913 resultados para real power loss


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The rural electrification is characterized by geographical dispersion of the population, low consumption, high investment by consumers and high cost. Moreover, solar radiation constitutes an inexhaustible source of energy and in its conversion into electricity photovoltaic panels are used. In this study, equations were adjusted to field conditions presented by the manufacturer for current and power of small photovoltaic systems. The mathematical analysis was performed on the photovoltaic rural system I- 100 from ISOFOTON, with power 300 Wp, located at the Experimental Farm Lageado of FCA/UNESP. For the development of such equations, the circuitry of photovoltaic cells has been studied to apply iterative numerical methods for the determination of electrical parameters and possible errors in the appropriate equations in the literature to reality. Therefore, a simulation of a photovoltaic panel was proposed through mathematical equations that were adjusted according to the data of local radiation. The results have presented equations that provide real answers to the user and may assist in the design of these systems, once calculated that the maximum power limit ensures a supply of energy generated. This real sizing helps establishing the possible applications of solar energy to the rural producer and informing the real possibilities of generating electricity from the sun.

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The effect of different methods of soil preparation on soil moisture loss, weed growth and soil resistance to penetration has been quantified for the Latosols of Bebedouro experiment station of CPATSA-EMBRAPA, Petrolina,PE, Brazil. The methods studied are manual preparation, preparation by animal drawn wheeled tool carrier and tractorized implements. The drying characteristics of three fields with different soil physical properties were studied prior to conducting the experiment. The different methods of soil preparation caused the soil moisture loss differently. The plot prepared by animal drawn tool carrier retained more moisture for longer time even at deeper layers. The soil resistance to penetration on the surface increased with time with little variation at deeper layers.

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Background: Remote telemonitoring holds great potential to augment management of patients with coronary heart disease (CHD) and atrial fibrillation (AF) by enabling regular physiological monitoring during physical activity. Remote physiological monitoring may improve home and community exercise-based cardiac rehabilitation (exCR) programs and could improve assessment of the impact and management of pharmacological interventions for heart rate control in individuals with AF.

Objective: Our aim was to evaluate the measurement validity and data transmission reliability of a remote telemonitoring system comprising a wireless multi-parameter physiological sensor, custom mobile app, and middleware platform, among individuals in sinus rhythm and AF.

Methods: Participants in sinus rhythm and with AF undertook simulated daily activities, low, moderate, and/or high intensity exercise. Remote monitoring system heart rate and respiratory rate were compared to reference measures (12-lead ECG and indirect calorimeter). Wireless data transmission loss was calculated between the sensor, mobile app, and remote Internet server.

Results: Median heart rate (-0.30 to 1.10 b∙min-1) and respiratory rate (-1.25 to 0.39 br∙min-1) measurement biases were small, yet statistically significant (all P≤.003) due to the large number of observations. Measurement reliability was generally excellent (rho=.87-.97, all P<.001; intraclass correlation coefficient [ICC]=.94-.98, all P<.001; coefficient of variation [CV]=2.24-7.94%), although respiratory rate measurement reliability was poor among AF participants (rho=.43, P<.001; ICC=.55, P<.001; CV=16.61%). Data loss was minimal (<5%) when all system components were active; however, instability of the network hosting the remote data capture server resulted in data loss at the remote Internet server during some trials.

Conclusions: System validity was sufficient for remote monitoring of heart and respiratory rates across a range of exercise intensities. Remote exercise monitoring has potential to augment current exCR and heart rate control management approaches by enabling the provision of individually tailored care to individuals outside traditional clinical environments.

