991 resultados para Peak load shaving


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This paper proposes a novel peak load management scheme for rural areas. The scheme transfers certain customers onto local nonembedded generators during peak load periods to alleviate network under voltage problems. This paper develops and presents this system by way of a case study in Central Queensland, Australia. A methodology is presented for determining the best location for the nonembedded generators as well as the number of generators required to alleviate network problems. A control algorithm to transfer and reconnect customers is developed to ensure that the network voltage profile remains within specification under all plausible load conditions. Finally, simulations are presented to show the performance of the system over a typical maximum daily load profile with large stochastic load variations.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.

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Die wachsende Weltbevölkerung bedingt einen höheren Energiebedarf, dies jedoch unter der Beachtung der nachhaltigen Entwicklung. Die derzeitige zentrale Versorgung mit elektrischer Energie wird durch wenige Erzeugungsanlagen auf der Basis von fossilen Primärenergieträgern und Kernenergie bestimmt, die die räumlich verteilten Verbraucher zuverlässig und wirtschaftlich über ein strukturiertes Versorgungssystem beliefert. In den Elektrizitätsversorgungsnetzen sind keine nennenswerten Speicherkapazitäten vorhanden, deshalb muss die von den Verbrauchern angeforderte Energie resp. Leistung jederzeit von den Kraftwerken gedeckt werden. Bedingt durch die Liberalisierung der Energiemärkte und die geforderte Verringerung der Energieabhängigkeit Luxemburgs, unterliegt die Versorgung einem Wandel hin zu mehr Energieeffizienz und erhöhter Nutzung der dargebotsabhängigen Energiequellen. Die Speicherung der aus der Windkraft erzeugten elektrischen Energie, wird in den Hochleistungs-Bleiakkumulatoren, errichtet im ländlichen Raum in der Nähe der Windkraftwerke, eingespeichert. Die zeitversetzte Einspeisung dieser gespeicherten elektrischen Energie in Form von veredelter elektrischer Leistung während den Lastspitzen in das 20 kV-Versorgungsnetz der CEGEDEL stellt die Innovation in der luxemburgischen Elektrizitätsversorgung dar. Die Betrachtungen beschränken sich somit auf die regionale, relativ kleinräumige Einbindung der Windkraft in die elektrische Energieversorgung des Großherzogtums Luxemburg. Die Integration der Windkraft im Regionalbereich wird in den Vordergrund der Untersuchung gerückt. Überregionale Ausgleichseffekte durch Hochspannungsleitungen der 230/400 kV-Systeme werden außer Acht gelassen. Durch die verbrauchernahe Bereitstellung von elektrischer Spitzenleistung vermindern sich ebenfalls die Übertragungskosten aus den entfernten Spitzenlastkraftwerken, der Ausbau von Kraftwerkskapazitäten kann in die Zukunft verschoben werden. Die Emission von Treibhausgasen in thermischen Kraftwerken wird zum Teil reduziert. Die Berechnungen der Wirtschaftlichkeit von Hybridanlagen, zusammengesetzt aus den Windkraftwerken und den Hochleistungs-Bleiakkumulatoren bringen weitere Informationen zum Einsatz dieser dezentralen Speichern, als Partner der nachhaltigen Energieversorgung im ländlichen Raum. Die untersuchte Einspeisung von erneuerbarer Spitzenleistung lässt sich auch in die Entwicklungsländer übertragen, welche nicht über zentrale Kraftwerkskapazitäten und Verteilungsnetze verfügen.

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This paper reviews electricity consumption feedback literature to explore the potential of electricity feedback to affect residential consumers’ electricity usage patterns. The review highlights a substantial amount of literature covering the debate over the effectiveness of different feedback criteria to residential customer acceptance and overall conservation and peak demand reduction. Researchers studying the effects of feedback on everyday energy use have observed substantial variation in effect size, both within and between studies. Although researchers still continue to question the types of feedback that are most effective in encouraging conservation and peak load reduction, some trends have emerged. These include that feedback be received as quickly as possible to the time of consumption; be related to a standard; be clear and meaningful and where possible both direct and indirect feedback be customised to the customer. In general, the literature finds that feedback can reduce electricity consumption in homes by 5 to 20 per cent, but that significant gaps remain in our knowledge of the effectiveness and cost benefit of feedback.

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This paper suggests a supervisory control for storage units to provide load leveling in distribution networks. This approach coordinates storage units to charge during high generation and discharge during peak load times, while utilized to improve the network voltage profile indirectly. The aim of this control strategy is to establish power sharing on a pro rata basis for storage units. As a case study, a practical distribution network with 30 buses is simulated and the results are provided.

