Šis darbas nagrinėja naujas, lanksčias energijos efektyvumą skatinančias priemones, kurios paremtos rinką imituojančiais mechanizmais. Baltieji sertifikatai yra visiškai naujas mechanizmas, gyvuojantis tik nedaugelyje šalių. Energijos efektyvumo skatinimas yra tiesiogiai susijęs su ekologija, aplinkosauga, todėl priemonių skatinančių taupyti ir efektyviai naudoti energiją labai trūksta ir jų įvedimas į rinką yra labai aktualus. / This job deals with modeling the effects of introducing a market-based tool for improving end-users’ efficiency in an energy market which is already regulated through a cap-and-trade system for green house gas emissions and a quota system meant to improve competitiveness of energy produced using renewable resources. Our results show that the regulation of energy demand achieves its underlying objects of energy savings and energy efficiency solely at the expense of other goals such as the environmental efficiency of energy production. In our model, the implementation of a market for White Certificates (WCTS) causes energy producers’ investment in abatement to decrease along with the price for Brown Certificates and the amount of renewable energy demanded. Once we turn to the currently more empirically relevant case of integrating endusers only partially into WCTS, the unregulated group compensates in parts for the decrease in demand of the regulated group, due to an indirect price effect. As both supply and demand side of the market are regulated, this special set of regulations applied can, therefore, be compared to the grip of printers embracing the entire market, leaving some of it virtually scarred. Consequently, we intended to search for alternative policy measures, which are able to achieve an increase in endusers’ energy efficiency without the negative side-effects witnessed in case of a WCTS. In our model a subsidized reduction in the price for households’ investment... [to full text]

Made available in DSpace on 2016-08-17T14:52:47Z (GMT). No. of bitstreams: 1 Anselmo Rodrigues.pdf: 589170 bytes, checksum: 7eda1a9d5bbe5a0ef8355bc4c4d26ca8 (MD5) Previous issue date: 2003-08-15 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The restructuring of the electricity industry has caused an increase in the number of commercial transactions carried out in energy markets. These transactions are defined by market forces without considering the operational constraints of the transmission system. As a consequence, there are transactions that cause congestion in the transmission network, that means, violations of operational limits in one or more circuits of the transmission system. In this way, the congestion in the transmission system must be eliminated by using corrective actions, such as redispatch of generation/transactions and operation of control flow devices, to avoid cascading outages with uncontrolled loss of load. Currently, the majority of methodologies used in congestion management are based on deterministic models. It has been justified because of the complexity associated with the application of probabilistic models in generation/transmission systems. Nevertheless, some models have been developed to carry out probabilistic analysis of the congestion management. Usually, they are based on the Monte Carlo Method with nonsequential simulation and they only include bilateral transactions. However, multilateral transactions are also essential for the existence of the energy markets. The multilateral transactions reduce the financial risks associated with commercial transactions and allow the customers to have access to the energy providers. Additionally by ignoring multilateral transactions, the existing probabilistic models for the congestion management include only not-free-cost corrective actions, such as generation redispatch and transaction curtailments. On the other hand, free-cost corrective actions, such as phase shifting transformers and FACTS devices, can provide low cost solutions to eliminate congestion in interconnections of the transmission system. This condition is caused by the delay in carrying out reinforcements in the transmission systems due to financial and environmental constraints. Finally, it must be noted that only probabilistic indices based in expected values are evaluated by the probabilistic models of congestion management. However, system operators have difficulty in interpreting probabilistic indices based only in expected values. Therefore, it is necessary to develop new indices to carry out probabilistic analysis of congestion management. These new indices must consider traditionally accepted operational criteria and they must be easily interpreted by the system operators. This research has as its objective the development of models and techniques to carry out the probabilistic analysis of congestion management. The proposed models and techniques consider the following aspects associated with congestion management: the modeling of multilateral transactions, phase shifting transformers and the definition of Well-Being Indices to assess the reliability of the commercial transactions. These indices, allow the establishment of a link between the operational criteria traditionally used and the stochastic model of the electrical network. The models