135 research outputs found
Modelling Reliability of Supply and Infrastructural Dependency in Energy Distribution Systems
No full textThis thesis presents methods and models for assessing reliability of supply and infrastructural dependency in energy distribution systems with multiple energy carriers. The three energy carriers of electric power, natural gas and district heating are considered.
Models and methods for assessing reliability of supply in electric power systems are well documented, frequently applied in the industry and continuously being subject to research and improvement. On the contrary, there are comparatively few examples of formal reliability assessment models and methods applied to natural gas and district heating systems. This work aims at contributing to bridge this gap, considering the structural, operational and physical similarities and differences between the systems. A method for evaluating the reliability of supply in natural gas distribution systems is presented, based on state-of-the-art reliability calculations from the electric power domain. Furthermore, a novel modelling approach incorporating pipeline storage in reliability evaluation of high-pressure natural gas pipeline systems is presented.
Parallel energy infrastructures depend on each other at different levels, two of which are addressed in this work. First, by introducing a second energy carrier in an area dominated by electric power, the type of energy end-uses served by the electric power system is affected. An optimisation problem is formulated, finding the optimal allocation of switchgear in an electric power distribution system. It is shown how changes in energy end-uses cause changes in the expected customer interruption costs, which in turn affects the optimisation problem. Second, the dependency of district heating systems on electric power is modelled. Network models for the two systems are coupled, and the consequences of higher-order power system failures are quantified for both systems.
The methods and approaches presented in this thesis are demonstrated by use of simple examples, and applied to test networks and case studies
Environmental constraints in stochastic hydropower scheduling for long planning horizons
No full textThe transformation of the European power system to a climate-friendly one by 2050 involves a shift from fossil fuel generation to renewable energy sources. As a part of this transition, flexible assets are needed to balance out the increasing variability in electricity supply and demand to ensure stability in the system. Hydropower can be an enabler for the green transition because of the technology’s unique ability to provide both short-term operational flexibility and long-term energy storage in the reservoirs. On the other hand, hydropower plants may negatively impact surrounding ecosystems in several ways. To mitigate the negative impacts of hydropower, environmental regulations are normally defined in the licences of hydropower plants. Environmental regulations are necessary to protect local ecosystems and to respect the needs of other stakeholders. Nevertheless, such regulations may reduce the operational flexibility of the hydropower plants and are therefore also associated with a cost.
Good utilisation of renewable energy resources contributes to lower system costs and security of supply. To achieve efficient use of water for power generation, hydropower producers rely on decision support tools to schedule the short- and long-term operation of hydropower plants and reservoirs. Accurate representation of environmental constraints in hydropower scheduling models is required to make correct assessments of the operational flexibility of hydropower plants and the influence of environmental regulations. Understanding the implications of environmental constraints on the operation of hydropower plants and their capability to provide flexibility to power systems is imperative to effectively plan the operation of hydropower-dominated power systems with high shares of variable renewable power generation.
The work conducted in this thesis investigates the implications of environmental constraints on flexible hydropower plants in stochastic scheduling models with long planning horizons. The impacts of different types of environmental constraints have been assessed from the perspective of a profit-maximising power producer operating in a competitive market and from a cost-minimising system perspective considering a wind- and hydropower-dominated region of a power system. A special emphasis was put on the modelling and evaluation of reservoirfilling constraints that are formulated as reservoir-level dependent discharge limitations (soft reservoir-filling constraints). The results are disseminated through five scientific papers, where three are published and two are under review at the present time. The publications constitute the core of this thesis and substantiate the discussions and results presented here.
The work in this thesis contributes to the overall understanding of environmental constraints on the operations of hydropower plants. Two stochastic optimization models have been developed, one for the scheduling of a hydropower system from the perspective of a single producer and one for the scheduling of a windand hydropower-dominated region in a power system. The models are based on stochastic dynamic programming (SDP) and include non-convex reservoir-level dependent environmental constraints. The models are used to investigate the implications of environmental constraints on the operation of hydropower plants, the importance of including such constraints in the strategic scheduling of hydropower plants with reservoirs and, finally, the interplay between environmental constraints and reserve capacity requirements. Four different types of environmental constraints are considered in this thesis: a soft reservoir filling constraint (reservoir-level dependent discharge limitation), a reservoir ramping constraint, a minimum release constraint and a ramping constraint on discharge.
