Intelligent energy management based on SCADA system in a real Microgrid for smart building applications

Energy management is one of the main challenges in Microgrids (MGs) applied to Smart Buildings (SBs). Hence, more studies are indispensable to consider both modeling and operating aspects to utilize the upcoming results of the system for the different applications. This paper presents a novel energy management architecture model based on complete Supervisory Control and Data Acquisition (SCADA) system duties in an educational building with an MG Laboratory (Lab) testbed, which is named LAMBDA at the Electrical and Energy Engineering Department of the Sapienza University of Rome. The LAMBDA MG Lab simulates in a small scale a SB and is connected with the DIAEE electrical network. LAMBDA MG is composed of a Photovoltaic generator (PV), a Battery Energy Storage System (BESS), a smart switchboard (SW), and different classified loads (critical, essential, and normal) some of which are manageable and controllable (lighting, air conditioning, smart plugs operating into the LAB). The aim of the LAMBDA implementation is making the DIAEE smart for energy saving purposes. In the LAMBDA Lab, the communication architecture consists in a complex of master/slave units and actuators carried out by two main international standards, Modbus (industrial serial standard for electrical and technical monitoring systems) and Konnex (an open standard for commercial and domestic building automation). Making the electrical department smart causes to reduce the required power from the main grid. Hence, to achieve the aims, results have been investigated in two modes. Initially, the real-time mode based on the SCADA system, which reveals real daily power consumption and production of different sources and loads. Next, the simulation part is assigned to shows the behavior of the main grid, loads and BESS charging and discharging based on energy management system. Finally, the proposed model has been examined in different scenarios and evaluated from the economic aspect

Intelligent energy management based on SCADA system in a real Microgrid for smart building applications

Energy management is one of the main challenges in Microgrids (MGs) applied to Smart Buildings (SBs). Hence, more studies are indispensable to consider both modeling and operating aspects to utilize the upcoming results of the system for the different applications. This paper presents a novel energy management architecture model based on complete Supervisory Control and Data Acquisition (SCADA) system duties in an educational building with an MG Laboratory (Lab) testbed, which is named LAMBDA at the Electrical and Energy Engineering Department of the Sapienza University of Rome. The LAMBDA MG Lab simulates in a small scale a SB and is connected with the DIAEE electrical network. LAMBDA MG is composed of a Photovoltaic generator (PV), a Battery Energy Storage System (BESS), a smart switchboard (SW), and different classified loads (critical, essential, and normal) some of which are manageable and controllable (lighting, air conditioning, smart plugs operating into the LAB). The aim of the LAMBDA implementation is making the DIAEE smart for energy saving purposes. In the LAMBDA Lab, the communication architecture consists in a complex of master/slave units and actuators carried out by two main international standards, Modbus (industrial serial standard for electrical and technical monitoring systems) and Konnex (an open standard for commercial and domestic building automation). Making the electrical department smart causes to reduce the required power from the main grid. Hence, to achieve the aims, results have been investigated in two modes. Initially, the real-time mode based on the SCADA system, which reveals real daily power consumption and production of different sources and loads. Next, the simulation part is assigned to shows the behavior of the main grid, loads and BESS charging and discharging based on energy management system. Finally, the proposed model has been examined in different scenarios and evaluated from the economic aspect

Results from the translation and adaptation of the Iranian Short-Form McGill Pain Questionnaire (I-SF-MPQ): preliminary evidence of its reliability, construct validity and sensitivity in an Iranian pain population