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One of the most common Demand Side Management programs consists of Time-of-Use (TOU) tariffs, where consumers are charged differently depending on the time of the day when they make use of energy services. This paper assesses the impacts of TOU tariffs on a dataset of residential users from the Province of Trento in Northern Italy in terms of changes in electricity demand, price savings, peak load shifting and peak electricity demand at substation level. Findings highlight that TOU tariffs bring about higher average electricity consumption and lower payments by consumers. A significant level of load shifting takes place for morning peaks. However, issues with evening peaks are not resolved. Finally, TOU tariffs lead to increases in electricity demand for substations at peak time.

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Background. We investigated the likely impact of vaccines on the prevalence of and morbidity due to Chlamydia trachomatis (chlamydia) infections in heterosexual populations. Methods.An individual‐based mathematical model of chlamydia transmission was developed and linked to the infection course in chlamydia‐infected individuals. The model describes the impact of a vaccine through its effect on the chlamydial load required to infect susceptible individuals (the “critical load”), the load in infected individuals, and their subsequent infectiousness. The model was calibrated using behavioral, biological, and clinical data. Results.A fully protective chlamydia vaccine administered before sexual debut can theoretically eliminate chlamydia epidemics within 20 years. Partially effective vaccines can still greatly reduce the incidence of chlamydia infection. Vaccines should aim primarily to increase the critical load in susceptible individuals and secondarily to decrease the peak load and/or the duration of infection in vaccinated individuals who become infected. Vaccinating both sexes has a beneficial impact on chlamydia‐related morbidity, but targeting women is more effective than targeting men. Conclusions.Our findings can be used in laboratory settings to evaluate vaccine candidates in animal models, by regulatory bodies in the promotion of candidates for clinical trials, and by public health authorities in deciding on optimal intervention strategies.

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Foam-filled conical tubes have recently emerged as efficient energy absorbing devices to mitigate the adverse effects of impacts. The primary aim of this thesis was to generate research and design information on the impact and energy absorption response of empty and foam-filled conical tubes, and to facilitate their application in energy absorbing systems under axial and oblique loading conditions representative of those typically encountered in crashworthiness and impact applications. Finite element techniques supported by experiments and existing results were used in the investigation. Major findings show that the energy absorption response can be effectively controlled by varying geometry and material parameters. A useful empirical formula was developed for providing engineering designers with an initial estimate of the load ratio and hence energy absorption performances of these devices. It was evident that foam-filled conical tubes enhance the energy absorption capacity and stabilise the crush response for both axial and oblique impact loading without a significant increase in the initial peak load. This is practically beneficial when higher kinetic energy needs to be absorbed, thus reducing the impact force transmitted to the protected structure and occupants. Such tubes also increase and maintain the energy absorption capacity under global bending as well as minimise the reduction of energy absorption capacity with increasing load angle. Furthermore, the results also highlight the feasibility of adding a foam-filled conical tube as a supplementary device in energy absorbing systems, since the overall energy absorption performance of such systems can be favourably enhanced by only including a relatively small energy absorbing device. Above all, the results demonstrate the superior performance of foam-filled conical tube for mitigating impact energy in impact and crashworthiness applications.

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The growing demand of air-conditioning is one of the largest contributors to Australia’s overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The model developed demand side response model to allow consumers to manage and control air conditioning for every period, it is called intelligent control. This research investigates optimal response of end-user toward electricity price for several cases in the near future, such as: no spike, spike and probability spike price cases. The results indicate the potential of the scheme to achieve energy savings, reducing electricity bills (costs) to the consumer and targeting best economic performance for electrical generation distribution and transmission.

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A novel intelligent online demand side management system is proposed for peak load management in low-voltage distribution networks. This method uses low-cost controllers with low-bandwidth two-way communication installed in custumers’ premises and at distribution transformers to manage the peak load while maximising customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by simulation of three different feeder types.

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Increasing penetration of photovoltaic (PV) as well as increasing peak load demand has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and Battery Energy Storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop based BES system is evaluated for rural and urban scenarios (having different R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low resistance feeder), whereas, coordinated PV and BES support is required for the rural scenario (high resistance feeder). Constant as well as variable droop based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes is presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data is used to verify the efficacy of the proposed method.

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This paper presents an optimisation algorithm to maximize the loadability of single wire earth return (SWER) by minimizing the cost of batteries and regulators considering the voltage constraints and thermal limits. This algorithm, that finds the optimum location of batteries and regulators, uses hybrid discrete particle swarm optimization and mutation (DPSO + Mutation). The simulation results on realistic highly loaded SWER network show the effectiveness of using battery to improve the loadability of SWER network in a cost-effective way. In this case, while only 61% of peak load can be supplied without violating the constraints by existing network, the loadability of the network is increased to peak load by utilizing two battery sites which are located optimally. That is, in a SWER system like the studied one, each installed kVA of batteries, optimally located, supports a loadability increase as 2 kVA.

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A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.