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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.

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.

We consider the problem of choosing among different distribution channels for combinations of different products, and how to price, or share the costs under the various alternatives, in an efficient and fair way. The problem could also be interpreted in terms of producing different products in a joint production process, and choosing between technologies with different costs and cost structures. More specifically, we consider technologies with combinations of fixed and variable costs. The variable costs are assumed to be linear and separable in the products, i.e. for a given technology and product type, we have constant marginal costs. The optimal choice of distribution channel / production technology will depend on the total production plan, or demand. That is, both the level of the total quantities demanded, and also the relative shares of the demands for the different products influence what is the best solution. In a marginal cost pricing regime, this would lead to prices changing according to production level and product mix. The price changes would be abrupt, depending on the boundaries between the areas where the different production technologies dominate. As a function of output, the marginal cost prices may show large increments or decrements depending on which production or distribution technology is the best for the given product mix. In this setting we will consider cost sharing rules using game theoretic concepts. More specifically, we consider Aumann-Shapley prices, which can be interpreted as a natural extension of average cost prices to the case of joint production of several goods. Throughout, we illustrate the pricing rules in a small example, with two products, and several technologies to produce or distribute them.

The issue of finding market clearing prices in markets with non-convexities has had a renewed interest due to the deregulation of the electricity sector. In the day-ahead electricity market, equilibrium prices are calculated based on bids from generators and consumers. In most of the existing markets, several generation technologies are present, some of which have considerable non-convexities, such as capacity limitations and large start up costs. In this paper we present equilibrium prices composed of a commodity price and an uplift charge. The prices are based on the generation of a separating valid inequality that supports the optimal resource allocation. In the case when the sub-problem generated as the integer variables are held fixed to their optimal values possess the integrality property, the generated prices are also supported by non-linear price-functions that are the basis for integer programming duality.

This paper focuses on the combined effects of loss factors and zonal pricing in a system that takes as a starting point the procedures of transmission pricing in the Norwegian power system. It interprets the notion of loss factors in an AC power flow model, and develops a method for finding zonal prices consistent with a restricted AC optimal power flow. The effects of decomposing the nodal prices to find a loss factor to cover the marginal cost of losses, and letting the congestion management be resolved by zonal prices based on a DC approximation of the flows, are evaluated by comparing the resulting net prices to those of an optimal AC power flow (AC-OPF).

In this paper, we investigate methods for managing congestion on the grid in the Nordic power market. Specifically, we have considered the differences between using counter purchases as opposed to pricing out the transmission constraints of the grid. We show that the specific method used for congestion management greatly affects prices and therefore the surplus of the various agents, including the system operator. This means that the market agents may have preferences for one method, and take actions in order to influence which method is to be used. Based on this we have studied the incentives and possibilities of "moving" capacity constraints, and the effect this has on system performance. We have also looked into the differences between various pricing schemes, i.e. optimal nodal prices versus optimal zonal prices.

In 1997 an incentive-based regulation was introduced for Norwegian transmission and distribution companies. Under the following revenue regulation regime, the permissible revenue of a grid company is adjusted annually, and during the first regulation period, the new revenue cap was determined on the basis of last year’s revenue cap, adjusting for inflation, productivity improvement, and load growth. The idea behind the load growth compensation factor was that the grid companies should be compensated for increased costs due to grid expansion. Load growth was chosen, partly because it was considered to be an exogenously determined variable. However, in this paper, we will examine some investment incentives due to the load growth factor of the adjustment formula of the Norwegian regulation. We will show that as a result of parallel flows in electrical networks, a seemingly reasonable regulation policy of an electricity market may have paradoxical effects.

Our objective is to find prices on individual items in a combinatorial auction that support the optimal allocation of bundles of items, i.e. the solution to the winner determination problem of the combinatorial auction. The item-prices should price the winning bundles according to the corresponding winning bids, whereas the bundles that do not belong to the winning set should have strictly positive reduced cost. I.e. the bid on a non-winning bundle is strictly less than the sum of prices of the individual items that belong to the bundle, thus providing information to the bidders why they are not in the winning set. Since the winner determination problem is an integer program, in general we cannot find a linear price-structure with these characteristics. However, in this article we make use of sensitivity analysis and duality in linear programming to obtain this kind of price-information. The ideas are illustrated by means of numerical examples.

