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It has been generally accepted that calcium intake prevents bone loss, and frequent fracture resulted from osteoporosis. However, it is still elusive as to how effective sole calcium intake is in preventing or attenuating the severity of osteoporosis. Here, we demonstrate the effects of eggshell-casein phosphopeptide (ES-CPP), and compared these effects those of calcium supplement, for restoring ovariectomy-mediated bone loss. CPP, synthesized from the hydrolysis of casein (0.5%) using trypsin, was added to the grinded ES and was then administered to the ovariectomized (OVX) rat at 100 mg/kg for 4 weeks. Urine and feces from each group were collected each day, and were used to calculate the apparent calcium absorption rate in a day. After 4 weeks incubation, blood and femoral bones were isolated for the analysis of parameters representing osteoporosis. The apparent calcium absorption rate was significantly increased in the ES-CPP treated groups, in comparison to both the OVX and the commercial calcium supplement (CCS) treated group. Notably, treatment with ES-CPP markedly enhanced the calcium content in femoral bone and the relative weight of femoral bone to body weight, though calcium content in serum was barely changed by treatment with ES-CPP. Parameters of osteoporosis, such as osteocalcin in serum and bone mineral density, were rescued by treatment with ES-CPP, compared to treatment with commercial calcium supplement. This finding strongly suggests the possible use of ES-CPP in preventing or attenuating the severity of postmenopausal osteoporosis.

As renewable penetration increases in microgrids (MGs), the use of battery energy storage systems (BESSs) has become indispensable for optimal MG operation. Although BESSs are advantageous for economic and stable MG operation, their life degradation should be considered for maximizing cost savings. This paper proposes an optimal BESS scheduling for MGs to solve the stochastic unit commitment problem, considering the uncertainties in renewables and load. Through the proposed BESS scheduling, the life degradation of BESSs is minimized, and MG operation becomes economically feasible. To address the aforementioned uncertainties, a scenario-based method was applied using Monte Carlo simulation and the K-means clustering algorithm for scenario generation and reduction, respectively. By implementing the rainflow-counting algorithm, the BESS charge/discharge state profile was obtained. To formulate the cycle aging stress function and examine the life cycle cost (LCC) of a BESS more realistically, the nonlinear cycle aging stress function was partially linearized. Benders decomposition was adopted for minimizing the BESS cycle aging, total operating cost, and LCC. To this end, the general problem was divided into a master problem and subproblems to consider uncertainties and optimize the BESS charging/discharging scheduling problem via parallel processing. To demonstrate the effectiveness and benefits of the proposed BESS optimal scheduling in MG operation, different case studies were analyzed. The simulation results confirmed the superiority and improved performance of the proposed scheduling.

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