cost, and several outputs. In the unrestricted DEA models, we notice large differences in absolute and relative shadow prices, and for some companies, extreme weight on "geography" variables in the cost norms. There seems to be a tendency that companies with a large weight on geographic variables and / or a low weight on transported energy and customers become super efficient. This seems unreasonable, and one remedy may be to restrict prices / weights for individual outputs, or combinations of outputs. We consider absolute, relative and virtual weight restrictions, and show how to formulate the LP problems and how to interpret the restrictions. We discuss the relative price restrictions suggested for geography and high voltage variables by NVE (2008), and consider an alternative approach, using virtual weight restrictions on the combination of the three geography variables; forest, snow, and coast. Comparing the effects of the virtual approach to the relative, we notice that with relative weight restrictions, more companies are affected, but to a lesser extent. An important task when introducing weight restrictions in the DEA analyses is to determine the specific limits on the weights. Finding reasonable limits, depends on which type of weight restrictions that are considered, and should be based on knowledge of cost and technology in the industry. An advantage of the virtual weight restrictions is that they are on a more aggregated level than the relative ones, and it may be easier to establish limits on the overall effects on the total cost norm from a subset of outputs, rather than reasonable pair-wise comparisons of outputs weights. Finally, the report discusses implementation of DEA models with weight restrictions, and gives a short overview of available software.

Tidsforsinkelser i reguleringsmodellen gjør det nødvendig å kompensere for rentetap som skyldes at avskrivning og avkastning på en investering genererer en forsinket inntektsramme i forhold til en ren ”Rate of Return” (RoR)-basert inntektsramme. Kompensasjon for rentetap skal dekke økonomiske kostnader som ikke er registrert i regnskapet, og er ingen økonomisk gevinst. Tidsforsinkelser kan kompenseres på forskjellige måter, og vi ser på to ulike varianter: engangs justeringsparameter og løpende rentekompensasjon. Vi diskuterer også kort ex post inntektsrammefastsettelse, som fjerner tidsforsinkelsene i reguleringsmodellen, og innebærer at et representativt selskap (gjennomsnittlig effektivt) får inntekter tilsvarende en RoR-ramme. I et reguleringssystem som virker over tid og med vedvarende tidsforsinkelse, må kompensasjonen for tapt rente komme som et tillegg til en inntektsramme som er normalisert til beregnet (forsinket) kostnadsgrunnlag, og ikke som en del av den, slik den gjør i dagens reguleringsmodell. Ved overgang til en ny reguleringsmodell vil normalt også tidsprofilen på beregnede kapitalkostnader, lengden på forsinkelser og kompensasjonsform endres i forhold til foregående modell. Vi ser derfor på overgangseffekter mellom ulike reguleringsmodeller, som kan gi grunnlag for både overkompensasjon og underkompensasjon for allerede gjennomførte investeringer.

I NVEs nye reguleringsmodell, som skal gjelde fra 2007, blir nettselskapenes inntekt bestemt av en kostnadsnorm og selskapets egen kostnad med vekter på hhv 60 % og 40 % (50 % hver for 2007 og 2008). Egne kostnader er basert på regnskapsførte kostnader fra 2 år tilbake, det gjelder også kapitalkostnadene, med lineære avskrivninger og avkastning basert på bokførte verdier og renten som fastsettes av NVE. Kostnadsnormen er basert på resultatene fra sammenlignende effektivitetsanalyser (DEA). I tillegg vil det gjøres en normering av bransjeinntekten slik at gjennomsnittlig effektivitet bestemmer normalavkastning. For å ta hensyn til tidsforsinkelsen ved at kostnadsgrunnlaget baseres på to år gamle tall, er det videre introdusert en justeringsparameter for investeringer. I denne rapporten diskuterer vi noen av de valg som er foretatt for effektivitetsanalysene. Vi ser nærmere på effekten av å ha ulike modeller for ulike nettnivåer, valg av referanseperiode for kostnadsgrunnlaget og mer generelt effekter av kostnadsvariasjoner. Vi vil også kommentere utvelgelsen av geografi-variabler og insentiveffektene i den modifiserte varianten av supereffektivitet. Til slutt vil vi kommentere NVEs metodikk for kalibrering/normering av bransjens normkostnad og hvordan dette virker sammen med justeringsparameteren for investeringer.

I reguleringsmodellen som skal brukes for nettselskaper i kraftsektoren fra 2007, benyttes målestokk-konkurranse. Nettselskapenes inntekt bestemmes som et vektet gjennomsnitt av en kostnadsnorm og selskapets egen kostnad. Egne kostnader vil baseres på regnskapsførte kostnader 2 år tilbake i tid, mens kostnadsnormen er basert på resultatene fra sammenlignende effektivitetsanalyser (data envelopment analysis, DEA). I denne rapporten ser vi nærmere på ulike DEA-modeller. Vi ser også på insentivegenskaper i reguleringsmodellen og effekten av variasjon og usikkerhet i data. Vi diskuterer betydningen av modell-spesifikasjon på gjennomsnittlig effektivitet, og hvordan effektivitetsanalysene kan justeres slik at bransjen i snitt oppnår tilnærmet normal-avkastning. Siden kapitalkostnadene er basert på regnskapsførte størrelser, vil alder kunne påvirke effektivitetsanalyser og kostnadsnormer. I rapporten diskuterer vi en foreslått aldersparameter som skal korrigere for alderseffekten.

Dagens DEA-baserte effektivitetsmodell for regulering av nettselskaper i kraftsektoren har klare svakheter. I denne rapporten diskuteres noen sentrale svakheter ved dagens modell og det konkluderes med at den bør endres vesentlig. Det argumenteres for at man bør dele nettselskapenes kostnader i direkte nettrelaterte kostnader og andre kostnader. Sistnevnte gruppe inneholder aktivitetsgruppene måling, avregning, fakturering, tilsyn og administrasjon (MAFTA). Disse kostnadene bør normreguleres i forhold til antall kunder. Fastsettelsen av kostnadsnorm, samt retningslinjer for regnskapsmessig skille, bør utarbeides basert på dybdestudier av et mindre sett av effektive selskap. Det bør også innføres kontrollmekanismer knyttet til kvaliteten på kundehåndtering.

En hovedmålsetning ved regulering av nettselskaper i kraftsektoren har vært å gi insentiver til effektiv drift og investeringer. Nettrelaterte kostnader utgjør anslagsvis 80 % av selskapenes totale kostnadsbase. De inkluderer drifts- og vedlikeholdskostnader i tillegg til kapitalkostnader, dvs. avskrivninger og nødvendig avkastning på investert kapital. I denne rapporten foreslår vi at disse kostnadene ses i sammenheng, og at de settes ut fra en normert nyverdi for anlegget. Dette innebærer at nettrelaterte kostnader i størst mulig grad settes uavhengig av selskapets kontrollerbare kostnader, og isteden baseres på en slags beste praksis drift av et normert nett for vedkommende leveringsområde. Vi diskuterer både prinsipielt og praktisk hvordan en slik normering kan gjøres. Vi vektlegger at man kan unngå nåværende unaturlige skille mellom distribusjons- og regionalnett (og regnskapsmessige arbitrære kostnadsfordelinger). Normeringen av nyverdier og drifts- og vedlikeholdskostnader vil således reflektere på en konsistent måte, forskjeller i anleggets sammensetning mhp ulike nettkomponenter. Videre diskuterer rapporten betydningen av å kompensere selskapene for ex post korrigering av overflødig nett og for generell effektivitetsjustering av kapitalverdi og kostnadsnivå.