The efficiency of the power market is heavily affected by the operation and pricing of the transmission system and the topic of this thesis concerns the interaction of the transmission network and the energy markets. After describing different power flow models, we provide an overview of models developed to efficiently coordinate the allocation of transmission resources. The focus is mainly on short-term efficiency, and the survey is only partial, but provides an integrated overview of some of the theoretical models most frequently cited in the literature. An overview of the Norwegian transmission system is given, and we describe the tariff structure, which applies in the central high voltage grid. The implementation of short run marginal cost pricing is studied. More specifically, charges for marginal losses and zonal pricing are examined. Loop flow induces seemingly paradoxical situations in power transmission. We show that a new line may reduce social surplus, and we study the competitive effects of a new line. Throughout, the findings are illustrated by means of simple examples. This is to enhance readability and intuition.

Grid investments are normally done in electrical networks in order to achieve a well functioning integrated electricity market and/or making the network more secure, i.e. less sensitive to link failures. In general, there are two aspects to be considered when making a new grid investment, the first is that of detecting beneficial investments, and the second is how to induce them under the chosen market regime. We will show that network "improvements", i.e. strengthening a line or building a new line, may in fact be detrimental to social surplus, and that some agents will have incentives to advocate these changes.

In this paper we present a bilevel programming formulation of a deregulated electricity market. By looking at a deregulated electricity market in this format we achieve two things, the relation between a deregulated electricity market and other economic models that can be formulated as bilevel programming problems becomes clear, (i.e. Stackelberg leader-follower games and principal-agency models) an explanation of the reason why the so called "folk theorems" in electricity networks can be proven to be false The interpretation of a deregulated electricity market as a bilevel program also indicates the magnitude of the error that can be made if the electricity market model studied does not take the physical constraints into account or oversimplifies the electricity network to a radial network.

In the deregulated Norwegian electricity market a zonal transmission pricing system is used to cope with network capacity problems. In this paper we will illustrate some of the problems that the zonal pricing system, as implemented in Norway, has. With the use of small network examples we illustrate the difficulties involved in defining the zones, the redistribution effects of the surplus that a zonal pricing system has, as well as the conflicting interests concerning zone boundaries that are present among the various market participant. We also show that a zone allocation mechanism based on nodal prices does not necessarily lead to a zone system with maximal social surplus. Finally, we formulate an optimization model that when solved yields the zone system that maximizes social surplus given a pre-specification of the number of zones to be used.

The energy transition reveals a number of challenges for the planning and operation of electric power systems, many of which are the subject of active research. Among the open issues that relate to market design, one has been the subject of particularly intense debate in Europe since the liberalization: the market-based allocation of transmission capacity. Currently, the European electricity market is organized around the principle of zonal pricing, which is characterized by the delimitation of regions on the power network, that are called zones, inside which the electricity price is the same in the wholesale market. This principle is opposed to nodal pricing, in which the price is differentiated between every location. In this thesis, we present detailed models and algorithms for analyzing the efficiency of zonal pricing. In the first part, we focus on the short-term efficiency and, in particular, on the impacts of the optimization of the grid topology through transmission line switching for improving the efficiency of zonal pricing. The second part of the dissertation investigates the efficiency of zonal pricing in the long run, when investment decisions in generating capacity are accounted for. First, we propose a model of the long-run equilibrium of zonal pricing with flow-based market coupling, which is the current methodology used in practice in Europe for allocating transmission capacity. We show that this methodology introduces new inefficiencies in the context of capacity expansion. Then, we investigate whether additional locational instruments, such as capacity and energy-based signals or market-based re-dispatch, can restore the efficiency of investments in zonal pricing. For each of the three main contributions, we present simulation results of our models on a large-scale instance that represents the Central Western European network and we discuss the implications of our results for the performance of zonal electricity pricing. (FSA - Sciences de l'ingénieur) -- UCL, 2022

