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Facing stochastic variations of the loads due to an increasing penetration of renewable energy generation, online decision making under uncertainty in modern power systems is capturing power researchers' attention in recent years. To address this issue while achieving a good balance between system security and economic objectives, we propose a surrogate-enhanced scheme under a joint chance-constrained (JCC) optimal power-flow (OPF) framework. Starting from a stochastic-sampling procedure, we first utilize the copula theory to simulate the dependence among multivariate uncertain inputs. Then, to reduce the prohibitive computational time required in the traditional Monte-Carlo (MC) method, we propose to use a polynomial-chaos-based surrogate that allows us to efficiently evaluate the power-system model at non-Gaussian distributed sampled values with a negligible computing cost. Learning from the MC simulated samples, we further proposed a hybrid adaptive approach to overcome the conservativeness of the JCC-OPF by utilizing correlation of the system states, which is ignored in the traditional Boole's inequality. The simulations conducted on the modified Illinois test system demonstrate the excellent performance of the proposed method. 

Abstract. Secondary organic aerosol (SOA) constitutes a largefraction of atmospheric aerosol. To assess its impacts on climate and airpollution, knowledge of the number of phases in internal mixtures ofdifferent SOA types is required. Atmospheric models often assume thatdifferent SOA types form a single phase when mixed. Here, we present visualobservations of the number of phases formed after mixing differentanthropogenic and biogenic SOA types. Mixing SOA types generated inenvironmental chambers with oxygen-to-carbon (O/C) ratios between 0.34 and 1.05, we found 6 out of 15 mixtures of two SOA types to result in two phase particles. We demonstrate that the number of phases depends on thedifference in the average O/C ratio between the two SOA types (Δ(O/C)). Using a threshold Δ(O/C) of 0.47, we can predict the phasebehavior of over 90 % of our mixtures, with one- and two-phase particlespredicted for Δ(O/C)<0.47 and Δ(O/C)≥0.47,respectively. This threshold ΔO/C value provides a simple parameterto predict whether mixtures of fresh and aged SOA form one- or two-phase particles in the atmosphere. In addition, we show that phase-separated SOAparticles form when mixtures of volatile organic compounds emitted from realtrees are oxidized.