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Consumer participation occurs in all Victorian public mental health services. Area mental health services employ consumer consultants to enhance consumer participation across the network. Ongoing support of management is essential to the success of consumer participation. This project aimed to explore understandings of consumer participation from a manager's perspective. Semistructured interviews were conducted with seven participants in this qualitative, interpretive study. The thematic analysis revealed the complexities around defining consumer participation and demonstrated the difficulties and possible reasons as to why there is no real clarity between managers, service providers, and consumers as to what consumer participation should look like. Power and change were the primary themes. Power and the overwhelming consensus that the medical model and those working within it hold the most power was strongly represented in this study. Legislation and workplace settings were seen as considerable factors adding to the disempowerment of consumers within an already disempowering mental health system. Change was the other main theme that emerged, with culture and attitudes of the old ‘institutionalized’ thinking that still pervades some pockets of mental health services being seen as the major barriers to change. The role of the consumer consultant was a prominent subtheme, with their role in training and the education of workers seen as an essential and positive way to progress consumer participation. These findings demonstrate that managers consider there to be hope for consumers, brought about by collective action and lobbying, and through consumer participation in less-restrictive parts of the service (community settings).

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Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

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Drawing on interpretations of Foucault's techniques of power, we explored the discourses and power relations operative between groups of girls that appeared to influence their participation in Physical Education (PE) and outside of school in sport and physical activity (PA) in rural and regional communities. Interviews and focus groups were conducted in eight secondary schools with female students from Year 9 (n = 22) and 10 (n = 116). Dominant gendered and performance discourses were active in shaping girls’ construction of what it means to be active or ‘sporty’, and these identity positions were normalised and valued. The perceived and real threat of their peer's gaze as a form of surveillance acted to further perpetuate the power of performance discourses; whereby girls measured and (self) regulated their participation. Community settings were normalised as being exclusively for skilled performers and girls self-regulated their non-participation according to judgements made about their own physical abilities. These findings raise questions about the ways in which power relations, as forged in broader sociocultural and institutional discourse–power relations, can infiltrate the level of the PE classroom to regulate and normalise practices in relation to their, and others, PA participation.

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Microgrid (MG) power system plays an important role to fulfill reliable and secure energy supply to critical loads of communities as well as for communities in remote area. Distributed Generation (DG) sources integrated in a MG provides numerous benefits, at the same time leads to power quality issues in the MG power distribution network. Power Quality (PQ) issue arises due to the integration of an intermittent nature of Renewable Energy (RE) sources with advanced Power Electronics (PE) converter technology. Also, presence of non-linear and unbalancing loads in MG seems to affect PQ of the energy supply in power distribution network. In this paper, PQ impacts like; power variation, voltage variation, Total Harmonic Distortion (THD), and Unbalance voltage level have been analysed in Low Voltage (LV) distribution network of typical MG power system model. In this study, development of MG model and PQ impact analysis through simulation has been done in PSS-Sincal software environment. Analysis results from the study can be used as a guideline for developing a real and independent MG power system with improved PQ conditions.

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Increasing returns to scale and firms' market power are two potential sources of sunspot expectations in neoclassical models. We show that in New Keynesian models, returns to scale and market power can have fundamentally different implications for broad macroeconomic issues, including self-fulfilling expectations, depending on the nature of price rigidity. Our findings suggest that the design of stabilization monetary policy can depend on precise knowledge about the economy's real and nominal features. Therefore, a clear understanding of the specific economic environment and its relevance to monetary policymaking for ensuring macroeconomic stability can be an integrated part of monetary policy practice.

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This paper presents a robust control design scheme for a multidistributed energy resource (DER) microgrid for power sharing in both interconnected and islanded modes. The scheme is proposed for micgrogrids consisting of photovoltaic (PV) units and wind turbine driven doubly fed induction generators (DFIGs). A battery is integrated with each of the wind and solar DER units. The control scheme has two levels: 1) one centralized multi-input–multi-output robust controller for regulating the set reference active and reactive powers and 2) local real and reactive power droop con-trollers, one on each DER unit. The robust control scheme utilizes multivariable H1 control to design controllers that are robust to the changes in the network and system nonlinearities. The effectiveness of the proposed controller is demonstrated through large-distur-bance simulations, with complete nonlinear models, on a test micro-grid. It is found that the power sharing controllers provide excellent performance against large disturbances and load variations during islanding transients and interconnected operation.

