937 resultados para electricity sales
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Tässä diplomityössä selvitetään teollisen mittakaavan merituulipuistojen taloudellisia ja osin myös teknisiä rakentamisedellytyksiä Kokkolan seudun rannikolla. Lisäksi työssä tarkastellaan erilaisten tukitoimien vaikutusta tuulivoiman kannattavuuteen sekä selvitetään lyhyesti merituulivoiman hallinnollisia ja oikeudellisia edellytyksiä. Esimerkkikohteina tarkastellaan viittä Kokkolan edustalle suunniteltua merituulipuistoa, joiden tehot ovat 20 – 100 MW ja yksikkökoot 1,8 – 5 MW. Tuulipuistojen tuuliolot on arvioitu läheisten mittauspisteiden tietojen perusteella ja niiden pohjalta on laskettu puistojen energiantuotto. Tuulivoimaloiden huipunkäyttöajoiksi on saatu noin 2400 – 2500 h/a. Puistojen investointikustannukset ovat noin 6 500 –10 200 mk/kW: itse turbiinin lisäksi suurimpia kustannuseriä ovat perustukset ja sähköverkkoliitäntä. Vuosittaisten käyttö- ja kunnossapitokustannusten suuruudeksi on arvioitu noin 3 % investointikustannuksista. Kannattavuustarkastelut on suoritettu 5 % laskentakorolla ja 25 vuoden pitoajalle. Tuotantokustannukset ovat ilman tukia noin 27 – 38 p/kWh. Kun sähkön hintana on 150 mk/MWh, ei taloudellista kannattavuutta voida saavuttaa edes nykyisin käytössä olevan investointi- ja tuotantotuen avulla. Tuulisähköstä saatava mahdollinen ”vihreän sähkön lisä” tai päästökaupan aloittaminen voisivat mahdollistaa tuulivoiman taloudellisen kannattavuuden myös silloin, kun sähkön hintataso on matala. Kannattavuutta voitaisiin parantaa myös tukijärjestelmällä, joka painottaa nykyistä enemmän tuotantoa.
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Sähkönmyyntiyhtiön liiketoimintaan liittyy muiden yritysten toiminnan tavoin erilaisia riskejä. Riskit jaetaan operationaalisiin ja markkinariskeihin. Operationaalisia riskejä ovat esimerkiksi erilaiset henkilöstöön, tietojärjestelmiin tai operatiiviseen toimintaan liittyvät riskit. Sähkönmyyntiyhtiön liiketoimintaan kohdistuu myös erilaisia markkinariskejä, joihin tyypillisesti liittyy sekä voiton että tappion mahdollisuus. Sähkönmyyntiyhtiön liiketoimintaan liittyviä markkinariskejä ovat esimerkiksi volyymiriski, profiiliriski, hintariski ja johdannaisriski. Työssä käydään läpi myös muita markkinariskejä sekä pohditaan riskien suojautumiskeinoja. Markkinariskejä voidaan hallita useiden eri keinojen avulla. Tavallisimpia näistä ovat esimerkiksi johdannaisten ja peak- sekä profiilituotteiden hankkiminen, joiden avulla hallitaan markkinahintojen muutosten vaikutuksia liiketoiminnan tulokseen. Lisäksi yritys voi käyttää riskienhallintakeinoina monipuolista jälkilaskentaa sekä raportointia liiketoiminnan keskeisiltä osilta. Erityisesti riskienhallintakeinona käytetään erilaisia riskimittareita, joista Profit at Risk-riskimittarin katsottiin soveltuvan parhaiten sähkönmyyntiyhtiön riskienhallinnan tueksi. Riskienhallinnan kehityksen näkökulmasta yrityksen on syytä miettiä sopimusten hinnoitteluaan sekä suojausstrategiaansa.