The findings imply that environmental constraints may have considerable impacts on seasonal reservoir management and that, under certain conditions, there is an economic benefit in planning for soft reservoir filling constraints (reservoirdependent discharge limitations) in advance. Furthermore, the results show that reservoir-level dependent (i.e., state-dependent) constraints may induce a nonconcave expected future profit function and significantly change the expected marginal value of storing water in some periods. The work also investigates and discusses the impacts of three different types of discharge constraints (i.e., reservoir-level dependent discharge limitations, minimum release requirements and ramping restrictions on discharge) on the available flexibility in a hydrodominated region of a power system. The results show that the impacts on the capability to meet the demand for electricity and reserve capacities requirements depend on the characteristics of the environmental constraints, such as if the constraint mainly reduces the available power capacity or the amount of regulated energy production, and if the constraint includes state- and time-dependencies
Hydro-Thermal Multi-Market Optimization
No full textFundamental optimering av kraftsystemet er essensielt for å anskaffe korrekt beslutningsstøtte
for investeringer og for optimal drift av kraftsystemet. Med en økt andel av ukontrollerbare
energikilder og utfasing av kull og atomkraft forventes det at en høyere andel av regulerbar kapasitet
holdes ute av energimarkedet for å tilby balansetjenester. Når en høyere andel kapasitet
reserveres i balansemarkedene må de fundamentale markedsmodellene bli revurdert ettersom de
i hovedsak kun vurderer energi. Derfor vil denne masteroppgaven videreutvikle en prototype
under utvikling for fundamental multi-marked hydro-termisk modellering ved navn PriMod.
Målet med denne oppgaven har vært å inkludere krav for opp- og nedregulerende kapasitet i
modellen og undersøke hvordan ulike allokeringsmetoder og volumkrav påvirker kraftsystemet.
Både reserveallokering innenfor hele norden og innenfor hvert prisomåde er testet. I tillegg er
et verktøy for å analysere hvordan det økonomiske overskuddet fordeles lagt til. Simuleringene
er kjørt over en sommer- og en vinteruke for å teste hvordan modellen responderer ved ulike
klimatiske forhold.
Resultatene viser at økte reservevolumer for oppregulering øker områdeprisen for energi. Effekten
er mest tydelig om vinteren når lasten er på sitt høyeste. På omvendt vis fører økte volumer
nedregulering til synkende områdepriser, spesielt om sommeren når etterspørselen etter energi
er lav. Dette understreker at økte volumer i reservemarkedene vil ha en signifikant påvirkning
på energiprisene. Dette viser at behovet for en fundamental multi-markedsmodell er essensielt
for korrekt modellering av kraftsystemet.
Videre illustrerer resultatene at oppreguleringsprisen øker om vinteren når termiske kraftverk
tilbyr reserver til høy pris. Om sommeren øker nedreguleringsprisen da kraftsystemet må tvinge
inn produksjon fra dyre vannkraftverk som kjører med tap. For å kompensere for de tapte inntektene
må systemoperatøren betale tilbyderne av reserver for sin kapasitet. Simuleringene
viser at denne systemkostnaden er høyest om sommeren når både opp- og ned regulering blir
kostbart. Alene er oppregulering dyrere i uke 9 enn nedregulering er i uke 31 for samme mengde
reserver.
Ved å betrakte de økonomiske beregningene kan det observeres at økte reserver senker konsumentoverskuddet om vinteren og øker det om sommeren ettersom systemprisen endres. Produsentoverskuddet følger motsatt trend. Selv om produsent- og konsumentoverskuddet endrer
seg som forventet, synker ikke det totale overskuddet med strengere reservekrav. Ettersom
de ulike scenarioene håndterer reservoarene ulikt, blir kostnadene for vannkraft ulike. Videre
analyser må derfor til for å undersøke hvordan vannverdiene korrekt kan representeres. Dette
resulterer i økt økonomisk overskudd i tilfeller der det motsatte er forventet.
Alt i alt viser PriMod lovende resultater til å bli en velfungerende fundamental multi-markeds
modell, men mangler fortsatt en del detaljer rundt håndteringen av genererende enhetene som
tilbyr reserver for å kunne modellere balansemarkedene korrekt.Fundamental modeling of the power system is essential to provide decision support for investments
and optimal system operation. With increased penetration of intermittent generation and
the outfacing of coal and nuclear power, it is expected that more dispatchable capacity will be
held out of the energy market to provide balancing services. With more generation reserved in
capacity markets, the fundamental market models need to be re-visited as they mostly consider
the product of energy. This serves as the motivation for this thesis which further develops a
prototype under development for fundamental hydro-thermal multi-market modeling, referred
as PriMod.