and indices, proposed in this research, have been based on the Monte Carlo Method with non-sequential simulation and in the linearized optimal power flow. The optimal power flow problems associated with the congestion management have been solved using the Primal-Dual Interior-Point Method. The practical application and the validation of the models and indices proposed in this research have been carried out in two systems: the IEEE System, proposed in 1996, for Reliability Studies. The main conclusions obtained with the application of the proposed models and techniques in the IEEE system are: multilateral congestion management can improve the reliability of commercial transactions, load profiles have significant effects on the Well-Being indices of the transactions, the base case condition has great impact in the Well-Being indices associated with a set of transactions and the operation of phase-shifting transformers and can decrease significantly the curtailments in the commercial transactions. / A reestruturação da indústria de eletricidade causou um aumento no número de transações comerciais efetuadas em mercados de energia. Estas transações são definidas por forças de mercado sem considerar restrições operacionais do sistema de transmissão. Consequentemente existem transações comerciais que causam congestão no sistema de transmissão, ou seja, resultam em violações de limites operacionais em um ou mais circuitos do sistema de transmissão. Desta forma, a congestão no sistema de transmissão deve ser eliminada usando-se ações corretivas, tais como redespacho de geração/transações e operação de dispositivos de controle de fluxo, para evitar contingências em cascata com perda de carga descontrolada. Atualmente, a maioria das metodologias usadas no gerenciamento da congestão se baseia em métodos determinísticos. Isto tem sido justificado devido a complexidade associada com a aplicação de modelos probabilísiticos em sistemas de geração/transmissão. Apesar disto, alguns modelos foram desenvolvidos para realizar uma análise probabilística do gerenciamento da congestão. Estes modelos geralmente se baseiam no método de Monte Carlo com Simulação Não-Sequencial e somente incluem transações bilaterais. Entretanto, transações multilaterais são também de grande importância para a existência dos mercados de energia. Os contratos multilaterais reduzem os riscos financeiros associados com transações comerciais e permitem que os consumidores tenham acesso aos fornecedores de energia. Além de não considerarem transações multilaterais, os modelos probabilísticos existentes para o gerenciamento da congestão somente incluem ações corretivas não-livres de custo, tais como redespacho da geração e cortes nas transações. Por outro lado, ações corretivas livres de custo, tais como transformadores defasadores e dispositivos FACTS, podem fornecer soluções de baixo custo para eliminar a congestão nas interligações do sistema de transmissão. Esta condição é causada pelo atraso na realização de reforços no sistema de transmissão devido a restrições financeiras e ambientais. Finalmente, observa-se que apenas índices probabilísticos que se baseiam em valores esperados são calculados pelos modelos probabilísticos de gerenciamento da congestão. Entretanto, operadores do sistema tem dificuldade em interpretar índices probabilísticos que se baseiam em valores esperados. Devido a isto, é necessário desenvolver novos índices para realizar uma análise probabilística do gerenciamento da congestão. Estes novos índices devem considerar critérios de avaliação tradicionalmente aceitos e serem facilmente interpretados pelos operadores do sistema. Este trabalho de pesquisa tem como objetivo desenvolver modelos e técnicas para realizar a análise probabilística do gerenciamento da congestão. Os modelos e técnicas propostos neste trabalho consideraram os seguintes aspectos associados com o gerenciamento da congestão: modelagem de transações multilaterais e transformadores defasadores no gerenciamento da congestão e a definição de índices de robustez para analisar a confiabilidade das transações comerciais. Estes índices permitem estabelecer um elo entre critérios de operação tradicionalmente usados e a modelagem probabilística da rede elétrica. Os modelos e índices propostos neste trabalho de pesquisa se baseiam no Método de Monte Carlo com simulação não-sequencial e no fluxo de potência ótimo linearizado. Os problemas de fluxo de potência ótimo associados com o gerenciamento da congestão foram resolvidos usando-se o Método de Pontos-Interiores Primal-Dual. A aplicação prática e validação dos modelos e índices propostos nesta pesquisa foi realizada através de diversos testes no sistema IEEE, proposto em 1996, para estudos de confiabilidade. As principais conclusões obtidas com a aplicação dos modelos e técnicas propostos no sistema IEEE são: o gerenciamento da congestão multilateral pode aumentar a confiabilidade das transações comerciais, perfis de carga tem efeitos significativos nos índices de robustez das transações comerciais, a condição do caso base tem grande impacto nos índices de robustez associados com um conjunto de transações e a operação de transfotmadores defasadores pode diminuir significativamente as interrupções nas transações comerciais.

