Experiment was conducted to evaluate the effect of weaning age on growth performance, feed intake, feed efficiency (FE) and blood metabolites in Nili-Ravi male buffalo (Bubalus bubalis) calves. Twenty-four male buffalo calves were assigned to one of the three treatment groups: continuous milk feeding (CMF), limited milk feeding (LMF) and early weaning (EW), and weaned off milk at 12, 10 and 8 weeks of age, respectively. For the first 3 days after birth, calves in all three treatments were fed colostrum, and were then moved to individual milk feeding at 10% of BW for the next 6 weeks. Thereafter, the provision of milk to the CMF group was gradually tapered to zero through week 12, using week 6 intakes as a base. The LMF calves were fed milk at 7.5%, 5.0%, 3.5%, and 1.5% of BW during weeks 7 to 10, respectively. Lastly, calves in the EW group were fed milk at 5.0% and 2.5% of BW at weeks 7 and 8, respectively. Calf starter (CS) feed was also provided ad libitum from weeks 2 to 12 and individual intakes were recorded on a daily basis. Blood samples were taken from weeks 6 to 12, on a weekly basis; whereas, the BW, heart girth, withers height and hip width were measured at the start of experiment and later on a weekly basis. Weight gain, average daily gain, and body measurements were the same across all three groups. Milk intake was lower (P < 0.05), whereas CS intake was greater (P < 0.05) in the EW calves compared with the other treatment groups. Dry matter intake was greater (P < 0.05) in the EW and LMF calves compared with the CMF calves. The FE was greater (P < 0.05) in the CMF calves compared with the LMF and EW treatment groups. Blood glucose concentration was similar among the treatments; however, blood urea nitrogen was greater (P < 0.05) in the EW calves compared with the CMF and LMF groups. Plasma concentration of non-esterified fatty acids was higher (P < 0.05) in the EW calves compared with the CMF calves. In light of these results, it is evident that buffalo calves can be successfully weaned as early as 8 weeks of age without negatively affecting their growth performance.

This paper presents a novel approach to manage distributed DC microgrids (DCMG) by integrating a time-of-use (ToU) electricity pricing scheme and an internal price rate calculation mechanism. The proposed power-management system is designed to effectively handle uncertainties such as utility grid (UG) availability, fluctuating electricity prices, battery state of charge (SOC) levels, and frequent plug-ins and plug-outs of electric vehicles (EVs). Uncertainties in DCMG systems often lead to inefficiencies, power imbalances, and inexact voltage regulation issues within DCMGs. In addition, to maintain the power balance and constant voltage regulation under various operational states, the proposed scheme also incorporates secondary control into the DCMG power-management system. Unlike the existing approaches that often fail to adapt dynamically to changing conditions, the proposed method is the first approach to consider the concept of internal price rate in designing the DCMG power management. To address this challenge, this approach proposes a more resilient power-management strategy to enhance the efficiency and adaptability of DCMG systems. Extensive simulations and experimental validations demonstrate the practicality and adaptability of the proposed control strategy under diverse test conditions, including operation transitions between grid-connected mode (GCM) and islanded mode (IM), low battery SOC condition, operation transition from the current control mode (CCM) to distributed secondary control mode (DSCM), and EV plug-in scenarios. The test results confirm that the proposed method enhances the reliability, efficiency, and economic viability of DCMG systems, making it a promising solution for future smart grid and renewable energy integrations.

Continuous power management for a decentralized DC microgrid (DCMG) is proposed in this study to achieve power balance and voltage regulation even under system uncertainty and voltage sensor failure. The DCMG system achieves continuous power management through only the primary controller to reduce the computational burden of each power agent. To enhance the reliability and resilience of the DCMG system under DC bus voltage (DCV) sensor failure, a DCV sensor fault detection algorithm is suggested. In this algorithm, DCV sensor failure is detected by comparing the measured DCV with the estimated DCV. If power agents identify the failure of the DCV sensor, it changes the operation properly according to the proposed control mode decision algorithm to guarantee the stability of the DCMG system. When uncertain conditions like sudden grid disconnection, DCV sensor failure, electricity price change, power variation in distributed generations, and critical battery status occur, the DCMG system is changed to transitional operation modes. These transitional operation modes are employed to transmit the power agent information to other agents without digital communication links (DCLs) and to accomplish power sharing even under such uncertain conditions. In the transitional operation modes of the DCMG system, the DCV levels are temporarily shifted to an appropriate level, enabling each power agent to detect the uncertainty conditions, and subsequently to determine its operation modes based on the DCV levels. The reliability and effectiveness of the proposed control strategy are confirmed via various simulation and experimental tests under different operating conditions.

To enhance the reliability and flexibility of DC microgrids (DCMGs), this paper presents a decentralized power flow control strategy (PFCS) by using the transition operation modes. The transition operation modes are introduced as an effective communication method among power units, eliminating the use of additional digital communication links (DCLs) for the purpose of ensuring the power balance as well as the voltage regulation even under uncertain conditions. During the transition operation modes, the power unit which transmits the information shifts the DC-link voltage level, and the power unit which receives the information continuously monitors the DC-link voltage with predetermined time. When uncertain conditions occur in a particular power unit, this power unit triggers the transition operation modes to send this information to all power units in the DCMG system. The proposed PFCS can maintain the DC-link voltage at the nominal value for steady-state conditions both in the grid-connected mode and islanded mode. Moreover, the proposed PFCS significantly enhances the overall reliability of the decentralized DCMG system by effectively addressing several uncertainties stemmed from electricity price fluctuations, grid availability, battery state-of-charge (SOC) levels, and wind power variations. The scalability of the DCMG system is also demonstrated by incorporating an electric vehicle (EV) unit as an additional energy storage system (ESS). The EV unit seamlessly cooperates with the existing battery unit, functioning as additional ESS to regulate the DC-link voltage when the battery SOC level is low. Simulation and experimentation results under various conditions demonstrate the effectiveness of the proposed PFCS.

In this paper, a continuous power management for a decentralized DC microgrid (DCMG) is proposed to achieve voltage regulation and power balance even under system uncertainty and voltage sensor failure. The DCMG system achieves a continuous power management through only the primary controller to reduce the computational burden of each power agent. To enhance the reliability and resilience of the DCMG system under voltage sensor failure, a DC bus voltage (DCV) sensor fault detection algorithm is proposed. In this algorithm, the DCV sensor failure is detected by comparing the measured DCV with the estimated DCV. When the power agent identifies the DCV sensor failure, it changes the operation properly according to the proposed control mode decision algorithm to maintain the stability of the DCMG system. When uncertain conditions such as the power variation of the distributed generations, sudden grid disconnection, DCV sensor failure, electricity price change, and critical battery status occur, the DCMG system is changed to transitional operation modes. These transitional operation modes are employed to transmit the power agent information to other agents without digital communication links (DCLs) and to accomplish power sharing even under such uncertain conditions. In the transitional operation modes of the DCMG system, the DCV levels are temporarily shifted to an appropriate level, enabling each power agent to detect the uncertainty conditions, and subsequently to determine its operation modes based on the DCV levels. Simulation and experimental results under different test conditions confirm the reliability and effectiveness of the proposed control scheme.