This thesis studies the new interconnector NordLink's effect on electricity prices in the Norwegian price area N 0 2 and in Germany. When examining the cable's price effect, we assess how the price volatility has developed, whether price convergence between the areas has occurred, and if the highest price levels in Germany have been reduced. The study is conducted by estimating a quantile regression model for both areas. In the models, we control for various factors known to impact day-ahead electricity prices. The variable of interest is a dummy variable that marks the first exchange of electricity through NordLink, which allows for a before-after analysis of the cable's price effect on both areas. Our results indicate that NordLink has had a price-reducing effect in the German market, while it has increased prices in N0 2 for the given period. Hence, price convergence between the previously separated markets is seen as an effect of the cable. The results also show that NordLink has had the most significant impact on German prices at the highest parts of its distribution, confirming a peak shaving effect. Moreover, the results show decreasing price volatility in Germany and partial evidence for volatility exacerbation in N02. Further, the thesis argues that through NordLink, gas and EUAs' effect on electricity prices in N0 2 has been strengthened. Additionally, we find renewables' downward pressure on electricity prices to be strengthened in both areas after the opening of NordLink. In Germany, the price-reducing effect from NordLink is only found in conjunction with renewables. nhhmas

Given the more frequent occurrence of weather extremes, growing awareness and responsibility of the climate crisis and its consequences can be observed within the population. It seems as if growing climate change concerns ultimately lead to more and more people switching to an ecological lifestyle. However, from time to time, one does observe a divergence of what individuals claim to do in order to limit the effects of climate change and what they actually do. This so-called green gap was verified in several domains of human behavior, among others, in residential energy-conserving behavior. As energy consumption is one of the main contributors to a household’s carbon footprint, improving one’s understanding of the determinants of residential energy consumption behavior is fundamental to promoting energy-conserving behavior effectively, thereby limiting climate change. Therefore, this thesis used an explanatory research approach to investigate the relationship between the psychological variables energy-saving attitudes and intentions and electricity consumption. The study is based on the Theory of Planned Behavior. The IDEAL Household Energy Dataset, published by the University of Edinburgh, served as the primary data source. This master’s thesis focused on 30 Scottish single-households. The households’ responses to survey questions measuring energy-saving attitudes and intentions were matched with electricity consumption estimates based on sensor data measuring instantaneous power usage over a period of more than five weeks. The results indicate that energy-saving attitudes have a negative effect on electricity consumption, whereas energy-saving intentions do not impact actual electricity consumption to a statistically significant degree. Moreover, a mediating effect of energy-saving intentions on the relationship between energy-saving attitudes and electricity consumption, which is based on the Theory of Planned Behavior, could not be detected. This study contributes to the residential energy-conserving literature focusing on psychological factors by (1) using actual energy consumption data, (2) focusing on single households, and (3) providing evidence for the importance of controlling for the time an individual spends at home. nhhmas

Due to the high costs related to green hydrogen, most of the world’s hydrogen today is supplied from grey hydrogen, resulting in a substantial carbon footprint. However, with decreasing capital costs, and the possibility to exploit electricity price fluctuations to reduce production costs, green hydrogen could prove to become a competitive alternative. This thesis focuses on evaluating the potential to reduce the total cost of hydrogen production stemming from alkaline water electrolysis. The method is based on exploiting electricity price fluctuations through excess production capacity combined with hydrogen storage. A mathematical, multi-period decision model was developed to find the most cost-efficient, long-term production schedule for an on-site, grid-connected production plant. Model results stem from various scenarios representing different horizons and storage options to determine the optimally combined capacities for production and storage. Thus, the effects of plant cost reductions, increased electricity price fluctuations, innovative storage solutions, and improving efficiencies are explored in regard to hydrogen production. The main findings show that it is costly to exploit electricity price fluctuations to reduce hydrogen costs when obligated to satisfy a required demand. In most cases, the cost of additional production and storage equipment counteracts the benefit of producing in hours of low-cost electricity. However, under certain circumstances, mainly very volatile electricity prices and underground hydrogen storage, hydrogen costs can be reduced through investments in excess production capacity. Additionally, under a special cost structure for grid fees, capacity expansions became substantially more attractive, in which an optimal solution pushed the determined limit for production capacity. In a future scenario, a 36% increase in daily production capacity was observed to be the economically preferred option, which resulted in a production cost reduction of 8.86% and an overall decrease in the levelized cost of hydrogen. nhhmas