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Diplomityön tavoitteena on esitellä sähkökaupan ja erityisesti sähköyhtiöiden kokemia sähkönmyynnin riskejä sekä kuvata sähkönmyyntiin liittyvää riskienhallinnan problematiikkaa. Tarkastelun näkökulmana on tietojärjestelmien ja saatavissa olevan tiedon hyödyntäminen energiayhtiöiden riskienhallinnassa. Toinen päätavoitteista on tutkia, kuinka saatavilla olevaa tiedon hyödyntämistä voidaan kehittää sähkönmyynnin hinnoittelussa sekä suojausten suunnittelussa. Työ toteutettiin työskentelemällä asiantuntijana energia-alaan keskittyneessä ohjelmistoyrityksessä sekä haastattelemalla yhdeksän suomalaisen sähkönmyyntiyhtiön henkilöitä riskienhallinnan haasteiden sekä tietojärjestelmien näkökulmasta. Saatavilla olevien tietojen nykyistä parempi hyödyntäminen ja automatisointi voivat auttaa pienentämään yhtiöiden riskitasoa ja parantaa menestymisen edellytyksiä sähkönmyynnin vähittäismarkkinoilla. Lisäksi kulloiseenkin markkinatilanteeseen sopivat sähkön hankintahinnan suojausstrategiat sekä monipuoliset dynaamiset hinnoittelumallit auttavat pienentämään yhtiön kokemia riskejä tai niiden vaikutuksia. Näiden hyödyntäminen vaatii laajaa ymmärrystä sähkö- ja johdannaismarkkinoiden toiminnasta sekä usein myös nykyisten tietojärjestelmien kehittämistä. Tulevaisuudessa yhä yleistyvä hajautettu tuotanto sekä kysynnän jousto asettavat tietojärjestelmille uusia vaatimuksia, jotka toteutuessaan mahdollistavat uudenlaisten palveluiden käyttöönoton sekä voivat tuoda tilaa myös alan uusille toimijoille. Työssä käsitellään energiayhtiöiden kokemia riskejä sähkönmyynnin näkökulmasta, esitellään alan yleisimmät riskit sekä keinot ja työkalut niiltä suojautumiseen. Työn lopuksi tarkastellaan sähkönmyynnin ja –hankinnan oleellisimpia prosesseja riskienhallinnan kehittämisen näkökulmasta.
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Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.
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Shipping list no.: 2001-0254-P.
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A key objective of developing countries is to provide affordable access to modern energy services in order to support economic and social development. The paper presents a number of arguments for why and in which way energy access and affordability can play a key role in national development programs and in achieving the Millennium Development Goals. Approaches for measuring accessibility and affordability are presented, drawing on case studies of Bangladesh. Brazil, and South Africa, countries with different rates of electrification. Affordability of using electricity is examined in relation to the energy expenditure burden for households and time consumption. Conclusions focus on lessons learned and recommendations for implementing policies, instruments, and regulatory measures to tackle the challenge of affordability. (C) 2011 Elsevier Ltd. All rights reserved.
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The proposed method to analyze the composition of the cost of electricity is based on the energy conversion processes and the destruction of the exergy through the several thermodynamic processes that comprise a combined cycle power plant. The method uses thermoeconomics to evaluate and allocate the cost of exergy throughout the processes, considering costs related to inputs and investment in equipment. Although the concept may be applied to any combined cycle or cogeneration plant, this work develops only the mathematical modeling for three-pressure heat recovery steam generator (HRSG) configurations and total condensation of the produced steam. It is possible to study any n x 1 plant configuration (n sets of gas turbine and HRSGs associated to one steam turbine generator and condenser) with the developed model, assuming that every train operates identically and in steady state. The presented model was conceived from a complex configuration of a real power plant, over which variations may be applied in order to adapt it to a defined configuration under study [Borelli SJS. Method for the analysis of the composition of electricity costs in combined cycle thermoelectric power plants. Master in Energy Dissertation, Interdisciplinary Program of Energy, Institute of Eletro-technical and Energy, University of Sao Paulo, Sao Paulo, Brazil, 2005 (in Portuguese)]. The variations and adaptations include, for instance, use of reheat, supplementary firing and partial load operation. It is also possible to undertake sensitivity analysis on geometrical equipment parameters. (C) 2007 Elsevier Ltd. All rights reserved.
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Many works have shown the potential of the Brazilian sugarcane industry as an electricity supplier. However, few studies have studied how this potential could be achieved without jeopardizing the production of sugar and ethanol. Also, the impact of modifications in the cogeneration plant on the costs of production of sugar and ethanol has not been evaluated. This paper presents an approach to the problem of exergy optimization of cogeneration systems in sugarcane mills. A general model to the sugar and ethanol production processes is developed based on data supplied by a real plant, and an exergy analysis is performed. A discussion is made about the variables that most affect the performance of the processes. Then, a procedure is presented to evaluate modifications in the cogeneration system and in the process, and their impact on the production costs of sugar, ethanol and electricity. Furthermore, a discussion on the renewability of processes is made based on an exergy index of renewability. As a general conclusion, besides adding a new revenue to the mill, the generation of excess electricity improves the exergo-environmental performance of the mill as a whole. (C) 2010 Elsevier Ltd. All rights reserved.
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This paper critically assesses several loss allocation methods based on the type of competition each method promotes. This understanding assists in determining which method will promote more efficient network operations when implemented in deregulated electricity industries. The methods addressed in this paper include the pro rata [1], proportional sharing [2], loss formula [3], incremental [4], and a new method proposed by the authors of this paper, which is loop-based [5]. These methods are tested on a modified Nordic 32-bus network, where different case studies of different operating points are investigated. The varying results obtained for each allocation method at different operating points make it possible to distinguish methods that promote unhealthy competition from those that encourage better system operation.
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There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.