Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

A Gradient-Type Method For Real-Time State Estimation Of Water Distribution Networks

Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.

Neustonic distribution of decapod planktonic stages and competence of brachyuran megalopae in coastal waters

Settlement rate may not reflect larval supply to coastal waters in different marine invertebrates and demersal fishes. The importance of near-shore oceanography and behaviour of late larval stages may be underestimated. The present study conducted neustonic sampling over station grids and along full-length transects at two embayments in south-eastern Brazil to (1) compare diurnal and nocturnal occurrence of most frequent decapod stages to assess their vertical movements, (2) describe the formation of larval patches and (3) measure competence of crab megalopae according to their distance to recruitment grounds. Several shrimp species apparently undergo a diel vertical migration, swimming crab megalopae showed no vertical movements and megalopae of the intertidal crab Pachygrapsus transversus revealed a reversed vertical migration. During the day, crab megalopae aggregated in convergence zones just below surface slicks. These larvae consisted of advanced, pre-moult stages, at both mid-bay and near-shore patches. Competence, measured as the time to metamorphosis in captivity, was similar between larval patches within each taxon. Yet, subtidal portunids moulted faster to juveniles than intertidal grapsids, possibly because they were closer to settlement grounds. Megalopae of Pachygrapsus from benthic collectors moulted faster than those from bay areas. These results suggest that alternative vertical migration patterns of late megalopae favour onshore transport, and actual competence takes place very close to suitable substrates, where larvae may remain for days before settlement. Lack of correlation between larval supply and settlement for Pachygrapsus suggests that biological processes, besides onshore transport, may play an important role in determining settlement success of coastal crabs.

Geostatistical analysis of the spatial distribution of Rotylenchulus reniformis on cotton cultivated under crop rotation

The spatial distribution of Rotylenchulus reniformis on cotton cultivated in crop rotation with sorghum-peanut-velvetbean was studied using geostatistics. The experimental field, which had been continuously cropped with cotton for 20 years, comprised two 32 x 48 m-grids, each divided in sixty-four 4 x 6 in sampling plots. For all crops, 300 cm(3) soil samples were taken at the center of each plot at crop germination (Pi) and again at harvest (Pf), from which the numbers of nematodes were determined. The results revealed that the spatial distribution of R. reniformis was highly aggregated and with the aid of geostatistical techniques the nematode intensities were mapped and the risk areas accurately identified. Consequently, geostatistics is here considered a useful tool for planning nematode control strategies, particularly in precision agriculture.

A multi-objective evaluation of the impact of the penetration of Distributed Generation

This paper proposes a methodology to consider the effects of the integration of DG on planning. Since DG has potential to defer investments in networks, the impact of DG on grid capacity is evaluated. A multi-objective optimization tool based on the meta-heuristic MEPSO is used, supporting an alternative approach to exploiting the Pareto front features. Tests were performed in distinct conditions with two well-known distribution networks: IEEE-34 and IEEE-123. The results combined minimization and maximization in order to produce different Pareto fronts and determine the extent of the impact caused by DG. The analysis provides useful information, such as the identification of futures that should be considered in planning. A future means a set of realizations of all uncertainties. MEPSO also presented a satisfactory performance in obtaining the Pareto fronts. © 2011 IEEE.

Advanced network reconfiguration system applied to CEMIG-D system

In the network reconfiguration context, the challenge nowadays is to improve the system in order to get intelligent systems that are able to monitor the network and produce refined information to support the operator decisions in real time, this because the network is wide, ramified and in some places difficult to access. The objective of this paper is to present the first results of the network reconfiguration algorithm that has been developed to CEMIG-D. The algorithm's main idea is to provide a new network configuration, after an event (fault or study case), based on an initial condition and aiming to minimize the affected load, considering the restrictions of load flow equations, maximum capacity of the lines as well as equipments and substations, voltage limits and system radial operation. Initial tests were made considering real data from the system, provided by CEMIG-D and it reveals very promising results. © 2013 IEEE.

Analysis of efficiency and rationality in a sugar-alcohol mill using hyperboloid a-load and potency

Brazil is the world's largest producer of sugar cane and which in the state of São Paulo concentrate the greatest amount of sugar cane field of the country. The sugar-alcohol sector has the capacity to produce sufficient thermal and electrical energy to be used in their process of production and commercialize of surplus in electricity distribution network. Therefore it is necessary to evaluate the energy efficiency and rationality within the mill. Accordingly this research proposed analyze the sugar-alcohol mill's sectors globally and individually, located in the west center of the São Paulo state, using the valuation methodology employed by the Agência Nacional de Energia Elétrica (ANEEL) in the industries that do not have systems of cogeneration. In this analysis, the hyperboloids of load and potency were applied based on the indexes of potency factor and load factor that allow estimate the efficiency and rationality. © 2013 IEEE.