The main objective of this thesis has been the implementation of constraints regarding up and
down regulation and to investigate the impact different allocation methods and reserve volumes
has on the power system. Both reservation of capacity within the entire Nordic power system
and within each price zone is tested. In addition, a tool to analyze how the economic surplus
distributes has been created. The simulations are run over a winter week and a summer week to
analyze the impact of different climatic conditions.
The results show that increased volumes for up regulating reserves increase the energy prices.
The effect is most prominent at the price peaks during winter when the load is high. Contrarily,
increased volumes of down regulating capacity decrease the energy prices, mostly during
summer when the load is at its lowest. This underlines that for increased volumes of reserves
procured in balancing markets, the price impact in the energy market is significant, highlighting
the need for a fundamental multi-market model.
Moreover, the results illustrate that up regulating prices increase during winter as expensive
thermal units supply up regulation at expensive costs. In the summer, the down regulating
prices increase with increased reservation volumes as hydro power stations are forced to produce
energy at lost profit. The lost profit achieved by forcing production for down regulating
or holding back capacity for up regulation will be compensated by the TSO. Individually, the
reservation costs for up regulation in week 9 are more expensive than the down regulation costs
in week 31 for the same amount of reserved capacity. However, combined the total reservation
costs are higher in week 31 as both up and down regulation becomes costly.
Regarding the welfare calculations, increased reserve procurement decreases the consumer surplus
during winter as the energy prices increase and increases the consumer surplus during
summer when the energy prices decrease. The producer surplus follows the opposite trend.
However, in the calculations of surplus from hydro power, there are some irregularities as the
producer surplus depends on the water values and the future costs of water. Since the different
simulations handles reservoirs differently, the costs of hydro power are different in the simulations.
Further investigation of the producer surplus from hydro power is therefore needed.
Resultingly, the total surplus does not decrease for increased reserve procurement as would be
expected.
The thesis results indicate that PriMod shows great potential in serving as a fundamental multimarket
model, but still lacks some details in the handling of reserve units to obtain realistic
modeling of the balancing markets
Hydro-Thermal Multi-Market Optimization
No full textFundamental optimering av kraftsystemet er essensielt for å anskaffe korrekt beslutningsstøtte
for investeringer og for optimal drift av kraftsystemet. Med en økt andel av ukontrollerbare
energikilder og utfasing av kull og atomkraft forventes det at en høyere andel av regulerbar kapasitet
holdes ute av energimarkedet for å tilby balansetjenester. Når en høyere andel kapasitet
reserveres i balansemarkedene må de fundamentale markedsmodellene bli revurdert ettersom de
i hovedsak kun vurderer energi. Derfor vil denne masteroppgaven videreutvikle en prototype
under utvikling for fundamental multi-marked hydro-termisk modellering ved navn PriMod.
Målet med denne oppgaven har vært å inkludere krav for opp- og nedregulerende kapasitet i
modellen og undersøke hvordan ulike allokeringsmetoder og volumkrav påvirker kraftsystemet.
Både reserveallokering innenfor hele norden og innenfor hvert prisomåde er testet. I tillegg er
et verktøy for å analysere hvordan det økonomiske overskuddet fordeles lagt til. Simuleringene
er kjørt over en sommer- og en vinteruke for å teste hvordan modellen responderer ved ulike
klimatiske forhold.
Resultatene viser at økte reservevolumer for oppregulering øker områdeprisen for energi. Effekten
er mest tydelig om vinteren når lasten er på sitt høyeste. På omvendt vis fører økte volumer
nedregulering til synkende områdepriser, spesielt om sommeren når etterspørselen etter energi
er lav. Dette understreker at økte volumer i reservemarkedene vil ha en signifikant påvirkning
på energiprisene. Dette viser at behovet for en fundamental multi-markedsmodell er essensielt
for korrekt modellering av kraftsystemet.
