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With the advancement of supply-side reforms in the energy and power fields, a comprehensive energy system that integrates various energy sources such as electricity, heat, and natural gas has become the main development trend. Based on this, this paper proposes a combined heat and power(CHP) microgrid model with renewable energy. Based on the improved particle swarm algorithm, the optimal scheduling problem of the microgrid model is calculated, and a feasible optimal scheduling strategy considering both economy and low carbon is proposed. Finally, the economy and correctness of the optimal scheduling strategy proposed in this paper are verified by simulation.

To decrease wind curtailment rate and increase wind power accommodation, power purchase area should increase wind power purchase. However, the current electricity price of wind power is higher than that of thermal power, which makes wind power accommodation difficult to quantify. It is not practical to optimize these two objectives of the wind power accommodation and power purchase cost. Based on this contradiction, this paper describes this contradiction by constructing a multi-objective optimization model (MOOM) that considers the above two objectives. Firstly, the model is resolved by hybrid particle swarm optimization and gravity search algorithm (HPSO-GSA) to obtain Pareto optimal solution set. Then, according to fuzzy satisfaction function, Pareto optimal solution is selected from Pareto optimal frontier. Finally, the typical daily load and wind farm output value in spring of a certain region are taken as examples for simulation verification. It is verified that the proposed method can indeed provide a scientific power purchase scheme for regional power purchase.

A novel metal–organic cage 1·8PF6− was precisely self-assembled using polynitrogen pyrazine-triazine ligand as linker L1 and bpyPd(NO3)2 as coordination corner (where 1·8PF6− = [(bpyPd)4L12]8+·8PF6−; L1 = 4, 6-bis((pyrazin-2-ylmethyl)amino)-1,3,5-triazin-2-ol); bpy = 2,2′-bipyridine) in aqueous solution. The capsule-like coordination cage 1·8PF6− was fully characterized by single-crystal X-ray diffraction analysis, 1H and 13C-NMR and ESI–MS analysis. In the crystal structure, cage 1 closely stacked into a stable 3D framework structure with a regular channel. By employment of such crystalline adsorbent material, permanganate anion (MnO4−) can be rapidly adsorbed into cationic channel and exchanged with hexafluorophosphate anion from water, in which the crystallinity of cage 1 remained unaffected before and after adsorption. Moreover, the anion adsorption and exchanging behavior was revealed by Fourier transform infrared spectra (FTIR), powder X-ray diffraction analysis (PXRD), scanning electron microscopy (SEM), electron adsorption and fluorescence spectroscopy.

Adopting a traditional culture method and PCR–DGGE, this paper discusses the biofilm development on a polyethylene pipeline in model water distribution systems. When chlorine is absent, different hydraulic conditions had no effect on biofilm development. Biofilm HPCs developed up to a stable level in 7 days and maintained at 105 CFU/cm2. The diversity of bacteria increased as time went on, and some kinds of bacteria changed greatly: Sphingomonas sp. tended to excrete extracellular polymers and Mycobacterium sp. had a highly hydrophobic surface, gradually taking the place of some other kinds. When chlorine is present, biofilm HPCs under shear stress 0.95 N/m2 was about a quarter of that of 0.18 N/m2. The diversity of the bacteria decreased relatively, and Acinetobacter baumannii, with a good drug-fast ability, became the dominant bacterium.

The anaerobic biodegradability of 23 nitrogenous compounds, including nitrogenous heterocyclic compounds and aliphatic amines, was tested and assessed in integration. These nitrogenous compounds were classified into readily, partially, and poorly biodegradable compounds after calculation of their integrated assessment indices (IAIs), Rules for anaerobic biodegradation of these compounds were also drawn. Stepwise regression and backpropagation artificial neural network (BP-ANN) methods were applied to establish quantitative structure–biodegradability relationships (QSBRs) based on the assessment results. In QSBR models, three molecular structure descriptors—second-order molecular connectivity index ( 2 χ v 3 χ p v ), and energy of the highest occupied molecular orbital (EHOMO)—were included. After analysis of the sensitivity of variables in QSBR models, it was found that the key molecular structure descriptor affecting anaerobic biodegradability of nitrogenous compounds is EHOMO, which is directly proportional to the anaerobic biodegradability of nitrogenous compounds.

In this study, anaerobic biodegradability of 47 kinds of aliphatic compounds was tested and assessed in integrate. These aliphatic compounds were classified into readily, partially and poorly biodegradable compounds after their integrated assessment indices (IAI) were calculated. Some laws of anaerobic biodegradation of aliphatic compounds were drawn. Stepwise regression and back propagation artificial neural network (BP-ANN) methods were applied to establish quantitative structure biodegradability relationship (QSBR) based on the assessment results. In QSBR models, six molecular structure descriptors were included. After analyzing the sensitivity of variables in QSBR models, it was found that the key molecular structure descriptors affecting anaerobic biodegradability of aliphatic compounds were total energy (TolE) and molecular diameter (D), which were in direct proportion to the anaerobic biodegradability of aliphatic compounds.