Models and simulators have been widely used in urban contexts for many decades. The drawback of most current models is that they are normally designed for specific objectives, so the elements considered are limited and they do not take into account the potential synergies between related systems. The necessity of a framework to model complex smart city systems with a comprehensive smart city model has been remarked by many authors. Therefore, this PhD thesis presents: i) a general conceptual framework for the modelling of energy related activities in smart cities, based on determining the spheres of influence and intervention areas within the city, and on identifying agents and potential synergies among systems, and ii) the development of a holistic energy model of a smart city for the assessment of different courses of action, given its geo-location, regulatory and technical constraints, and current energy markets. This involves the creation of an optimization model that permits the optimal planning and operation of energy resources within the city. In addition, several analyses were carried out to explore different hypothesis for the smart city energy model, including: a)      an assessment of the importance of including network thermal constraints in the planning and operation of DER systems at a low voltage distribution level, b)      an analysis of aggregator’s market modelling approaches and the impact on prices due to DER aggregation levels, and c)      an analysis of synergies between different systems in a smart city context. Some of the main findings are: It is sensible to not consider network thermal constraints in the planning of DER systems. Results showed that the benefit decrement of considering network constraints was approximatively equivalent to the cost of reinforcing the network when necessary after planning without considering network constraints. The level of aggregation affects the planning and overall benefits of DER systems. Also, price-maker approaches could be more appropriate for the planning and operation of energy resources for medium to large aggregation sizes, but could be unnecessary for small sizes, with low expected impact on the market price. Synergies between different energy systems exist in an interconnected smart city context. Results showed that the overall benefits of a joint management of systems were greater than those of the independently managed systems. Lastly, the smart city energy model was applied to a case study simulating a real smart city implementation, considering five real districts in the southern area of Madrid, Spain. This analysis allowed to assess the potential benefits of the implementation of a real smart city programme, and showed how the proposed smart city energy model could be used for the planning of pilot projects. To the best of our knowledge, such a smart city energy model and modelling framework had not been developed and applied yet, and no economic results in terms of the potential benefits of such a smart city initiative had been previously reported. / <p>QC 20171010</p>

This master thesis approaches the energy markets from the point of view of an electricity trader acting on the retail markets, in particular an electricity supplier to the end customers. The first part introduces the reader into the basic practices applied in the management process of the portfolio of end customers, which includes metering and evaluation of the real take-off, planning and prediction and, of course, final evaluation of the imbalances. Second part explains the principles of balance management in case of the entire ČEPS electrical grid, mechanics of the imbalances settlement and describes its actual setting with focus on the way it motivates the market participants for minimization of their own imbalances and therefore improvement of the overall electrical grid balance. The final part describes the basic construction of the risk surcharges, which the supplier adds to the commodity price to cover the costs caused by the existence of his end customers' imbalances. Furthermore, it is shown how the dependence on the system imbalance influences the size of the risk surcharge and the basic model is extended to include even this factor. Because the supplier does not set the surcharge at the level of individual end customer but for the entire portfolio, the functioning and power of the portfolio effect, which brings an extra savings in the imbalances settlement costs, is also explored in the final part. The possibility of dependence presence in the imbalances of individual end customers is also accounted for. For the first time in the Czech academic literature the economic problems that are faced by the electricity supplier to the end customers are examined and the analysis and solution of one important problem is provided in the full picture. However, the most important contribution of this master thesis lays in the opening of this topic to further examination on the academic ground.

Cette thèse porte sur la valorisation et les stratégies financières de couverture des risques dans les marchés de l'énergie. Ces marchés présentent des particularités qui les distinguent des marchés financiers standards, notamment l'illiquidité et l'incomplétude. L'illiquidité se reflète par des coûts de transactions importants et des contraintes sur les volumes échangés. L'incomplétude est l'incapacité de pouvoir répliquer parfaitement des produits dérivés. Nous nous intéressons à différents aspects de l'incomplétude de marché. La première partie porte sur la valorisation dans les modèles de Lévy. Nous obtenons une formule approximative du prix d'indifférence et nous mesurons la prime minimale à apporter par rapport au modèle de Black-Scholes. La deuxième partie concerne la valorisation d'options spread en présence de corrélation stochastique. Les options spread portent sur la différence