838 resultados para demand side management (DSM)


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The penetration of the electric vehicle (EV) has increased rapidly in recent years mainly as a consequence of advances in transport technology and power electronics and in response to global pressure to reduce carbon emissions and limit fossil fuel consumption. It is widely acknowledged that inappropriate provision and dispatch of EV charging can lead to negative impacts on power system infrastructure. This paper considers EV requirements and proposes a module which uses owner participation, through mobile phone apps and on-board diagnostics II (OBD-II), for scheduled vehicle charging. A multi-EV reference and single-EV real-time response (MRS2R) online algorithm is proposed to calculate the maximum and minimum adjustable limits of necessary capacity, which forms part of decision-making support in power system dispatch. The proposed EV dispatch module is evaluated in a case study and the influence of the mobile app, EV dispatch trending and commercial impact is explored.

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Data la sempre maggiore richiesta di fabbisogno energetico, si è sviluppata una nuova filosofia nella gestione dei consumi energetici, il DSM (demand side management), che ha lo scopo di incoraggiare il consumatore ad usare energia in modo più intelligente e coscienzioso. Questo obiettivo, unito all’accumulo di energia da fonti rinnovabili, permetterà un abbassamento dell’utilizzo dell’energia elettrica proveniente dal consumo di fonti non rinnovabili e altamente inquinanti come quelle a combustibili fossili ed una diminuzione sia del consumo energetico, sia del costo per produrre energia che dell’energia stessa. L’home automation e la domotica in ambiente domestico rappresentano un esempio di DSM. L’obiettivo di questa tesi è quello di creare un sistema di home automation utilizzando tecnologie opensource. Sono stati utilizzati device come board Arduino UNO, Raspberry Pi ed un PC con sistema operativo GNU/Linux per creare una simulazione di un sistema di home automation abbinato alla gestione di celle fotovoltaiche ed energy storaging. Il sistema permette di poter spegnere un carico energetico in base a delle particolari circostanze come, per esempio, il superamento di una certa soglia di consumo di energia elettrica. Il software utilizzato è opensource e mira a poter ottimizzare il consumo energetico secondo le proprie finalità. Il tutto a dimostrare che si può creare un sistema di home automation da abbinare con il presente e futuro delle fonti rinnovabili utilizzando tecnologie libere in modo tale da preservare privacy e security oltre che customizzazione e possibilità di adattamento a diverse circostanze. Nella progettazione del sistema è stato implementato un algoritmo per gestire varie situazioni all’interno di un ambiente domestico. La realizzazione di tale algoritmo ha prodotto ottimi risultati nella raggiungimento degli obiettivi prefissati. Il progetto di questa tesi può essere ulteriormente ampliato ed il codice è reperibile in un repository pubblico.

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The main objective of the thesis is to seek insights into the theory, and provide empirical evidence of rebound effects. Rebound effects reduce the environmental benefits of environmental policies and household behaviour changes. In particular, win-win demand side measures, in the form of energy efficiency and household consumption pattern changes, are seen as ways for households and businesses to save money and the environment. However, these savings have environmental impacts when spent, which are known as rebound effects. This is an area that has been widely neglected by policy makers. This work extends the rebound effect literature in three important ways, (1) it incorporates the potential for variation of rebound effects with household income level, (2) it enables the isolation of direct and indirect effects for cases of energy efficient technology adoption, and examines the relationship between these two component effects, and (3) it expands the scope of rebound effect analysis to include government taxes and subsidies. MACROBUTTON HTMLDirect Using a case study approach it is found that the rebound effect from household consumption pattern changes targeted at electricity is between 5 and 10%. For consumption pattern changes with reduced vehicle fuel use, the rebound effect is in the order of 20 to 30%. Higher income households in general are found to have a lower total rebound effect; however the indirect effect becomes relatively more significant at higher household income levels. In the win-lose case of domestic photovoltaic electricity generation, it is demonstrated that negative rebound effects can occur, which can potentially amplify the environmental benefits of this action. The rebound effect from a carbon tax, which occurs due to the re-spending of raised revenues, was found to be in the range of 11-32%. Taxes and transfers between households of different income levels also have environmental implications. For example, a more progressive tax structure, with increased low income welfare payments is likely to increase greenhouse gas emissions. Subsidies aimed at encouraging environmentally friendly consumption habits are also subject to rebound effects, as they constitute a substitution of government expenditure for household expenditure. For policy makers, these findings point to the need to incorporate rebound effects in the environmental policy evaluation process.’

