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The term “integrated valuation” is defined and its relevance is discussed in terms of bridging the gap between cost-effectiveness analysis and economic valuation in the implementation of the European Union Water Framework Directive. We demonstrate how to integrate benefit valuation with the ecosystem services cascade framework using an Object-Oriented Bayesian Network (OOBN). The OOBN is then used to assess the benefits of nutrient abatement measures across a cascade of submodels of the driver-pressure-state-impact-response (DPSIR) chain for the Vanemfjord lake in Morsa catchment in south-eastern Norway. The lake is part of a complex lake system in a semi-urbanized catchment dominated by forest and agriculture. The catchment has highly variable seasonal climatic conditions affecting nutrient run-off and algal blooms. It has been one of the most eutrophic lakes in Norway with periodic cyanobacteria blooms, but continues to attract a large recreational user population, despite the large variations in water quality. The “DPSIR-OOBN” model is used as a case study of “integrated valuation” and evaluated for its applicability for decision support in nutrient abatement. We find that the DPSIR-OOBN model meets seven of the nine criteria we propose for “integrated valuation”. The model struggles to meet the criteria that ecological, social and economic values should be defined consistently in relation to impacts on lake quality. While the DPSIR-OOBN integrates from valuation methods across an ecosystem cascade to management alternatives, it is neither a full benefit-cost analysis, nor a multi-criteria analysis. However, we demonstrate how the DPSIR-OOBN can be used to explore issues of consistency in scaling and weighting of different ecological, social and economic values in the catchment system. Bayesian belief networks offer a consistent approach to analysing how management implementation probability may determine economic valuation. We discuss the implication of our integrated valuation not being able to account for farmer responses, in particular the incentive effects of the model not being able to predict abatement effectiveness and value. The resolution of the nutrient monitoring data and modeling technologies that were at our disposal are probably better in the Morsa catchment than for any other catchment of this size in Norway. We therefore conclude that using our integrated valuation model for assessing benefits of eutrophication abatement measures as part of the EU Water Framework Directive still lies in the realm of utopia – euphemistically speaking a “eutropia”. Financial support has been provided by the Research Council of Norway for the EUTROPIA project (grant no. 190028/S30), the European Union for the project FP6 AQUAMONEY (contract no. SSPI-022723), FP7 REFRESH (grant no. 244121) and the FP7 OpenNESS project (grant no. 308428).

Artikkelen er gjengitt med tillatelse fra Samfunnsøkonomenes Forening. Sjøkabel framfor luftspenn mellom Sima og Samnanger i Hardanger vil forsinke den nye strømforbindelsen fram til Bergensområdet. Et sentralt spørsmål i valget mellom sjøkabel og luftlinje er derfor hva som blir konsekvensene av forsinkelsen. Hvor lenge må man vente? Hva skjer med forsyningen av strøm til Bergensområdet i ventetiden? Kan man regne med kortere eller lengre perioder med strømavbrudd? Hvis strømforsyningen blir vanskelig, er det i så fall noe en kan gjøre for å forbedre situasjon? Dette var spørsmål som et av Sjøkabelutvalgene (Utvalg III), nedsatt av Olje- og energidepartementet, skulle besvare. Denne artikkelen er basert på hovedkonklusjonene fra utvalgets rapport.

Browsing by large ungulate wildlife species damages valuable trees, but increases the productivity of the wildlife stock. The optimal management of trees and wildlife involves a tradeoff between these two impacts, as well as correct timing of tree harvests from each forest stand. For a model of moose and pine in Norway, it is found that harvest of adjacent forest stands should be adjusted over time to bring the stands into synch. Doing so maximizes the moose productivity boost that occurs immediately following harvest of mature trees, and protects the young trees from overbrowsing by spreading out the browsing pressure among more young trees. This result is, however, sensitive to the specification of the relationship between forage availability and moose productivity.