Videre illustrerer resultatene at oppreguleringsprisen øker om vinteren når termiske kraftverk
tilbyr reserver til høy pris. Om sommeren øker nedreguleringsprisen da kraftsystemet må tvinge
inn produksjon fra dyre vannkraftverk som kjører med tap. For å kompensere for de tapte inntektene
må systemoperatøren betale tilbyderne av reserver for sin kapasitet. Simuleringene
viser at denne systemkostnaden er høyest om sommeren når både opp- og ned regulering blir
kostbart. Alene er oppregulering dyrere i uke 9 enn nedregulering er i uke 31 for samme mengde
reserver.
Ved å betrakte de økonomiske beregningene kan det observeres at økte reserver senker konsumentoverskuddet om vinteren og øker det om sommeren ettersom systemprisen endres. Produsentoverskuddet følger motsatt trend. Selv om produsent- og konsumentoverskuddet endrer
seg som forventet, synker ikke det totale overskuddet med strengere reservekrav. Ettersom
de ulike scenarioene håndterer reservoarene ulikt, blir kostnadene for vannkraft ulike. Videre
analyser må derfor til for å undersøke hvordan vannverdiene korrekt kan representeres. Dette
resulterer i økt økonomisk overskudd i tilfeller der det motsatte er forventet.
Alt i alt viser PriMod lovende resultater til å bli en velfungerende fundamental multi-markeds
modell, men mangler fortsatt en del detaljer rundt håndteringen av genererende enhetene som
tilbyr reserver for å kunne modellere balansemarkedene korrekt
Multi-Market Optimization of Energy Storage Taking Into Account Uncertainty
No full textIn this master thesis, the main focus has been to create an optimization model for an energy storage unit to consider the potential of storing energy for future use, when also operating in both the energy and balancing markets. The main goal was to successfully implement this model and study the potential of a storage unit maximizing profit within both markets, and how this affects the scheduling of the storage unit for varying storage capacity.
The whole model is split into different phases. It consists of a model setup in which the optimization problem is defined, and has a two-step solution procedure to analyze the given input scenarios. It will first execute the strategy phase to calculate storage values for each possible deterministic scenario which are weighted based on the stochastic probability, and then simulate a sequential performance in the simulation phase.
The results for a deterministic setup showed that the model manages to create a detailed storage value curve when the number of discretized points are kept at a reasonable amount. This also kept the accuracy of the simulation phase reasonably good. However, the accuracy and performance of the strategy phase struggled to be consistent when the capacity of the storage unit increased. This deviation decreased when changing to a stochastic setup, since all possible scenarios affected each other, and several of these scenarios performed better when the price variation increased.
In overall, the storage unit scheduling model has shown good performance and can be a useful option for analyzing storage units from a stochastic point of view when considering multiple markets
Analysing the Impact of 30 GW Offshore Wind Power in Norway using the Market Model FanSi
No full textI mai 2022 la den norske regjeringen frem en plan om å identifisere områder for 30 GW havvind innen 2040. Det ambisiøse havvind-initiativet vil betydelig øke Norges grønne energiproduksjon, noe som vil resultere i en mer robust energibalanse og opprettholde landets posisjon innenfor energiindustrien. Den betydelige økningen i vindkraftproduksjonen vil imidlertid ha konsekvenser for det norske kraftsystemet, som må være tilstrekkelig forberedt på denne økte kraftproduksjonen. En utfordring ligger i å håndtere den variable kraftproduksjonen forårsaket av vindkraft. Fleksibel vannkraftproduksjon antas å spille en viktig rolle i å støtte kraftsystemet mot den variable vindkraftproduksjonen.
Denne masteroppgaven har som mål å undersøke virkningen av 30 GW havvind på det norske kraftsystemet. I tillegg vil betydningen av plasseringen av vindparkene analyseres ved å undersøke tre forskjellige fordelinger av havvindkapasiteten i Norge. Analysen benytter seg av et datasett som representerer et scenario for det nord-europeiske kraftsystemet i 2030. Fem havvind-scenarioer for Norge simuleres: ett med null produksjon, et med 4,5 GW i sør, og tre scenarioer med 30 GW fordelt over ulike regioner i landet. Havvindproduksjonen overføres direkte til det nærmeste området på land uten noen tilsvarende endringer i det norske strømnettet eller kraftbehovet. Simuleringene er utført ved bruk av to ulike sett med vindserier for å analysere og sammenligne de nylig genererte vindseriene fra SINTEF Energi med vindseriene som er inkludert i datasettet.