This master thesis is a contribution to Statkraft's data center pilot project supported by User Case 2 of the Norwegian Center for Energy Transition Studies (NTRANS). NTRANS is researching the role of the energy system in the transition to a zero-emission society. NTRANS researches the development of environmentally friendly energy from a social science perspective, and in the interaction between technology and society. The research in NTRANS is building a knowledge base for the road to and the consequences of energy and climate change in Norway. NTRANS is working to understand how restructuring can give the business community opportunities for innovation and value creation. NTRANS includes various User Cases to address current issues in close dialogue with user partners (experts and stakeholders). User Case 2 (UC2) is about green power and industry and it is chaired by SINTEF, which is one of Europe’s largest independent research organizations. UC2 deals with the potential of new renewable power production (focus on offshore wind power) and the attraction of new power-intensive industries, and possible interaction between them in Norway. There are two pilot projects in UC2. Statkraft is leading one of them. Statkraft is Europe’s largest producer of renewable energy and is proactive in the electrification of the economy. This master thesis was developed to provide a business model innovation perspective to the pilot data center project by Statkraft. The objective of this research is to feed the funnel of new business opportunities to create more value out of the utilization of waste heat from cloud data centers in Norway. nhhmas

This thesis addresses the challenges of being an oil nation in a time where the world needs to combat climate changes. Emissions from fossil fuels are the dominant cause of global warming, and the need for actions to reduce the global combustion is obvious. Despite decades of international climate negotiations, the flow of emissions to the atmosphere continues to grow, and the heat continues towards new heights. Leading environmental economists now suggest restraining the supply of petroleum resources to reach targets related to climate change. We aim to study the effect today’s and potential climate policies have on oil production on the Norwegian continental shelf the next decade. Our results show that the currently announced climate policy does affect the extraction path of oil, given an expected oil price of 552.5 NOK. This is in line with similar research. We also look at the implementation of a production fee on oil. We find that the production fee will reduce resource wealth, and might change the extraction path on existing fields. The latter depends on the size of the fee. The higher estimate of 452.55 NOK per barrel causes 10 out of 11 fields in our sample to stop production. The lower estimatec fee of 25.86 NOK per barrel implies no changes to the extraction paths. nhhmas

An increasing share of renewable energy sources, such as offshore wind power, is expected in the future power markets. Several authors have found that power prices tend to decrease and fluctuate more when integrating offshore wind. This results from the merit order effect and the intermittent nature of wind power generation. The thesis aims to investigate how deployment of offshore wind power at Sørlige Nordsjø II and Utsira Nord will impact the Nordic day-ahead market. The optimization model used assumes that both sites are connected directly to the Norwegian mainline grid in NO2 and NO5. Adding offshore wind results in declining power prices for all three operating hours accounting for seasonal fluctuations in water reservoir levels. The level of price convergence in the initial baseline prices seems to impact the number of affected bidding areas. With low seasonal water level, all Nordic bidding areas expect for Finland are affected by the additional generation from offshore wind power, whereas only NO1, NO2 and NO5 are affected in the averageand high- seasonal water level scenarios. Moreover, generation increases in the bidding areas with the added capacity and decreases in other affected areas. Overall, the thesis illustrates trends of increasing price differences and price fluctuations when integrating offshore wind. nhhmas