The determination of farmland prices and the possibility of abovenormal returns to land ovnership, one-shot capital gains (losses) and continuing capital gains (losses) are examined using models based on asset pricing theory. These models appear to explain the rising farmland prices of the pre-1979 periods and their subsequent fall.

In this thesis we aimed to find the best methods for short-term load forecasting in the Norwegian electricity market during times of unprecedented price movements. We answered three questions related to this aim. The first was which model achieved the most accurate forecast. The second was whether our proposed models outperform the official forecasts published on the Entso-E platform. The third question asked was if the price movements had any effect on the accuracy of the load forecast. We constructed two SARIMAX models, a Gradient boosted decision tree, a Random Forest, and a Multilayer perceptron model. Our findings show the two SARIMAX models to be most accurate. These models outperformed the forecasts published on the Entso-E platform in four out of the five Norwegian bidding zones, measured in MAPE and RMSE. Finally, we have shown that forecasting load with and without price information did not result in significant differences in accuracy. Our findings did not indicate an increase in difficulty of forecasting 2021 compared to 2019, neither for the three southern bidding zones with higher price increase nor the northern two zones. I denne masteroppgaven har vi forsøkt å finne den beste metoden for kortsiktig prognostisering av elektrisitets-etterspørsel i perioder med ekstreme prisbevegelser. Vi har besvart tre spørsmål knyttet til denne problemstillingen. Det første var hvilken modell som oppnår høyest nøyaktighet. Det andre var om våre modeller presterer bedre enn de publiserte prognosene på Entso-Es offentlig tilgjengelige data-plattform. Det tredje spørsmålet var om de ekstreme prisbevegelsene hadde noen effekt på nøyaktigheten av prognosene. Vi har laget to SARIMAX modeller, en Gradient boosting decision tree-, en Random Forest og en Multilayer perceptron-modell. Gjennom arbeidet har vi vist at de to SARIMAX-modellene presterer best. Disse modellene er mer nøyaktig enn prognosene publisert på Entso-Es plattform for fire av de fem norske strømregionene, målt i MAPE og RMSE. Til slutt har vi vist at prognoser gjort både med og uten prisinformasjon ikke gir signifikante forskjeller i nøyaktighet. Det ble heller ikke påvist en klar forskjell i vanskelighetsgraden av å prognostisere 2021 sammenlignet med 2019, verken for de sørlige prissonene med høy prisvekst eller de nordlige sonene med en lavere prisvekst. M-ØA

The thesis explores how the Nord Pool power market prices forward-looking information. Specifically, the thesis investigates the efficiency, or the biasedness, of the derivatives side of the power market, how temperature is priced by the market, and how to account for uncertainty in future information. The thesis consists of an introductory chapter which comprises the context and background for the three studies, including a summary. Using data on current and future-looking information from futures prices, the thesis brings new evidence on how the efficiency of the futures market at Nord Pool has developed. Furthermore, the thesis investigates relationship between the relationship between temperature and power prices and the price forecasting information implied in weather forecasts. The thesis provides new insight into the effect of future looking information on the electricity spot prices. The findings indicate that futures on the Nord Pool spot price has been unbiased estimates of the future spot price since 2008. Furthermore, the effect of temperature on price were investigated and were found to be seasonally dependent, different across Norwegian price zones, and different across price quantiles. Also, the information from temperature forecasts is beneficial to use in price forecasts for up to 9 days ahead, but the uncertainty in temperature forecasts has to be accounted for.