Scenarioene er simulert ved bruk av den fundamentale markedmodellen FanSi. FanSi er en langtids hydro-termisk planleggingsmodell utviklet ved SINTEF Energi. Modellen bruker en metode kalt "Scenario-vifte simulator" som løser sekvenser av stokastiske optimeringsproblemer. FanSi beregner individuelle vannverdier for hvert reservoar i stedet for aggregerte vannverdier slik som i den mye brukte EMPS-modellen. Dette muliggjør en mer detaljert representasjon av vannkraftsystemet, som har vist seg å være gunstig for å håndtere svingninger i uregulert kraftproduksjon.
Studiens funn viser hvordan en betydelig økning i vindkraftproduksjon vil påvirke det norske kraftsystemet. Økende vindkraftproduksjon vil gi en nedgang i kraftpriser. En øking på 30 GW havvindproduksjon i Norge fører til hyppigere flaskehalser i overføringsnettet, noe som understreker viktigheten av å samkjøre vindkraftutvikling med overføringskapasitet og kraftbehov. Fleksibilitetsfaktoren for vannkraft øker for mer vindkraft i systemet, noe som demonsterer vannkraftens evne til å komplimentere vindkraftproduksjonen. Det samfunnsøkonomiske overskuddet for driften av kraftsystemet påvirkes positivt av økt vindkraftproduksjon i systemet, primært drevet av økt forbrukeroverskudd og større overskudd for systemansvarlig i kraftsystemet (TSO). Å fordele vindparkene over et større område fører til høyere samfunnsøkonomisk overskudd sammenlignet med å konsentrere dem i et mindre område.
De nye vindseriene resulterer i økt vindkraftproduksjon sammenlignet med vindserien som opprinnelig var inkludert i datasettet. Dette påvirket resultatene i scenario-studiet, og understreker dermed viktigheten av nøyaktige vindserier i simuleringer som involverer store mengder vindkraftproduksjon. I arbeidet med simuleringene ble det rettet spesielt fokus på sluttverdiinnstillingen i FanSi, som blir beregnet ved hjelp av vannverdiberegning i EMPS. Det ble oppdaget at disse vannverdiene var overdrevent høye for store mengder vindkraftproduksjon i systemet. Selv om det ble identifisert og implementert en forenklet løsning for simuleringene som er gjennomført i dette prosjektet, fremhever dette funnet behovet for videre analyser knyttet til sluttverdiinnstillingen.In May 2022, the Norwegian government presented a plan to identify areas for 30 GW offshore wind power before 2040. The ambitious offshore wind initiative will significantly boost Norway's green energy production, resulting in a more robust energy balance and maintaining the country's position in the energy industry. However, the substantial increase in wind power production will have a significant impact on the Norwegian power system, which must be adequately prepared to accommodate this increased power production. A considerable challenge lies in managing the variable power generation caused by intermittent wind power. Flexible hydropower production is expected to play a key role in supporting the power system to cope with variability.
This master’s thesis aims to investigate the impact of 30 GW offshore wind power on the Norwegian power system. Moreover, three different allocations of wind power capacity are analyzed to examine the impact of wind farm locations. The analysis utilizes a dataset representing a scenario for the Northern European power system in 2030. Five offshore wind scenarios in Norway are simulated, including one with zero production, another with 4.5 GW in the south, and three scenarios with 30 GW distributed across various regions of the country. The offshore wind production is directly transmitted to the nearest onshore area without any corresponding modifications made to the transmission system or power demand. Two sets of wind series are employed in the simulations to analyze and compare the recently generated wind series by SINTEF Energy Research with the original wind series initially included in the dataset.
The scenarios are simulated using the fundamental market model FanSi. FanSi is a long-term hydro thermal scheduling model developed at SINTEF Energy. The model utilizes a method called "Scenario Fan simulator", which solves sequences of stochastic optimization problems. FanSi computes individual water values for each reservoir instead of aggregated water values as in the widely used EMPS model. This allows for a more detailed representation of the hydropower system, which has shown to be beneficial regarding handling fluctuations in unregulated generation.
The findings of the study demonstrate the significant impact of substantial wind power production on the Norwegian power system. The results clearly indicate a noticeable decrease in area prices with increasing wind power production. The installation of 30 GW offshore wind capacity leads to a higher frequency of bottlenecks in the transmission system, highlighting the importance of aligning wind power developments with transmission capacity and power demand. The increased value factors for hydropower plants signify their ability to complement wind power generation and contribute to system balancing. Finally, the result reveals that social welfare from operating the power system is positively impacted by greater wind power production in the system, primarily driven by increased consumer surplus and surplus of the Transmission System Operator. Distributing the wind farms in a larger area leads to higher social welfare compared to concentrating them.