de prix entre deux sous-jacents -- par exemple gaz et électricité -- et sont très utilisées sur les marchés de l'énergie. Nous proposons une procédure numérique efficace pour calculer le prix de ces options. Enfin, la troisième partie traite de la valorisation d'un produit comportant un risque exogène dont il existe des prévisions. Nous proposons une stratégie dynamique optimale en présence de risque de volume, et l'appliquons à la valorisation des fermes éoliennes. De plus, une partie est consacrée aux stratégies optimales asymptotiques en présence de coûts de transactions. / This thesis tackles three issues on pricing and hedging in energy markets. Energy markets differ from financial markets mainly in two ways: illiquidity and incompletness. Illiquidity (or lack of liquidity) translates into transaction costs and volume constraints. Incompletness means incapacity to perfectly hedge derivatives. We study different aspects of incomplete markets. First, we focus on indifference pricing in exponential Lévy models. We obtained an approximate formula by considering a Lévy process as a perturbed Brownian motion. That way we obtain the minimal correction from Black-Scholes price. Second, we present a numerical procedure to price spread options when underlyings are stochastically correlated. These options are very popular in energy markets, underlyings being for instance gas and electricity. Third, we derive optimal strategies using exogeneous factors forecasts. We exhibit an explicit pricing formula and an optimal strategy handling volume risk and apply it to wind farms valuation. Finally, a short review of optimal strategies taking into account transaction costs is made

Sweden has developed ambitious goals regarding energy and climate politics. One major goal is to change the entire electricity production from fossil fuels to sustainable energy sources, this will contribute to Sweden being one of the first countries in the world with non-fossil fuel in the electricity sector. To manage this, major changes need to be implemented and difficulties on the existing grid will occur with the expansion of digitalization, electrification and urbanization. By using smart grids, it is possible to deal with these problems and change the existing electricity grid to use more distributed power generation, contributing to flexibility, stability and controllability. The goal with smart grids is to have a sustainable electricity grid with low losses, security of supply, environmental-friendly generation and also have choices and affordable electricity for customers. The purpose of this project is to identify and evaluate several indicators for a smart grid, how they relate and are affected when different scenarios with different technologies are implemented in a test system. Smart grid indicators are quantified metrics that measure the smartness of an electrical grid. There are five scenarios where all are based on possible changes in the society and electricity consumption, these scenarios are; Scenario A – Solar power integration, Scenario B – Energy storage integration, Scenario C – Electric vehicles integration, Scenario D – Demand response and Scenario E – Solar power, Energy storage, Electric vehicles and Demand response integration. A model is implemented in MATLAB and with Monte Carlo simulations expected values, standard deviation and confidence interval were gained. Four selected indicators (Efficiency, capacity factor, load factor and relative utilization) was then analyzed. The results show that progress on indicators related to all smart grid characteristics is needed for the successful development of a smart grid. In scenario C, all four selected indicators improved. This shows that these indicators could be useful for promoting the integration of electric vehicles in an electricity grid. In Scenario A, solar power integration contributed to all indicators deteriorate, this means that, technical solutions that can stabilize the grid are necessary to implement when integrating photovoltaic systems. The load factor is a good indicator for evaluating smart grids. This indicator can incentivize for an even load and minimize the peak loads which contributes to a flexible and efficient grid. With the capacity factor, the utilization and free capacity can be measured in the grid, but it can counteract renewable energy integration if the indicator is used in regulation.

No description available.

The traditional electricity market, holding centralized authority over consumers, is no longer adequate seeing a shift towards a more electrified, decentralized, and digitalized society. Increased energy prices, raising concerns about climate change, and tightening governmental regulations have resulted in that an extensive diffusion of renewable energy sources has evolved. This development is expected to change the structure of the sector, despite that an appropriate market design that can deal with these remains to be identified. The purpose of this study was to investigate how a business model of a digital platform, managing energy trading within a local community could be designed. This study contributes to a new dimension of energy transitions within a Multi-Level Perspective by studying a particular field of the transition in terms of flexibility market platforms. The rising need for flexible solutions, making the consumer a prosumer, and enabling shared energy through a digital platform involves uncertainty and challenges, where a suitable business model linking new technology to the emerging market needs to be defined. Despite the novelty of the research field of local energy markets, the aim of investigating business model designs for a local energy market platform has been reached through an exploratory case study and integration of theories from several fields. This study makes an analytical contribution of investigating