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Due to low electricity rates at nighttime, home charging for electric vehicles (EVs) is conventionally favored. However, the recent tendency in support of daytime workplace charging that absorbs energy produced by solar photovoltaic (PV) panels appears to be the most promising solution to facilitating higher PV and EV penetration in the power grid. This paper studies optimal sizing of workplace charging stations considering probabilistic reactive power support for plug-in hybrid electric vehicles (PHEVs), which are powered by PV units in medium voltage (MV) commercial networks. In this study, analytical expressions are first presented to estimate the size of charging stations integrated with PV units with an objective of minimizing energy losses. These stations are capable of providing reactive power support to the main grid in addition to charging PHEVs while considering the probability of PV generation. The study is further extended to investigate the impact of time-varying voltage-dependent charging load models on PV penetration. The simulation results obtained on an 18-bus test distribution system show that various charging load models can produce dissimilar levels of PHEV and PV penetration. Particularly, the maximum energy loss and peak load reductions are achieved at 70.17% and 42.95% respectively for the mixed charging load model, where the system accommodates respective PHEV and PV penetration levels of 9.51% and 50%. The results of probabilistic voltage distributions are also thoroughly reported in the paper.

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Using robotic systems for many missions that require power distribution can decrease the need for human intervention in such missions significantly. For accomplishing this capability a robotic system capable of autonomous navigation, power systems adaptation, and establishing physical connection needs to be developed. This thesis presents developed path planning and navigation algorithms for an autonomous ground power distribution system. In this work, a survey on existing path planning methods along with two developed algorithms by author is presented. One of these algorithms is a simple path planner suitable for implementation on lab-size platforms. A navigation hierarchy is developed for experimental validation of the path planner and proof of concept for autonomous ground power distribution system in lab environment. The second algorithm is a robust path planner developed for real-size implementation based on lessons learned from lab-size experiments. The simulation results illustrates that the algorithm is efficient and reliable in unknown environments. Future plans for developing intelligent power electronics and integrating them with robotic systems is presented. The ultimate goal is to create a power distribution system capable of regulating power flow at a desired voltage and frequency adaptable to load demands.

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Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

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Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system’s dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

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With the eye-catching advances in sensing technologies, smart water networks have been attracting immense research interest in recent years. One of the most overarching tasks in smart water network management is the reduction of water loss (such as leaks and bursts in a pipe network). In this paper, we propose an efficient scheme to position water loss event based on water network topology. The state-of-the-art approach to this problem, however, utilizes the limited topology information of the water network, that is, only one single shortest path between two sensor locations. Consequently, the accuracy of positioning water loss events is still less desirable. To resolve this problem, our scheme consists of two key ingredients: First, we design a novel graph topology-based measure, which can recursively quantify the "average distances" for all pairs of senor locations simultaneously in a water network. This measure will substantially improve the accuracy of our positioning strategy, by capturing the entire water network topology information between every two sensor locations, yet without any sacrifice of computational efficiency. Then, we devise an efficient search algorithm that combines the "average distances" with the difference in the arrival times of the pressure variations detected at sensor locations. The viable experimental evaluations on real-world test bed (WaterWiSe@SG) demonstrate that our proposed positioning scheme can identify water loss event more accurately than the best-known competitor.

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Non-orthogonal multiple access (NOMA) is emerging as a promising multiple access technology for the fifth generation cellular networks to address the fast growing mobile data traffic. It applies superposition coding in transmitters, allowing simultaneous allocation of the same frequency resource to multiple intra-cell users. Successive interference cancellation is used at the receivers to cancel intra-cell interference. User pairing and power allocation (UPPA) is a key design aspect of NOMA. Existing UPPA algorithms are mainly based on exhaustive search method with extensive computation complexity, which can severely affect the NOMA performance. A fast proportional fairness (PF) scheduling based UPPA algorithm is proposed to address the problem. The novel idea is to form user pairs around the users with the highest PF metrics with pre-configured fixed power allocation. Systemlevel simulation results show that the proposed algorithm is significantly faster (seven times faster for the scenario with 20 users) with a negligible throughput loss than the existing exhaustive search algorithm.