991 resultados para Demand Response
Resumo:
The recent changes on power systems paradigm requires the active participation of small and medium players in energy management. With an electricity price fluctuation these players must manage the consumption. Lowering costs and ensuring adequate user comfort levels. Demand response can improve the power system management and bring benefits for the small and medium players. The work presented in this paper, which is developed aiming the smart grid context, can also be used in the current power system paradigm. The proposed system is the combination of several fields of research, namely multi-agent systems and artificial neural networks. This system is physically implemented in our laboratories and it is used daily by researchers. The physical implementation gives the system an improvement in the proof of concept, distancing itself from the conventional systems. This paper presents a case study illustrating the simulation of real-time pricing in a laboratory.
Resumo:
The operation of distribution networks has been facing changes with the implementation of smart grids and microgrids, and the increasing use of distributed generation. The specific case of distribution networks that accommodate residential buildings, small commerce, and distributed generation as the case of storage and PV generation lead to the concept of microgrids, in the cases that the network is able to operate in islanding mode. The microgrid operator in this context is able to manage the consumption and generation resources, also including demand response programs, obtaining profits from selling electricity to the main network. The present paper proposes a methodology for the energy resource scheduling considering power flow issues and the energy buying and selling from/to the main network in each bus of the microgrid. The case study uses a real distribution network with 25 bus, residential and commercial consumers, PV generation, and storage.
Resumo:
A sustentabilidade do sistema energético é crucial para o desenvolvimento económico e social das sociedades presentes e futuras. Para garantir o bom funcionamento dos sistemas de energia actua-se, tipicamente, sobre a produção e sobre as redes de transporte e de distribuição. No entanto, a integração crescente de produção distribuída, principalmente nas redes de distribuição de média e de baixa tensão, a liberalização dos mercados energéticos, o desenvolvimento de mecanismos de armazenamento de energia, o desenvolvimento de sistemas automatizados de controlo de cargas e os avanços tecnológicos das infra-estruturas de comunicação impõem o desenvolvimento de novos métodos de gestão e controlo dos sistemas de energia. O contributo deste trabalho é o desenvolvimento de uma metodologia de gestão de recursos energéticos num contexto de SmartGrids, considerando uma entidade designada por VPP que gere um conjunto de instalações (unidades produtoras, consumidores e unidades de armazenamento) e, em alguns casos, tem ao seu cuidado a gestão de uma parte da rede eléctrica. Os métodos desenvolvidos contemplam a penetração intensiva de produção distribuída, o aparecimento de programas de Demand Response e o desenvolvimento de novos sistemas de armazenamento. São ainda propostos níveis de controlo e de tomada de decisão hierarquizados e geridos por entidades que actuem num ambiente de cooperação mas também de concorrência entre si. A metodologia proposta foi desenvolvida recorrendo a técnicas determinísticas, nomeadamente, à programação não linear inteira mista, tendo sido consideradas três funções objectivo distintas (custos mínimos, emissões mínimas e cortes de carga mínimos), originando, posteriormente, uma função objectivo global, o que permitiu determinar os óptimos de Pareto. São ainda determinados os valores dos custos marginais locais em cada barramento e consideradas as incertezas dos dados de entrada, nomeadamente, produção e consumo. Assim, o VPP tem ao seu dispor um conjunto de soluções que lhe permitirão tomar decisões mais fundamentadas e de acordo com o seu perfil de actuação. São apresentados dois casos de estudo. O primeiro utiliza uma rede de distribuição de 32 barramentos publicada por Baran & Wu. O segundo caso de estudo utiliza uma rede de distribuição de 114 barramentos adaptada da rede de 123 barramentos do IEEE.