Denne masteroppgaven analyserer rollen til tilbudsbegrensninger og salgsaktivitet på regional boligprisdynamikk i Norge. Gradsoppgaven setter heterogene boligpriser opp mot den relative betydningen av tilbudsbegrensninger og salgsaktivitet. Dette gjøres ved å analysere et datasett som inneholder kvartalsvis data for fem regioner over en tidsperiode på 19 år. Det er konstruert en feiljusteringsmodell (ECM) for å kunne estimere kortsiktig og langsiktig sammenhenger mellom regionale boligpriser og utvalgte forklaringsvariabler. Disse sammenhengene blir satt opp mot graden av tilbudsbegrensninger og salgsaktivitet i de utvalgte regionene, for å påpeke hvilken rolle tilbudsbegrensning og salgsaktivitet har for regional boligprisdynamikk. Resultatene avdekker at regioner med høyere grad av tilbudsbegrensninger opplever kraftigere boligprisrespons ved endring i forklaringsvariabler. Samtidig avdekker studien at høyere grad av salgsaktivitet sammenfaller med at boligprisen har raskere konvergenstid mot estimert likevekt. Heterogeniteten i regional boligprisdynamikk kan derfor delvis forklares. Som en konsekvens av den observerte markedsdynamikken kan enkelte regioner som lider av høy grad av tilbudsbegrensning oppleve bobbletendenser og generelt høyere boligprisnivåer. Studien avdekker imidlertid ikke bobbletendenser i dagens regionale boligmarkeder, men at prisnivået tilsynelatende kan utvikle seg til å bli utfordrende på sikt. This master’s thesis analyzes the role of supply constraints and sales activity on regional housing price dynamics in Norway. This thesis is unique because it sets heterogeneous house prices up against the impact of supply constraints and sales activity. This is accomplished by evaluating a data set containing quarterly data for five regions over a 19-year period. An error correction model (ECM) has been constructed to be able to estimate short-term and long-term relationship between regional house prices and selected explanatory variables. The findings suggest that regions with a higher degree of supply constraints are more sensitive to changes in explanatory variables. Moreover, the study reveals that a higher level of sales activity corresponds with a shorter period of housing price convergence toward the projected equilibrium. Therefore, the heterogeneity of regional housing price dynamics can be partly explained. As a result of the observed market dynamics, certain regions with a high degree of supply constraints may exhibit bubble tendencies and generally higher housing price levels. However, the analysis does not identify bubble trends in today’s regional housing markets, although the price level may become problematic in the long run. M-EUTV

