Probabilistic adaptive model predictive power pinch analysis (PoPA) energy management approach to uncertainty

This paper proposes a probabilistic power pinch analysis (PoPA) approach based on Monte–Carlo simulation (MCS) for energy management of hybrid energy systems uncertainty. The systems power grand composite curve is formulated with the chance constraint method to consider load stochasticity. In a predictive control horizon, the power grand composite curve is shaped based on the pinch analysis approach. The robust energy management strategy effected in a control horizon is inferred from the likelihood of a bounded predicted power grand composite curve, violating the pinch. Furthermore, the response of the system using the energy management strategies (EMS) of the proposed method is evaluated against the day-ahead (DA) and adaptive power pinch strategy

Star Models with Dark Energy

We have constructed star models consisting of four parts: (i) a homogeneous inner core with anisotropic pressure (ii) an infinitesimal thin shell separating the core and the envelope; (iii) an envelope of inhomogeneous density and isotropic pressure; (iv) an infinitesimal thin shell matching the envelope boundary and the exterior Schwarzschild spacetime. We have analyzed all the energy conditions for the core, envelope and the two thin shells. We have found that, in order to have static solutions, at least one of the regions must be constituted by dark energy. The results show that there is no physical reason to have a superior limit for the mass of these objects but for the ratio of mass and radius.Comment: 20 pages, 1 figure, references and some comments added, typos corrected, in press GR