Resumo:
All over the world, the liberalization of electricity markets, which follows different paradigms, has created new challenges for those involved in this sector. In order to respond to these challenges, electric power systems suffered a significant restructuring in its mode of operation and planning. This restructuring resulted in a considerable increase of the electric sector competitiveness. Particularly, the Ancillary Services (AS) market has been target of constant renovations in its operation mode as it is a targeted market for the trading of services, which have as main objective to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. In this way, with the increasing penetration of distributed energy resources including distributed generation, demand response, storage units and electric vehicles, it is essential to develop new smarter and hierarchical methods of operation of electric power systems. As these resources are mostly connected to the distribution network, it is important to consider the introduction of this kind of resources in AS delivery in order to achieve greater reliability and cost efficiency of electrical power systems operation. The main contribution of this work is the design and development of mechanisms and methodologies of AS market and for energy and AS joint market, considering different management entities of transmission and distribution networks. Several models developed in this work consider the most common AS in the liberalized market environment: Regulation Down; Regulation Up; Spinning Reserve and Non-Spinning Reserve. The presented models consider different rules and ways of operation, such as the division of market by network areas, which allows the congestion management of interconnections between areas; or the ancillary service cascading process, which allows the replacement of AS of superior quality by lower quality of AS, ensuring a better economic performance of the market. A major contribution of this work is the development an innovative methodology of market clearing process to be used in the energy and AS joint market, able to ensure viable and feasible solutions in markets, where there are technical constraints in the transmission network involving its division into areas or regions. The proposed method is based on the determination of Bialek topological factors and considers the contribution of the dispatch for all services of increase of generation (energy, Regulation Up, Spinning and Non-Spinning reserves) in network congestion. The use of Bialek factors in each iteration of the proposed methodology allows limiting the bids in the market while ensuring that the solution is feasible in any context of system operation. Another important contribution of this work is the model of the contribution of distributed energy resources in the ancillary services. In this way, a Virtual Power Player (VPP) is considered in order to aggregate, manage and interact with distributed energy resources. The VPP manages all the agents aggregated, being able to supply AS to the system operator, with the main purpose of participation in electricity market. In order to ensure their participation in the AS, the VPP should have a set of contracts with the agents that include a set of diversified and adapted rules to each kind of distributed resource. All methodologies developed and implemented in this work have been integrated into the MASCEM simulator, which is a simulator based on a multi-agent system that allows to study complex operation of electricity markets. In this way, the developed methodologies allow the simulator to cover more operation contexts of the present and future of the electricity market. In this way, this dissertation offers a huge contribution to the AS market simulation, based on models and mechanisms currently used in several real markets, as well as the introduction of innovative methodologies of market clearing process on the energy and AS joint market. This dissertation presents five case studies; each one consists of multiple scenarios. The first case study illustrates the application of AS market simulation considering several bids of market players. The energy and ancillary services joint market simulation is exposed in the second case study. In the third case study it is developed a comparison between the simulation of the joint market methodology, in which the player bids to the ancillary services is considered by network areas and a reference methodology. The fourth case study presents the simulation of joint market methodology based on Bialek topological distribution factors applied to transmission network with 7 buses managed by a TSO. The last case study presents a joint market model simulation which considers the aggregation of small players to a VPP, as well as complex contracts related to these entities. The case study comprises a distribution network with 33 buses managed by VPP, which comprises several kinds of distributed resources, such as photovoltaic, CHP, fuel cells, wind turbines, biomass, small hydro, municipal solid waste, demand response, and storage units.
Resumo:
Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.
Resumo:
The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.
Resumo:
A liberalização dos mercados de energia elétrica e a crescente integração dos recursos energéticos distribuídos nas redes de distribuição, nomeadamente as unidades de produção distribuída, os sistemas de controlo de cargas através dos programas de demand response, os sistemas de armazenamento e os veículos elétricos, representaram uma evolução no paradigma de operação e gestão dos sistemas elétricos. Este novo paradigma de operação impõe o desenvolvimento de novas metodologias de gestão e controlo que permitam a integração de todas as novas tecnologias de forma eficiente e sustentável. O principal contributo deste trabalho reside no desenvolvimento de metodologias para a gestão de recursos energéticos no contexto de redes inteligentes, que contemplam três horizontes temporais distintos (24 horas, 1 hora e 5 minutos). As metodologias consideram os escalonamentos anteriores assim como as previsões atualizadas de forma a melhorar o desempenho total do sistema e consequentemente aumentar a rentabilidade dos agentes agregadores. As metodologias propostas foram integradas numa ferramenta de simulação, que servirá de apoio à decisão de uma entidade agregadora designada por virtual power player. Ao nível das metodologias desenvolvidas são propostos três algoritmos de gestão distintos, nomeadamente para a segunda (1 hora) e terceira fase (5 minutos) da ferramenta de gestão, diferenciados pela influência que os períodos antecedentes e seguintes têm no período em escalonamento. Outro aspeto relevante apresentado neste documento é o teste e a validação dos modelos propostos numa plataforma de simulação comercial. Para além das metodologias propostas, a aplicação permitiu validar os modelos dos equipamentos considerados, nomeadamente, ao nível das redes de distribuição e dos recursos energéticos distribuidos. Nesta dissertação são apresentados três casos de estudos, cada um com diferentes cenários referentes a cenários de operação futuros. Estes casos de estudos são importantes para verificar a viabilidade da implementação das metodologias e algoritmos propostos. Adicionalmente são apresentadas comparações das metodologias propostas relativamente aos resultados obtidos, complexidade de gestão em ambiente de simulação para as diferentes fases da ferramenta proposta e os benefícios e inconvenientes no uso da ferramenta proposta.