The new wind series results in increased wind power production compared to the wind series initially included in the dataset. This had a considerable impact on the results obtained from the simulations, highlighting the significance of accurate wind series in simulations involving large shares of wind power production. Furthermore, particular emphasis is placed on the end value setting in FanSi, obtained from water value calculation in the EMPS model. It was found that these water values were excessively high for large amounts of wind power production in the system. While a simplified solution was identified and implemented for the simulations conducted in this thesis, these findings emphasize the importance of further investigations into this issue
Integrating Variable Wind Power Using a Hydropower Cascade
No full textAbstractIn this paper, we examine the ability of a hydropower cascade to balance variability from wind power. We consider a coordinated hydro-wind system that satisfies a single power balance, and we use a real-time control scheme to optimize system operations such that wind and load curtailment is minimized. The control scheme considers system hydraulics (including dynamic tailrace elevations and water travel times) and system constraints. Generation from an individual hydropower plant is modeled using a convex piecewise planar approximation. We give results from a case study involving hydro and wind power in the Pacific Northwest region of the United States. The objective of this paper is to present a framework for evaluating how the regulation of wind generation affects hydropower operations. Our intention is to use this framework in future work to perform a systematic study of balancing capability across different hydraulic conditions, system constraints, and wind generation scenarios
Analysis of Power System Scenarios for Norway 2030 using the Fundamental Market Model FanSi
No full textDet siste tiåret har Norges rolle i det Europeiske kraftmarkedet vært omdiskutert. Det har vært en enorm økning i Norske strømpriser det siste året grunnet lave vannstander i magasinene i tillegg til at Norge er koblet på det europeiske kraftnettet. Fremtiden er usikker. Det er forventet en økning i energibehov i alle sektorer samtidig som målet er null utslipp innen 2050. Innføringen av mer variabel fornybar energi i elektrisitetsmiksen gir et behov for bedre optimaliseringsverktøy som kan håndtere mer usikkerhet.
Langtidsmodellen FanSi er utviklet av SINTEF Energi. Den baserer seg på et konsept som benytter historisk værdata representert ved scenarioer til å modellere fremtidige værscenarioer. Et velkjent planleggingsverktøy EMPS benytter en aggregert representasjon av magasinene. FanSi aggregerer ikke magasin, noe som fører til en drastisk økning i beregningstiden. På den andre siden er dette en modell som er bedre rustet til å håndtere usikkerhet da modellen har en bedre utnyttelse av kortsiktig fleksibilitet.
Denne oppgaven undersøker to ulike aspekter ved FanSi. Det ene aspektet som er undersøkt angår den tekniske modellen og hvordan valget av parametere kan optimalisere simuleringen av et datasett. Det er valgt to parametere til å gjennomføre undersøkelsen. Disse er henholdsvis antall scenarioer og antall uker i scenarioviften. Det andre aspektet som er vurdert er å bruke FanSi som et analyseverktøy for å forstå utfallet av ulike endringer på det Nordeuropeiske kraftsystemet. Analysen tar for seg høye brenselpriser, en høy rasjoneringspris, fjerning av sjøkablene tilkoblet Norge og en økning i kapasiteten på linjene mellom Norge og Storbritannia. I tillegg benytter denne oppgaven FanSi til å diskutere fremtidige energisituasjoner i Norge, hvor de ulike scenarioene presentert blir kjørt på ulike datasett hvor Norge er både i en underskudds- og overskuddssituasjon. Datasettet som er brukt i analysen er laget av SINTEF Energi og representerer en mulig energisituasjon i 2030.