<p>Abstract</p> <p>Background</p> <p>The Short Form McGill Pain Questionnaire (SF-MPQ) is one of the most widely used instruments to assess pain. The aim of this study was to translate and culturally adapt the questionnaire for Farsi (the official language of Iran) speakers in order to test its reliability and sensitivity.</p> <p>Methods</p> <p>We followed Guillemin's guidelines for cross-cultural adaption of health-related measures, which include forward-backward translations, expert committee meetings, and face validity testing in a pilot group. Subsequently, the questionnaire was administered to a sample of 100 diverse chronic pain patients attending a tertiary pain and rehabilitation clinic. In order to evaluate test-retest reliability, patients completed the questionnaire in the morning and early evening of their first visit. Finally, patients were asked to complete the questionnaire for the third time after completing a standardized treatment protocol three weeks later. Intraclass correlation coefficient (ICC) was used to evaluate reliability. We used principle component analysis to assess construct validity.</p> <p>Results</p> <p>Ninety-two subjects completed the questionnaire both in the morning and in the evening of the first visit (test-retest reliability), and after three weeks (sensitivity to change). Eight patients who did not finish treatment protocol were excluded from the study. Internal consistency was found by Cronbach's alpha to be 0.951, 0.832 and 0.840 for sensory, affective and total scores respectively. ICC resulted in 0.906 for sensory, 0.712 for affective and 0.912 for total pain score. Item to subscale score correlations supported the convergent validity of each item to its hypothesized subscale. Correlations were observed to range from r²= 0.202 to r²= 0.739. Sensitivity or responsiveness was evaluated by pair t-test, which exhibited a significant difference between pre- and post-treatment scores (p < 0.001).</p> <p>Conclusion</p> <p>The results of this study indicate that the Iranian version of the SF-MPQ is a reliable questionnaire and responsive to changes in the subscale and total pain scores in Persian chronic pain patients over time.</p

Optimal operation of a real power hub based on PV/FC/GenSet/BESS and demand response under uncertainty

Due to global concerns about environmental issues, renewable energy sources (RESs), such as photovoltaics (PV), Fuel Cells (FC), and wind turbines, play an outstanding role in energy production. Also, other devices are needed to achieve a smart grid. First of all, a Microgrid (MG), as a smart grid, must be equipped by the Battery Energy Storage System (BESS) due to its astonishing advantages, such as providing power when RESs are not generating power, power quality improvement, RES integration facilitation, and financial benefits. Secondly, distributed generators should be installed to reduce dependency of MG on the main grid. In this paper, a cost-based mathematical optimization is used to evaluate the optimal amount of imported power from the main grid to the LAMBDA lab MG testbed, which is placed at Sapienza University of Rome. In this regard, this study considers four scenarios based on using different source, including PV array, FC and main grid, for load satisfaction. The LAMBDA lab is considered as a power hub with three optional inputs and an electrical demand in output. In addition, this study considers PV production and load demand as indeterministic parameters and evaluates the problem under uncertainties. As a result, a robust optimization problem is defined, and a powerful optimization function is used to reach the optimal power received from main grid

Is there an association between lumbosacral radiculopathy and painful gluteal trigger points? A cross-sectional study

Objective: The objective of this study was to compare the prevalence of gluteal trigger point in patients with lumbosacral radiculopathy with that in healthy volunteers. Design: In a cross-sectional, multistage sampling method, patients with clinical, electromyographic, and magnetic resonance imaging findings consistent with lumbosacral radiculopathy were examined for the presence of gluteal trigger point. Age- and sex-matched clusters of healthy volunteers were selected as the control group. The primary outcome of the study was the presence or absence of gluteal trigger point in the gluteal region of the patients and the control group. Results: Of 441 screened patients, 271 met all the inclusion criteria for lumbosacral radiculopathy and were included in the study. Gluteal trigger point was identified in 207 (76.4) of the 271 patients with radiculopathy, compared with 3 (1.9) of 152 healthy volunteers (P < 0.001). The location of gluteal trigger point matched the side of painful radiculopathy in 74.6 of patients with a unilateral radicular pain. There was a significant correlation between the side of the gluteal trigger point and the side of patients' radicular pain (P < 0.001). Conclusions: Although rare in the healthy volunteers, most of the patients with lumbosacral radiculopathy had gluteal trigger point, located at the painful side. Further studies are required to test the hypothesis that specific gluteal trigger point therapy could be beneficial in these patients. Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved

Optimal self-scheduling of a real energy hub considering local DG units and demand response under uncertainties

In this paper, a cost-based mathematical optimization is used to evaluate the optimal amount of imported power from the public main grid to a private microgrid, that is the LAMBDA lab Microgrid testbed placed at Sapienza University of Rome. In this regard, this study considers five tests based on using different sources, including a photovoltaic array, an emergency generator set, a fuel cell and the main grid, for load satisfaction. The LAMBDA lab can be considered as a multi-source multi-output energy hub with three optional sources and both electrical and heat demands in output. This paper considers photovoltaic production and load demand as indeterministic parameters and evaluates the problem under uncertainties. As a result, a stochastic programming model is defined, and a powerful optimization function is used to reach the optimal power received from the main grid. In addition, information gap decision theory (IGDT) is used to model the robustness of the problem against uncertainties associated with renewable generation unit (Photovoltaic system) and electricity loads applied on a real case for the first time. In the result section, the contribution of each source in electrical and heat load demands is presented in addition to the cost of each test by evaluating the effect of DR of 15%. Finally, a comparison between the stochastic programming method and IGDT has been accomplished

Optimal Self-scheduling of a real Energy Hub considering local DG units and Demand Response under Uncertainties

In this paper, a cost-based mathematical optimization is used to evaluate the optimal amount of imported power from the public main grid to a private microgrid, that is the LAMBDA lab Microgrid testbed placed at Sapienza University of Rome. In this regard, this study considers five tests based on using different sources, including a photovoltaic array, an emergency generator set, a fuel cell and the main grid, for load satisfaction. The LAMBDA lab can be considered as a multi-source multi-output energy hub with three optional sources and both electrical and heat demands in output. This paper considers photovoltaic production and load demand as indeterministic parameters and evaluates the problem under uncertainties. As a result, a stochastic programming model is defined, and a powerful optimization function is used to reach the optimal power received from the main grid. In addition, information gap decision theory (IGDT) is used to model the robustness of the problem against uncertainties associated with renewable generation unit (Photovoltaic system) and electricity loads applied on a real case for the first time. In the result section, the contribution of each source in electrical and heat load demands is presented in addition to the cost of each test by evaluating the effect of DR of 15%. Finally, a comparison between the stochastic programming method and IGDT has been accomplished

The diagnostic accuracy of gluteal trigger points to differentiate radicular from nonradicular low back pain

Objectives: Low back pain (LBP) is highly prevalent and costly to the society. Previous studies have shown an association between radicular LBP and trigger points (TrPs) in the superior-lateral quadrant of the gluteal area (GTrP). The objective of current study was to evaluate the diagnostic value of GTrP to predict nerve root involvement among patients with LBP. Materials and Methods: In a prospective, diagnostic accuracy study 325 consecutive patients with LBP were recruited. At first step, patients were evaluated for the presence or absence of the GTrP. A different investigator, blinded to the GTrP findings, then performed history taking and physical examination. Subsequently, all patients underwent a lumbar spine magnetic resonance imaging and, when indicated, electrodiagnostic tests. On the basis of the clinical and ancillary tests findings, a multidisciplinary panel of experts (the "reference standard"), blinded to the GTrP evaluation, allocated patients to radicular versus nonradicular LBP groups. The agreement between the GTrP findings, as a diagnostic test and the reference standard allocation was evaluated in a 2 by 2 contingency table. Results: The specificity of the GTrP test was 91.4 and its sensitivity was 74.1. The area under the receiver operating characteristic curve was 0.827 (0.781 to 0.874). Positive likelihood ratio was 8.62 and negative likelihood ratio was 0.28. Positive and negative predictive values were 91.9 and 72.7, respectively. Discussion: As a clinical finding, TrPs in superior-lateral quadrant of gluteal area are highly specific indicators for radicular LBP. Incorporating these TrPs evaluation in routine physical examination of patients with LBP could decrease the need for more costly, time-consuming, and invasive diagnostic tests. © 2015 Wolters Kluwer Health, Inc