Resumo:
Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.
Resumo:
Sähkönmittaus suoritetaan enenevissä määrin älykkäiden energiamittareiden avulla niin Suomessa kuin muuallakin maailmassa. Älykkäät energiamittarit mahdollistavat huomattavasti monipuolisemman mittaustiedon saannin kuin tavanomaisilla mittareilla saatavan pelkän kulutetun energian määrän. Mittauksesta vastuussa olevalle taholle syntyy kuluja mittareiden asennuksesta uusien tehokkaampien tietojärjestelmien ylläpitoon siirryttäessä uuteen älykkäämpään mittausjärjestelmään. Kulujen kattamiseksi olisi hyödyllistä, jos monipuolisempaa mittaustietoa voitaisiin käyttää laajemmin kuin pelkästään asiakkaiden laskutukseen. Tästä johtuen mittaustiedon tehokasta hyödyntämistä varten tulee kehittää uusia palveluja esimerkiksi raportoinnin, mittaustietojen analysoinnin sekä kysyntäjouston saralla. Tässä työssä esitellään älykkäisiin energiamittareihin liittyvää tekniikkaa ja syitä miksi älykkäämpiin sähkönmittausjärjestelmiin ollaan siirtymässä. Mittaroinnin nykytilannetta käydään läpi niin Suomen kuin eräiden muidenkin Euroopan maiden osalta. Työssä esitetään myös muutamia käytännön palvelumahdollisuuksia ja pohditaan millaiseksi sähkönmittausjärjestelmät tulevaisuudessa muotoutuvat.
Resumo:
Growing recognition of the electricity grid modernization to enable new electricity generation and consumption schemes has found articulation in the vision of the Smart Grid platform. The essence of this vision is an autonomous network with two-way electricity power flows and extensive real-time information between the generation nodes, various electricity-dependent appliances and all points in-between. Three major components of the Smart Grids are distributed intelligence, communication technologies, and automated control systems. The aim of this thesis is to recognize the challenges that Smart Grids are facing, while extinguishing the main driving factors for their introduction. The scope of the thesis also covers possible place of electricity Aggregator Company in the current and future electricity markets. Basic functions of an aggregator and possible revenue sources along with demand response feasibility calculations are reviewed within this thesis.
Resumo:
Työssä tarkastellaan PJM:n RPM-pohjaisen kapasiteettimarkkinan vaikutuksia kysynnän-joustoresurssien määrän kasvattamiseen PJM:n kysynnän hintajousto- sekä luotettavuus-pohjaisten kysynnänjousto-ohjelmien yhteydessä. Työssä tarkastellaan myös millaisia ky-synnänjousto-ohjelmia PJM:ssä on olemassa ja miten ne toimivat.
Resumo:
Työssä tarkoituksena oli tutkia voidaanko valaistuksella toteutettua kysynnän joustoa. Työssä tutustuttiin mahdollisiin markkinapaikkoihin ja kysynnän jousto tarkoittaa. Työssä käydään läpi valaistuksen perusteita, sekä nykyisien ohjaustapojen energiatehokkuutta tukevia ratkaisuja. Tekniselle toteutukselle ei ole estettä, käytännöntoteutukselle esteeksi muodostuu valaistustason muutoksen häiritsevyys. Järjestelmällä voidaan muodostaa valaistukselle hinta mitä halutaan palvelusta maksaa. Työssä tarkasteltiin ohjauksen sijoittamista esimerkkikuormalle.