Å finne den optimale parametriseringen er viktig når vannverdier skal beregnes og vil i hovedsak påvirke områder med en stor andel vannkraft i produksjonsporteføljen, slik som Norge. Fra å analysere ulike parametriseringer viser denne oppgaven at å øke antall scenarioer i scenarioviften i alle tilfeller vil gi lavere områdepriser og et bedre samfunnsøkonomisk overskudd, uten å gi en drastisk økning i beregningstid. Å øke brenselprisen har den største effekten på det Nordeuropeiske kraftsystemet sammenlignet med de andre scenarioene og resulterer i ekstreme områdepriser og et lavere samfunnsøkonomisk overskudd. En økning i kapasiteten mellom Norge og Storbritannia minsker flaskehalser i det Nordeuropeiske kraftsystemet, noe som resulterer i et høyere samfunnsøkonomisk overskudd. Områdeprisene i Norge vil oppleve en liten økning mens resten av Europa får en reduksjon i prisene. Å fjerne sjøkablene tilkoblet Norge er gunstig for de norske områdeprisene i et overskuddsscenario, men vil gi ekstreme priser om situasjonen er underskudd. Resultatene underbygger hvordan sjøkabler mellom Norge og Europa er en viktig del av det Nordeuropeiske systemet ved å utjevne strømpriser og ved å fungere som en forsyningssikkerhet i kritiske perioder.There have been discussions about Norway’s role in the European power market in the last decade. Norwegian area prices have skyrocketed in the last year due to an interconnected power system and low inflow to the reservoirs. The future is uncertain. There is expected to be an increase in energy demand in all sectors, while the aim is to be net-zero by 2050. The introduction of more variable renewable energy to the electricity mix creates the need for better optimization tools that can handle more uncertainty.
FanSi is a long-term hydro-thermal scheduling model developed by SINTEF Energy Research. It is built on a concept that uses historical records for inflow represented as scenarios to model possible future weather year scenarios. A widely used scheduling model, EMPS, uses an aggregated reservoir representation. FanSi does not aggregate reservoirs, which increases the computational time drastically. On the other hand, it better models short-term flexibility and is a model better equipped to handle uncertainty.
This thesis assesses two different aspects of FanSi. A feature investigated is the technical model and how to optimize datasets through parameters used when running FanSi. An assessment of two parameters, respectively, the number of scenarios and the number of weeks in the scenario fan, is done. The second aspect investigated is using FanSi as an analysis tool to understand the consequences of different changes to the North-European power system. The analyzed cases are high fuel prices, a high rationing price, removing the subsea cables from Norway, and increasing the capacity from Norway to Great Britain. In addition, this thesis utilizes FanSi to elaborate on future energy situations in Norway, running the scenarios presented above on Norway in scarcity and Norway in surplus situations. SINTEF Energy Research has provided the dataset used for the analysis, representing a possible power situation in 2030.
Finding the optimal parametrization is crucial when calculating water values and will mainly affect hydropower-based areas like Norway. From analyzing different parametrizations, this thesis shows how increasing the number of scenarios for all cases gives lower Norwegian area prices and better social welfare without compromising run time. Increasing the fuel prices has the most extensive significance on the North-European system compared to the other scenarios, resulting in extreme area prices and lower social welfare. Scaling up the capacity between Great Britain and Norway relieves the Northern European system of bottlenecks, resulting in higher social welfare. While prices in Norway experience a slight increase, the rest of the European areas obtain a price reduction. Removing the subsea cables out of Norway is beneficial for Norway in a surplus situation but results in extreme power prices in a scarcity situation. The results show how the subsea cables have an essential role in the North-European system, equalizing prices and functioning as a security of supply for Norway in critical periods
Stochastic daily hydrothermal scheduling based on decomposition and parallelization
No full textThis paper studies the stochastic short term hydrothermal scheduling of systems that have a significant contribution from controllable reservoirs, focusing on the reservoirs´ operation policy when non-linearity and deployment of supplementary reserves at the real operation stage are modeled. Wind power and forced outages of power plants and transmission lines are treated as stochastic variables, and the total reserve is an endogenous variable to the model. The problem includes cascaded hydro systems with head-sensitive plants, a DC power flow representation with nonlinear transmission losses, and four types of operating reserves; and it aims at pre-positioning generation and reserves schedules in the light of the expected deployment of operating reserves throughout the day. To solve the optimization problem, a hybrid scheme elaborated from outer approximation and Benders decomposition is applied. The proposed solution method is tested in a real size system, where its effectiveness, in terms of computational peed and accuracy, is demonstrated.Fil: López Salgado, Carlos Josue. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Helseth, Arild. Norwegian University Of Science And Technology. Faculty Of Information Technology And Electrical Engineering.; NoruegaFil: Ojeda Esteybar, Diego Mauricio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; ArgentinaFil: Año, Osvaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentin
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