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There has been a developing interest in smart grids, the possibility of significantly enhanced performance from remote measurements and intelligent controls. For transmission the use of PMU signals from remote sites and direct load shed controls can give significant enhancement for large system disturbances rather than relying on local measurements and linear controls. This lecture will emphasize what can be found from remote measurements and the mechanisms to get a smarter response to major disturbances. For distribution systems there has been a significant history in the area of distribution reconfiguration automation. This lecture will emphasize the incorporation of Distributed Generation into distribution networks and the impact on voltage/frequency control and protection. Overall the performance of both transmission and distribution will be impacted by demand side management and the capabilities built into the system. In particular, we consider different time scales of load communication and response and look to the benefits for system, energy and lines.

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This paper proposes a method of short term load forecasting with limited data, applicable even at 11 kV substation levels where total power demand is relatively low and somewhat random and weather data are usually not available as in most developing countries. Kalman filtering technique has been modified and used to forecast daily and hourly load. Planning generation and interstate energy exchange schedule at load dispatch centre and decentralized Demand Side Management at substation level are intended to be carried out with the help of this short term load forecasting technique especially to achieve peak power control without enforcing load-shedding.

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The smart grid is a highly complex system that is being formed from the traditional power grid, adding new and sophisticated communication and control devices. This will enable integrating new elements for distributed power generation and also achieving an increasingly automated operation so for actions of the utilities as for customers. In order to model such systems a bottom-up method is followed, using only a few basic elements which are structured into two layers: a physical layer for the electrical power transmission, and one logical layer for element communication. A simple case study is presented to analyse the possibilities of simulation. It shows a microgrid model with dynamic load management and an integrated approach that can process both electrical and communication flows.

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We review literature on several types of energy efficiency policies: appliance standards, financial incentive programs, information and voluntary programs, and management of government energy use. For each, we provide a brief synopsis of the relevant programs, along with available existing estimates of energy savings, costs, and cost-effectiveness at a national level. The literature examining these estimates points to potential issues in determining the energy savings and costs, but recent evidence suggests that techniques for measuring both have improved. Taken together, the literature identifies up to four quads of energy savings annually from these programs - at least half of which is attributable to appliance standards and utility-based demand-side management, with possible additional energy savings from the U.S. Department of Energy's (DOE's) ENERGY STAR, Climate Challenge, and Section 1605b voluntary programs to reduce carbon dioxide (CO 2) emissions. Related reductions in CO 2 and criteria air pollutants may contribute an additional 10% to the value of energy savings above the price of energy itself. Copyright © 2006 by Annual Reviews. All rights reserved.

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Dwindling fossil fuel resources and pressures to reduce greenhouse gas emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is to instantaneously meet demand, to operate to standards and reduce greenhouse gas emissions. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating has been studied previously, particularly at the domestic level to provide load control, peak shave and to bene?t end-users ?nancially with lower bills, particularly in vertically integrated monopolies. In this paper a number of continuous direct load control demand response based electric water heating algorithms are modelled to test the effectiveness of wholesale electricity market signals to study the system bene?ts. The results are compared and contrasted to determine which control algorithm showed the best potential for energy savings, system marginal price savings and wind integration.