Resumo:
Työssä tarkasteltiin älykkäiden sähköverkkojen näkökulmasta, millaisia toiminnallisuuksia kiinteistöautomaatiojärjestelmiltä odotetaan ja miten markkinoilla olevat järjestelmät vastaavat näihin odotuksiin. Lisäksi arvioitiin, kuinka taloudellisesti kannattavia valittuihin automaatiojärjestelmiin kuuluvat energian käytön hallintaan liittyvät toiminnallisuudet ovat sähkönkäyttäjien näkökulmasta. Lopuksi tehtiin lyhyt katsaus kiinteistöautomaatiojärjestelmien tulevaisuuden näkymiin. Kiinteistöautomaatiolla voidaan vaikuttaa energian käytön tehokkuuteen ohjaamalla esimerkiksi valaistusta, ilmanvaihtoa, ilmastointia, lämmitystä ja sähkölaitteita. Eräs vaihtoehto on toteuttaa ohjauksen avulla markkinapohjaista kysyntäjoustoa, jossa kiinteistön sähköjärjestelmän toimintaa säädetään sähkön hinnan perusteella. Kiinteistössä tulee myös voida tehdä laitekohtaisia energiankulutuksen mittauksia, jotka antavat tietoa sähkönkäyttäjille eri laitteiden sähkönkulutuksesta. Kiinteistöautomaation ja sähkön pientuotannon yleistymisen myötä on myös etähallittavien virtuaalivoimaloiden toteuttaminen tulossa mahdolliseksi. Lisäksi laskettiin sähkönkäyttäjän kannalta lämmityksen, valaistuksen ja ilmanvaihdon ohjauksen kannattavuutta ja selvitettiin, että tutkituissa esimerkkijärjestelmissä suurin säästöpotentiaali on lämmityksen ohjauksessa.
Resumo:
Muuttuva sähköntuotantorakenne yhdessä Euroopan yhdentyvien sähkömarkkinoiden kanssa muuttaa energiayhtiöiden toimintaympäristöä tulevaisuudessa. Markkinoilta poistu-va säätökykyinen lauhdevoima ja lisääntyvä säiden mukaan vaihteleva tuuli- ja aurin-koenergia lisäävät säätövoiman tarvetta energiajärjestelmässä. Osa lisääntyvästä säätövoi-man tarpeesta voidaan kattaa kulutuksen kysyntäjoustoa lisäämällä. Tässä työssä tavoitteena on kehittää Savon Voima Oyj:lle kysyntäjoutopalvelu yritysasiak-kaille. Työssä kartoitetaan kysyntäjouston eri markkinapaikkojen mahdollisuuksia kysyntä-jouston toteuttamiselle, sekä käydään läpi niiden asettamia rajoitteita kysyntäjouston to-teuttamisen kannalta. Työn osana kehitettyä kysyntäjouston potentiaalin laskentatyökalua käytetään arvioitaessa valittujen pilottiasiakkaiden potentiaalia Elspot-markkinoille osallistuvan kysyntäjouston osalta. Laskennan tulosten perusteella kysyntäjouston toteuttaminen Elspot-markkinoille on kannattavaa valittujen pilottiasiakkaiden kohdalla. Työssä käydään läpi kysyntäjoustopalvelun prosessia, sen vaiheita sekä huomioon otettavia asioita tarjottaessa kysyntäjoustopalvelua yrityksille. Lopuksi esitetään liiketoimintamalli, jolla palvelua lähdetään yritysasiakkaille tarjoamaan. Liiketoimintamallissa esitetään koh-deryhmät ja markkinat kysyntäjouston toteuttamiselle.
Resumo:
The electricity distribution sector will face significant changes in the future. Increasing reliability demands will call for major network investments. At the same time, electricity end-use is undergoing profound changes. The changes include future energy technologies and other advances in the field. New technologies such as microgeneration and electric vehicles will have different kinds of impacts on electricity distribution network loads. In addition, smart metering provides more accurate electricity consumption data and opportunities to develop sophisticated load modelling and forecasting approaches. Thus, there are both demands and opportunities to develop a new type of long-term forecasting methodology for electricity distribution. The work concentrates on the technical and economic perspectives of electricity distribution. The doctoral dissertation proposes a methodology to forecast electricity consumption in the distribution networks. The forecasting process consists of a spatial analysis, clustering, end-use modelling, scenarios and simulation methods, and the load forecasts are based on the application of automatic meter reading (AMR) data. The developed long-term forecasting process produces power-based load forecasts. By applying these results, it is possible to forecast the impacts of changes on electrical energy in the network, and further, on the distribution system operator’s revenue. These results are applicable to distribution network and business planning. This doctoral dissertation includes a case study, which tests the forecasting process in practice. For the case study, the most prominent future energy technologies are chosen, and their impacts on the electrical energy and power on the network are analysed. The most relevant topics related to changes in the operating environment, namely energy efficiency, microgeneration, electric vehicles, energy storages and demand response, are discussed in more detail. The study shows that changes in electricity end-use may have radical impacts both on electrical energy and power in the distribution networks and on the distribution revenue. These changes will probably pose challenges for distribution system operators. The study suggests solutions for the distribution system operators on how they can prepare for the changing conditions. It is concluded that a new type of load forecasting methodology is needed, because the previous methods are no longer able to produce adequate forecasts.