Performance analysis of smart grid communication protocol DNP3 over TCP/IP in a heterogeneous traffic environment

This paper presents simulation results of the DNP3 communication protocol over a TCP/IP network, for Smart Grid applications. The simulation was performed using the NS-2 network simulator. This study aimed to use the simulation to verify the performance of the DNP3 protocol in a heterogeneous LAN. Analyzing the results it was possible to verify that the DNP3 over a heterogeneous traffic network, with communication channel capacity between 60 and 85 percent, it works well with low packet loss and low delay, however, with traffic values upper 85 percent, the DNP3 usage becomes unfeasible because the information lost, re-transmissions and latency are significantly increased. © 2013 IEEE.

Metodologia de projeto cooperativo para condicionadores de qualidade de energia

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Disturbance detection for optimal database storage in electrical distribution systems using artificial immune systems with negative selection

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

Análise do impacto de sistemas fotovoltaicos conectados à rede de distribuição na qualidade da energia de uma smart city: Análise do impacto de sistemas fotovoltaicos conectados à rede de distribuição na qualidade da energia de uma smart city

Pós-graduação em Engenharia Elétrica - FEIS

Active power reserve for frequency control provided by distributed generators in distribution networks

In a smart grid environment, attention should be paid not only to the power supplied to satisfy loads and system losses but also to the services necessary to provide security and stability to the system: the so-called ancillary services. As they are well known the benefits that distributed generation can bring to electrical systems and to the environment, in this work the possibility that active power reserve for frequency control could be provided by distributed generators (DGs) in an efficient and economical way is explored. The proposed methodology was tested using the IEEE 34-bus distribution test system. The results show improvements in the capacity of the system for this ancillary service and decrease in system losses and payments of the distribution system operator to the DGs.

Análise de desempenho de redes de comunicação wireless em aplicações de Smart Grid

Pós-graduação em Engenharia Elétrica - FEIS

Designing piezoresistive plate-based sensors with distribution of piezoresistive material using topology optimization

Piezoresistive sensors are commonly made of a piezoresistive membrane attached to a flexible substrate, a plate. They have been widely studied and used in several applications. It has been found that the size, position and geometry of the piezoresistive membrane may affect the performance of the sensors. Based on this remark, in this work, a topology optimization methodology for the design of piezoresistive plate-based sensors, for which both the piezoresistive membrane and the flexible substrate disposition can be optimized, is evaluated. Perfect coupling conditions between the substrate and the membrane based on the `layerwise' theory for laminated plates, and a material model for the piezoresistive membrane based on the solid isotropic material with penalization model, are employed. The design goal is to obtain the configuration of material that maximizes the sensor sensitivity to external loading, as well as the stiffness of the sensor to particular loads, which depend on the case (application) studied. The proposed approach is evaluated by studying two distinct examples: the optimization of an atomic force microscope probe and a pressure sensor. The results suggest that the performance of the sensors can be improved by using the proposed approach.

Middleware for quality-based context distribution in mobile systems

The continuous advancements and enhancements of wireless systems are enabling new compelling scenarios where mobile services can adapt according to the current execution context, represented by the computational resources available at the local device, current physical location, people in physical proximity, and so forth. Such services called context-aware require the timely delivery of all relevant information describing the current context, and that introduces several unsolved complexities, spanning from low-level context data transmission up to context data storage and replication into the mobile system. In addition, to ensure correct and scalable context provisioning, it is crucial to integrate and interoperate with different wireless technologies (WiFi, Bluetooth, etc.) and modes (infrastructure-based and ad-hoc), and to use decentralized solutions to store and replicate context data on mobile devices. These challenges call for novel middleware solutions, here called Context Data Distribution Infrastructures (CDDIs), capable of delivering relevant context data to mobile devices, while hiding all the issues introduced by data distribution in heterogeneous and large-scale mobile settings. This dissertation thoroughly analyzes CDDIs for mobile systems, with the main goal of achieving a holistic approach to the design of such type of middleware solutions. We discuss the main functions needed by context data distribution in large mobile systems, and we claim the precise definition and clean respect of quality-based contracts between context consumers and CDDI to reconfigure main middleware components at runtime. We present the design and the implementation of our proposals, both in simulation-based and in real-world scenarios, along with an extensive evaluation that confirms the technical soundness of proposed CDDI solutions. Finally, we consider three highly heterogeneous scenarios, namely disaster areas, smart campuses, and smart cities, to better remark the wide technical validity of our analysis and solutions under different network deployments and quality constraints.