This thesis contributes to a project by the Norwegian University of Life Sciences (NMBU) featuring a pilot Vehicle to Grid (V2G) park at Oslo Gardermoen Airport. The goal of the project is two-fold. On one hand, the goal is to provide the airport, a large power consumer who pays power tariffs, with viable measures to shave power peaks and thereby reduce costs. On the other hand, the example of an airport is used to illustrate how V2G can be implemented in a feasible way for EV owners. If successful, this would be advantageous both to power grid operators, to EV owners, and to large power consumers who facilitate EV charging. The thesis approaches power peak shaving by utilizing electric vehicles (EVs) from two angles: Load shifting by scheduling EV charging, and EVs as alternative power supply through vehicle to grid (V2G). EVs with one-way charging capability can be utilized for the first approach, while EVs with two-way charging capability (currently not many) can be utilized for both. In a setting where a large power consumer facilitates long term parking and charging of EVs on its property, both approaches in combination can contribute to reducing power tariffs for the large power consumer. Before V2G is ready for full scale implementation, scheduling the charging is a step in the right direction, and can be seen as ground work for V2G. This thesis presents a Python program demonstrating a method based on scheduling theory, adjusted to minimize simultaneous power demand from EVs, and schedule it outside of expected power peaks. To this author's knowledge, the theory has not been used for this purpose before. While V2G is most commonly regarded from a grid operation perspective, the focus of this thesis is to organize V2G as a mutually beneficial cooperation between representatives of grid interests and the owners of EVs. The technical process that occurs during V2G can be described in very different business terms, depending on perspective. While control based V2G contracts are most commonly considered, stemming from the perspective that the grid operator takes control over (rents) the EV battery to use for V2G, this thesis explores contract designs that regard EV owners as electricity traders, who own the electricity in their battery until they decide to sell it. This leaves more control in the hands of EV owners. Different demand response mechanisms are explored to trigger electricity sale under different circumstances. The thesis concludes with a volume based V2G contract design for the case at Oslo Gardermoen Airport, where EV owners agree to sell a certain electricity volume during a predefined time frame, that the airport may extract when it suits their purposes. Elements from a price based contract, where EV owners define a sales price that triggers a sale when matched by the market price, is also included for certain circumstances. An approach to design V2G contracts for different circumstances can be derived from the discussion. Denne oppgaven bidrar til et prosjekt i regi av Norges Miljø- og Biovitenskapelige Universitet (NMBU), som omhandler et V2G-pilotprosjekt ved Oslo Lufthavn, Gardermoen. Prosjektets mål er todelt. På den ene siden er målet å tilby flyplassen, en stor strømkunde som betaler effekttariffer, virkemidler for å jevne ut effekttopper og dermed redusere kostnader. På den annen side brukes flyplassen som et eksempel på hvordan V2G kan innføres på en gangbar måte for elbileiere. Hvis dette lykkes, vil det komme både nettoperatører, elbileiere og store strømkunder som fasiliterer elbillading, til gode. Oppgaven tilnærmer seg effekttopputjevning ved hjelp av elbiler fra to ulike vinkler: Lastforflytning gjennom tidsplanlegging av elbillading, og elbiler som alternativ kraftforsyning gjennom vehicle to grid (V2G). Elbiler med batterier som kan lades én vei kan brukes til den første tilnærmingen, og elbiler som kan lade to veier (foreløpig ikke mange) kan brukes til begge deler. I tilfeller der en stor strømkunde fasiliterer langtidsparkering og lading av elbiler på eiendommen sin, kan en kombinasjon av begge tilnærmingene bidra til å redusere effekttariffer for strømkunden. Før V2G er modent for innføring i full skala, er tidsplanlegging av ladingen et steg i riktig retning, og kan ses på som forarbeid for V2G. Denne oppgaven presenterer et Python-program som demonstrerer en metode bygget på scheduling-teori, tilpasset til å sikre at minst mulig effekt trekkes samtidig til lading av elbiler, i tillegg til å planlegge det utenfor forventede effekttopper. Såvidt denne forfatteren vet er ikke teorien blitt brukt til dette formålet tidligere. V2G er oftest diskutert sett fra en nettoperatørs perspektiv. Denne oppgaven fokuserer på å organisere V2G som et samarbeid mellom representater for kraftnettets interesser og elbileiere, til gjensidig nytte for begge. Den tekniske prosessen som skjer ved V2G kan beskrives på flere måter i forretningsøyemed, avhengig av perspektiv. V2G er vanligvis diskutert som en kontrollbasert kontrakt, sprunget ut av et perspektiv der nettoperatøren tar kontroll over (leier) elbilbatteriet til V2G-bruk. Oppgaven utforsker kontraktsutforminger som springer ut av et perspektiv der elbileieren anses som en krafthandler, som eier elektrisiteten i sitt eget batteri, og kan velge å selge den. Dette gir elbileieren mer kontroll. Forskjellige etterspørselsrespons-mekanismer utforskes for å utløse salg av elektrisitet under ulike omstendigheter. Oppgaven konkluderer med en volumbasert kontraktsutforming til case-studien ved Oslo Lufthavn, Gardermoen, der elbileiere forplikter seg til å selge et visst elektrisitetsvolum ila. en forhåndsdefinert tilkoblingsperiode. Flyplassen kan kan kjøpe dette volumet på tidspunkt som passer deres formål innenfor den avtalte perioden. Elementer fra en prisbasert kontrakt, der en forhåndsdefinert salgspris utløser et elektrisitetssalg idet markedsprisen matcher den, er også inkludert for visse tilfeller. En tilnærming til V2G-kontraktsutforming til forskjellige sammenhenger kan utledes fra diskusjonen. M-MF