859 resultados para electricity distribution networks


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This paper introduces a parallel implementation of an agent-based model applied to electricity distribution grids. A fine-grained shared memory parallel implementation is presented, detailing the way the agents are grouped and executed on a multi-threaded machine, as well as the way the model is built (in a composable manner) which is an aid to the parallelisation. Current results show a medium level speedup of 2.6, but improvements are expected by incor-porating newer distributed or parallel ABM schedulers into this implementa-tion. While domain-specific, this parallel algorithm can be applied to similarly structured ABMs (directed acyclic graphs).

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Plug-in electric vehicles will soon be connected to residential distribution networks in high quantities and will add to already overburdened residential feeders. However, as battery technology improves, plug-in electric vehicles will also be able to support networks as small distributed generation units by transferring the energy stored in their battery into the grid. Even though the increase in the plug-in electric vehicle connection is gradual, their connection points and charging/discharging levels are random. Therefore, such single-phase bidirectional power flows can have an adverse effect on the voltage unbalance of a three-phase distribution network. In this article, a voltage unbalance sensitivity analysis based on charging/discharging levels and the connection point of plug-in electric vehicles in a residential low-voltage distribution network is presented. Due to the many uncertainties in plug-in electric vehicle ratings and connection points and the network load, a Monte Carlo-based stochastic analysis is developed to predict voltage unbalance in the network in the presence of plug-in electric vehicles. A failure index is introduced to demonstrate the probability of non-standard voltage unbalance in the network due to plug-in electric vehicles.

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Single phase distributed energy resources (DERs) can cause voltage rise along distribution feeder and power imbalance among the phases. Usually transformer tap setting are used to mitigate voltage drop along feeders. However this can aggravate the voltage rise problem when DERs are connected. Moreover if the power generation in a phase is more than its load demand, the excess power in that phase will be fed back to the transmission network. In this paper, a unified power quality compensator (UPQC) has been utilized to alleviate the voltage quality excess power circulation problems. Through analysis and simulation results, the mode of operation of UPQC is highlighted. The proposals are validated through extensive digital computer simulation studies using PSCAD and MATLAB.

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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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In this paper, a loss reduction planning in electric distribution networks is presented based on the successful experiences in distribution utilities of IRAN and some developed countries. The necessary technical and economical parameters of planning are calculated from related projects in IRAN. Cost, time, and benefits of every sub-program including seven loss reduction approaches are determined. Finally, the loss reduction program, the benefit per cost, and the return of investment in optimistic and pessimistic conditions are introduced.

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Installation of domestic rooftop photovoltaic cells (PVs) is increasing due to feed–in tariff and motivation driven by environmental concerns. Even though the increase in the PV installation is gradual, their locations and ratings are often random. Therefore, such single–phase bi–directional power flow caused by the residential customers can have adverse effect on the voltage imbalance of a three–phase distribution network. In this chapter, a voltage imbalance sensitivity analysis and stochastic evaluation are carried out based on the ratings and locations of single–phase grid–connected rooftop PVs in a residential low voltage distribution network. The stochastic evaluation, based on Monte Carlo method, predicts a failure index of non–standard voltage imbalance in the network in presence of PVs. Later, the application of series and parallel custom power devices are investigated to improve voltage imbalance problem in these feeders. In this regard, first, the effectiveness of these two custom power devices is demonstrated vis–à–vis the voltage imbalance reduction in feeders containing rooftop PVs. Their effectiveness is investigated from the installation location and rating points of view. Later, a Monte Carlo based stochastic analysis is utilized to investigate their efficacy for different uncertainties of load and PV rating and location in the network. This is followed by demonstrating the dynamic feasibility and stability issues of applying these devices in the network.

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This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.

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Integrating Photovoltaic (PV) systems with battery energy storage in the distribution network will be essential to allow for continued uptake of domestic PV system installations. With increasing concerns regarding environmental and climate change issues, incorporating sources of renewable energy into power networks across the world will be key for a sustainable future. Australia is well placed to utilise solar energy as a significant component of its future energy generation and within the last 5 years there has been a rapid growth in the penetration levels seen by the grid. This growth of PV systems is causing a number of issues including intermittency of supply, negative power flow and voltage rises. Using the simulator tool GridLAB-D with a model of a typical South-East Queensland (SEQ) 11 kV distribution feeder, the effect of various configurations of PV systems have been offset with Battery Energy Storage Systems (BESS). From this, combinations of PV and storage that are most effective at mitigating the issues were explored.

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This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

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This chapter presents the stability analysis based on bifurcation theory of the distribution static compensator (DSTATCOM) operating both in current control mode as in voltage control mode. The bifurcation analysis allows delimiting the operating zones of nonlinear power systems and hence the computation of these boundaries is of interest for practical design and planning purposes. Suitable mathematical representations of the DSTATCOM are proposed to carry out the bifurcation analyses efficiently. The stability regions in the Thevenin equivalent plane are computed for different power factors at the Point of Common Coupling (PCC). In addition, the stability regions in the control gain space are computed, and the DC capacitor and AC capacitor impact on the stability are analyzed in detail. It is shown through bifurcation analysis that the loss of stability in the DSTATCOM is in general due to the emergence of oscillatory dynamics. The observations are verified through detailed simulation studies.

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In this thesis various schemes using custom power devices for power quality improvement in low voltage distribution network are studied. Customer operated distributed generators makes a typical network non-radial and affect the power quality. A scheme considering different algorithm of DSTATCOM is proposed for power circulation and islanded operation of the system. To compensate reactive power overflow and facilitate unity power factor, a UPQC is introduced. Stochastic analysis is carried out for different scenarios to get a comprehensive idea about a real life distribution network. Combined operation of static compensator and voltage regulator is tested for the optimum quality and stability of the system.

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This paper presents simulation results for future electricity grids using an agent-based model developed with MODAM (MODular Agent-based Model). MODAM is introduced and its use demonstrated through four simulations based on a scenario that expects a rise of on-site renewable generators and electric vehicles (EV) usage. The simulations were run over many years, for two areas in Townsville, Australia, capturing variability in space of the technology uptake, and for two charging methods for EV, capturing people's behaviours and their impact on the time of the peak load. Impact analyses of these technologies were performed over the areas, down to the distribution transformer level, where greater variability of their contribution to the assets peak load was observed. The MODAM models can be used for different purposes such as impact of renewables on grid sizing, or on greenhouse gas emissions. The insights gained from using MODAM for technology assessment are discussed.