five pioneering projects, all developing digital platforms enabling integration of flexibility into the electricity market. This further contributes to the design-implementation gap of theories when developing a local energy market, by suggesting the most vital parameters to take into account. Based on the findings, a suggestion on a suitable business model design and a corresponding market design was developed. The main objective of the proposed market design is to serve as a basis to bring forward flexibility available from prosumers and their controllable demand and supply arrangement, including renewable energy technology generation and storage devices. The intention is to maintain a balanced and transparent distribution network at the lowest possible costs, while, at the same time functioning as reserve storage towards the main grid, reducing the risk of capacity shortage. Additional insights were raised that can be helpful in the evaluation of utilizing flexibility energy assets before making grid investments, following the recently presented recommendation of the EU's Clean Energy package. / Den traditionella elmarknaden, karaktäriserad av en centraliserad styrning, är inte längre hållbar då utvecklingen av marknaden går mot ett allt mer elektrifierat, decentraliserat och digitaliserat samhälle. Ökande energipriser, växande oro för klimatfrågor tillsammans med en allt snävare reglering av energimarknaden har resulterat i en omfattande ökning av förnybara energikällor. Denna utveckling förväntas förändra sektorns struktur, där en lämplig marknadsdesign som kan hantera detta återstår att identifiera. Syftet med denna studie var att undersöka hur en affärsmodell för en digital plattform, anpassad för att hantera lokal energidelning, kan utformas. Denna studie bidrar till en ny dimension av energitransformationen från ett multi-nivå-perspektiv genom att studera ett särskilt område av övergången i form av flexibla marknadsplattformar. Det ökande behovet av flexibla lösningar, där konsumenter blir prosumenter och energi delas lokalt via digitala plattform innebär osäkerheter och utmaningar. En lämplig affärsmodell som kan anknyta de nya tekniska lösningarna som krävs till lokala energimarknader bör därav definieras. Trots att forskningsområdet som berör lokala energimarknader kan anses relativt nytt och delvis outforskat, har målet att undersöka affärsmodellkoncept för en lokal energimarknadsplattform uppnåtts genom en fallstudie och iterationer av teorier inom flertalet områden. Denna studie bidrar med en analytisk undersökning av fem innovativa projekt som alla utvecklar digitala plattformar för att möjliggöra integrering av flexibilitet till elmarknaden. Detta bidrar även till det kunskapsgap som har identifierats mellan design och implementering fas vid utvecklandet av lokala energimarknader, genom föreslagna parameter som anses grundläggande och som bör tas hänsyn till. Baserat på resultatet presenterades ett förslag på en lämplig design för affärsmodell samt en tillhörande marknadsdesign. Huvudsyftet med den föreslagna marknadsdesignen är att utgöra en grund för gynnandet av en mer flexibel elektricitet hantering. Detta möjliggörs genom introduktionen av prosumenter till marknaden, där allt mer elektricitet produceras från förnybara källor och där konsumtion samt produktion regleras med hjälp av integrerade lagringsenheter. Målet är att upprätthålla ett balanserat och transparent distributionsnät till lägsta möjliga kostnad, medan marknaden även fungerar som ett reservlager mot kraftnätet, vilket minskar risken för kapacitetsbrist runt om i Sverige. Ytterligare insikter från denna studie påvisar hur de befintliga energitillgångarna kan utnyttjas på ett mer flexibelt och effektivt sätt, vilka stöds av de nyligen presenterade rekommendationerna från EU:s Clean Energy-paket.

Mycorrhizal Networks (MNs) facilitate the exchange of resources including energy, water, nutrients, and information between trees and plants in forest ecosystems. This work explored MNs as an inspiration for new market models in transactive energy networks, which similarly involve exchanges of energy and information between buildings in local communities. Specific insights from the literature on the structure and function of MNs were translated into an energy model with the aim of addressing challenges associated with the proliferation of distributed energy resources (DERs) at the grid edge and the incorporation of DER aggregations into wholesale energy markets. First, a systematic review of bio-inspired computing interventions applied to microgrids and their interactions with modern energy markets established a technical knowledge base within the context of distributed electrical systems. Second, a bio-inspired design process built on this knowledge base to yield a structural and functional blueprint for a computational mycorrhizal energy market simulation. Lastly, that computational model was implemented and simulated on a blockchain-compatible, multi-agent software platform to determine the effect that mycorrhizal strategies have on transactive energy market performance. The structural translation of a mapped ectomycorrhizal network of Douglas-firs in Oregon, USA called the 'wood-wide web' created an effective framework for the organization of a novel mycorrhizal energy market model that enabled participating buildings to redistribute percentages of their energy assets on different competing exchanges throughout a series of week-long simulations. No significant changes in functional performance –- as determined by economic, technical, and ecological metrics – were observed when the mycorrhizal results were compared to those of a baseline transactive energy community without periodic energy asset redistribution. Still, the model itself is determined to be a useful tool for further exploration of innovative, automated strategies for DER