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Over the last decade there has been a rapid global increase in wind power stimulated by energy and climate policies. However, as wind power is inherently variable and stochastic over a range of time scales, additional system balancing is required to ensure system reliability and stability. This paper reviews the technical, policy and market challenges to achieving ambitious wind power penetration targets in Ireland’s All-Island Grid and examines a number of measures proposed to address these challenges. Current government policy in Ireland is to address these challenges with additional grid reinforcement, interconnection and open-cycle gas plant. More recently smart grid combined with demand side management and electric vehicles have also been presented as options to mitigate the variability of wind power. In addition, the transmission system operators have developed wind farm specific grid codes requiring improved turbine controls and wind power forecasting techniques.

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While the benefits of renewable energy are well known and used to influence government policy there are a number of problems which arise from having significant quantities of renewable energies on an electricity grid. The most notable problem stems from their intermittent nature which is often out of phase with the demands of the end users. This requires the development of either efficient energy storage systems, e.g. battery technology, compressed air storage etc. or through the creation of demand side management units which can utilise power quickly for manufacturing operations. Herein a system performing the conversion of synthetic biogas to synthesis gas using wind power and an induction heating system is shown. This approach demonstrates the feasibility of such techniques for stabilising the electricity grid while also providing a robust means of energy storage. This exemplar is also applicable to the production of hydrogen from the steam reforming of natural gas.

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The development of smart grid technologies and appropriate charging strategies are key to accommodating large numbers of Electric Vehicles (EV) charging on the grid. In this paper a general framework is presented for formulating the EV charging optimization problem and three different charging strategies are investigated and compared from the perspective of charging fairness while taking into account power system constraints. Two strategies are based on distributed algorithms, namely, Additive Increase and Multiplicative Decrease (AIMD), and Distributed Price-Feedback (DPF), while the third is an ideal centralized solution used to benchmark performance. The algorithms are evaluated using a simulation of a typical residential low voltage distribution network with 50% EV penetration. © 2013 IEEE.

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This study characterizes the domestic loads suitable to participate in the load participation scheme to make the power system more carbon and economically efficient by shifting the electricity demand profile towards periods when there is plentiful renewable in-feed.

A series of experiments have been performed on a common fridge-freezer, both completely empty and half full. The results presented are ambient temperature, temperature inside the fridge, temperature inside the drawer of the fridge, temperature inside the freezer, thermal time constants, power consumption and electric energy consumed.

The thermal time constants obtained clearly demonstrate the potential of such refrigeration load for Smart Customer Load Participation.

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The future European power system will have a hierarchical structure created by layers of system control from a Supergrid via regional high-voltage transmission through to medium and low-voltage distribution. Each level will have generation sources such as large-scale offshore wind, wave, solar thermal, nuclear directly connected to this Supergrid and high levels of embedded generation, connected to the medium-voltage distribution system. It is expected that the fuel portfolio will be dominated by offshore wind in Northern Europe and PV in Southern Europe. The strategies required to manage the coordination of supply-side variability with demand-side variability will include large scale interconnection, demand side management, load aggregation and storage in the context of the Supergrid combined with the Smart Grid. The design challenge associated with this will not only include control topology, data acquisition, analysis and communications technologies, but also the selection of fuel portfolio at a macro level. This paper quantifies the amount of demand side management, storage and so-called 'back-up generation' needed to support an 80% renewable energy portfolio in Europe by 2050. © 2013 IEEE.

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The power system of the future will have a hierarchical structure created by layers of system control from via regional high-voltage transmission through to medium and low-voltage distribution. Each level will have generation sources such as large-scale offshore wind, wave, solar thermal, nuclear directly connected to this Supergrid and high levels of embedded generation, connected to the medium-voltage distribution system. It is expected that the fuel portfolio will be dominated by offshore wind in Northern Europe and PV in Southern Europe. The strategies required to manage the coordination of supply-side variability with demand-side variability will include large scale interconnection, demand side management, load aggregation and storage in the concept of the Supergrid combined with the Smart Grid. The design challenge associated with this will not only include control topology, data acquisition, analysis and communications technologies, but also the selection of fuel portfolio at a macro level. This paper quantifies the amount of demand side management, storage and so-called ‘back-up generation’ needed to support an 80% renewable energy portfolio in Europe by 2050.

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Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.