Distributed Generation Control Using Ripple Signaling and a Multiprotocol Communication Embedded Device

Remotely performing real-time distributed generation control and a demand response is a basic aspect of the grid ancillary services provided by grid operators, both the transmission grid operators (TSOs) and distribution grid operators (DNOs), in order to ensure that voltage, frequency and power loads of the grid remain within safe limits. The stochastic production of electrical power to the grid from the distributed generators (DGs) from renewable energy sources (RES) in conjunction with the newly appeared stochastic demand consumers (i.e., electric vehicles) hardens the efforts of the DNOs to keep the grid’s operation within safe limits and prevent cascading blackouts while staying in compliance with the SAIDI and SAIFI indices during repair and maintenance operations. Also taking into consideration the aging of the existing grid infrastructure, and making it more prone to failure year by year, it is yet of great significance for the DNOs to have access to real-time feedback from the grid’s infrastructure—which is fast, has low-cost upgrade interventions, is easily deployed on the field and has a fast response potential—in order to be able to perform real-time grid management (RTGM). In this article, we present the development and deployment of a control system for DG units, with the potential to be installed easily to TSO’s and DNO’s substations, RES plants and consumers (i.e., charging stations of electric vehicles). This system supports a hybrid control mechanism, either via ripple signaling or through a network, with the latter providing real-time communication capabilities. The system can be easily installed on the electric components of the grid and can act as a gateway between the different vendors communication protocols of the installed electrical equipment. More specifically, a commercially available, low-cost board (Raspberry Pi) and a ripple control receiver are installed at the substation of a PV plant. The board communicates in real-time with a remote server (decision center) via a 5G modem and with the PV plants inverters via the Modbus protocol, which acquires energy production data and controls the output power of each inverter, while one of its digital inputs can be triggered by the ripple control receiver. The ripple control receiver receives on-demand signals with the HEDNO, triggering the digital input on the board. When the input is triggered, the board performs a predefined control command (i.e., lower the inverter’s power output to 50%). The board can also receive control commands directly from the remote server. The remote server receives real-time feedback of the acquired inverter data, the control signals from the ripple control receiver and the state and outcome of each performed control command

The role of maternal gut hormones in normal pregnancy: fasting plasma active glucagon-like peptide 1 level is a negative predictor of fetal abdomen circumference and maternal weight change

Objective: Maternal weight in pregnancy contributes to a glycemic environment that affects fetal growth. Gut peptides (glucagon-like peptide 1 (GLP1), glucose-dependent insulinotropic peptide (GIP), ghrelin, and peptide YY (PYY)) have been related to insulin sensitivity and secretion, weight control, and adipose tissue metabolism. This study aimed at examining the associations of gut hormones during pregnancy with maternal glucose homeostasis, maternal weight, and fetal growth. Methods: A total of 55 pregnant nonobese, nondiabetic Caucasian women were examined during the three trimesters of pregnancy, and anthropometric measurements, evaluation of fasting maternal plasma GLP1 (active), ghrelin (active), total PYY, total GIP, and a 75-g oral glucose tolerance test were done in them. Homeostasis model assessment (HOMA-R), insulin sensitivity index (ISI), and indices of insulin secretion were calculated. Fetal growth was estimated by ultrasound. Results: Fasting GLP1 increased significantly from the second to the third trimester (P < 0.05). Fasting GLP1 correlated positively with high-density lipoprotein cholesterol (r=0.52, P=0.04). At the second trimester, fasting GLP1 levels correlated negatively with fetal abdomen circumference (r=-0.55, P=0.034), birth weight (r=-0.50, P=0.040), HOMA-R (r=-0.65, P=0.001), insulin secretion, and triglycerides. At the first trimester, fasting ghrelin levels correlated negatively with HOMA-R and insulin secretion, and positively with ISI. In backward multiple regression analysis, the first trimester GLP1 levels were the best negative predictors of the second trimester fetal abdomen circumference (beta=-0.96, P=0.009). In longitudinal regression model, maternal fat and HOMA-R were the positive predictors of maternal weight change during pregnancy, and fasting GLP1 levels were the negative predictors of maternal weight change during pregnancy. Conclusions: During pregnancy, maternal GLP1 might be involved in mechanisms that compensate for the pregnancy-related increase in glycemia and insulin resistance, suggesting a role of this peptide in maternal metabolism and weight and fetal growth

The role of maternal gut hormones in normal pregnancy : fasting plasma active glucagon-like peptide 1 level is a negative predictor of fetal abdomen circumference and maternal weight change

Objective Maternal weight in pregnancy contributes to a glycemic environment that affects fetal growth. Gut peptides (glucagon-like peptide 1 (GLP1), glucose-dependent insulinotropic peptide (GIP), ghrelin, and peptide YY (PYY)) have been related to insulin sensitivity and secretion, weight control, and adipose tissue metabolism. This study aimed at examining the associations of gut hormones during pregnancy with maternal glucose homeostasis, maternal weight, and fetal growth. Methods A total of 55 pregnant nonobese, nondiabetic Caucasian women were examined during the three trimesters of pregnancy, and anthropometric measurements, evaluation of fasting maternal plasma GLP1 (active), ghrelin (active), total PYY, total GIP, and a 75-g oral glucose tolerance test were done in them. Homeostasis model assessment (HOMA-R), insulin sensitivity index (ISI), and indices of insulin secretion were calculated. Fetal growth was estimated by ultrasound. Results Fasting GLP1 increased significantly from the second to the third trimester (P<0.05). Fasting GLP1 correlated positively with high-density lipoprotein cholesterol (r=0.52, P=0.04). At the second trimester, fasting GLP1 levels correlated negatively with fetal abdomen circumference (r=−0.55, P=0.034), birth weight (r=−0.50, P=0.040), HOMA-R (r=−0.65, P=0.001), insulin secretion, and triglycerides. At the first trimester, fasting ghrelin levels correlated negatively with HOMA-R and insulin secretion, and positively with ISI. In backward multiple regression analysis, the first trimester GLP1 levels were the best negative predictors of the second trimester fetal abdomen circumference (β=−0.96, P=0.009). In longitudinal regression model, maternal fat and HOMA-R were the positive predictors of maternal weight change during pregnancy, and fasting GLP1 levels were the negative predictors of maternal weight change during pregnancy. Conclusions During pregnancy, maternal GLP1 might be involved in mechanisms that compensate for the pregnancy-related increase in glycemia and insulin resistance, suggesting a role of this peptide in maternal metabolism and weight and fetal growth