integration into modern energy market structures and electrical infrastructure in the age of Web3, especially as new science emerges to better explain trigger and feedback mechanisms for carbon exchange through MNs and how mycorrhizae adapt to changes in the environment. This dissertation concludes with a brief discussion of policy implications and an analysis applying the ecological principles of robustness, biodiversity, and altruism to the collective energy future of the human species. / Doctor of Philosophy / Beneath the forest floor, a network of fungi connects trees and plants and allows them to exchange energy and other resources. This dissertation compares this mycorrhizal network (mycorrhiza = fungus + root) to a group of solar-powered buildings generating energy and exchanging it in a local community marketplace (transactive energy markets). In the analogy, the buildings become the plants, the solar panels become the leaves, and the electrical grid represents the mycorrhizal network. Trees and plants produce their own energy through photosynthesis and then send large portions of it down to the roots, where they can trade it or send it to neighbors via the mycorrhizal network. Similarly, transactive energy markets are designed to allow buildings to sell the energy they produce on-site to neighbors, usually at better rates. This helps address a major infrastructure challenge that is arising with more people adding roof-top solar to their homes. The grid that powers our buildings is old now and it was designed to send power from a central power plant out to its edges where most homes and businesses are located. When too many homes produce solar power at the same time, there is nowhere for it to go, and it can easily overload the grid leading to fires, equipment failures, and power outages. Mycorrhizal networks solve this problem in part through local energy balancing driven by cooperative feedback patterns that have evolved over millennia to sustain forest ecosystems. This work applies scientific findings on the structure and function of mycorrhizal networks (MNs) to energy simulation methods in order to better understand the potential for building bio-inspired energy infrastructure in local communities. Specifically, the mapped structure of a MN of douglas-fir trees in Oregon, USA was adapted into a digital transactive energy market (TEM) model. This adaptation process revealed that a single building can connect to many TEMs simultaneously and that the number of connections can change over time just as symbiotic connections between organisms grow, decay, and adapt to a changing environment. The behavior of MNs in terms of when those connections are added and subtracted informed the functionality of the TEM model, which adds connections when community energy levels are high and subtracts connections when energy levels are low. The resulting 'mycorrhizal' model of the TEM was able to change how much energy each connected household traded on it by changing the number of connections (more connections mean more energy and vice versa). Though the functional performance of the mycorrhizal TEM did not change significantly from that of a typical TEM when they were the context of decentralized computer networks (blockchains) and distributed artificial intelligence. A concluding discussion addresses ways in which elements of this new model could transform energy distribution in communities and improve the resilience of local energy systems in the face of a changing climate.

In September 2017, Luleå Energi introduced a new price model on district heating for their enterprise customers with the intention to create stronger incentives for energy efficiency measures, and provide price signals that better correspond to the underlying production costs. The purpose of this thesis is to investigate whether the intentions of Luleå Energi has been fulfilled, not the least in the form of improved energy efficiency among the affected enterprises. This thesis also provides a theoretical assessment of the new price model through conducting a literature review. The empirical analysis builds on theories addressing issues such as bounded rationality, profit maximizing firms, uncertainty, and imperfect information. The results show that the new price model may have been hindered by bounded rationality amongst the enterprise customers, and the overall low price level of district heating services in Luleå. Results also show that even if the new price model is fairly good at creating incentives, it could probably become more effective if the effect price component were based on enterprise customers current effect usage rather than the enterprise customers effect usage during the previous winter season. / I september 2017 introducerade Luleå Energi en ny prismodell för deras fjärrvärme tjänster gentemot företagskunder med intentionen att skapa starkare incitament för energieffektiviseringsåtgärder och förse marknaden med prissignaler som motsvarar de underliggande produktionskostnaderna. Syftet med denna uppsats är att undersöka huruvida Luleå Energi’s intentioner har blivit uppfyllda, inte minst i form av energieffektiviseringsåtgärder. Studien kommer också att, med hjälp av en litteraturstudie, genomföra en teoretisk bedömning av den nya prismodellen. Studien applicerar teorier som begränsad rationalitet, vinstmaximerande företag, osäkerhet och ofullständig information. Resultaten visar att den nya prismodellen eventuellt hindras av begränsad rationalitet hos kunderna, och den överlag låga prisnivån på fjärrvärme i Luleå kommun. Resultaten visar också att även om den nya prismodellen är någorlunda bra på att skapa incitament så skulle den troligen kunna bli effektivare genom att basera effektpriskomponenten på företagskundernas nuvarande effektanvändning istället för företagskundernas effektanvändning under den föregående vintersäsongen.