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With the continuous development of urbanization and industrialization in the world, concrete is widely used in various engineering constructions as an engineering material. However, the consequent problem of durability of concrete structures is also becoming increasingly prominent. As an important additional measure, a protective coating can effectively improve the durability of concrete performance. Moreover, the uniformity of the concrete surface coating will directly affect its protective effect. Therefore, we propose a nondestructive inspection and evaluation method of coating uniformity based on infrared imaging and cluster analysis for concrete surface coating uniformity detection and evaluation. Based on the obtained infrared images, a series of processing and analysis of the images were carried out using MATLAB software to obtain the characteristics of the infrared images of the concrete surface. Finally, by extracting the temperature distribution data of the pixel points on the concrete surface, an evaluation method of concrete surface coating uniformity based on a combination of cluster analysis and hierarchical analysis was established. The evaluation results show that the determination results obtained by this method are consistent with the actual situation. This study has a positive contribution to the testing of concrete surface coating uniformity and its evaluation.

In view of the influence of the randomness, volatility and anti-peak-regulation characteristics of large-scale grid-connected wind power output on the grid’s peak-regulation and dispatching, the technical means of joint operation of concentrated Solar power system with thermal storage and wind power is adopted. The complementarity of solar-thermal and wind power output and the dispatchability of thermal storage are used to suppress the fluctuation of wind power output, reduce the peak-valley difference of power grid load, reduce the cost of thermal power peak shaving, and reduce wind power abandonment. Considering that the uncertainties of wind power and light power bring about the increase of dispatch operation risk, the conditional value-at-risk (CVaR) is used to measure the risk loss caused by uncertainty factors to dispatch operation. Aiming at the lowest total dispatch cost and risk cost, the economic dispatch strategy of solar thermal- wind power system considering CVaR is studied. Finally, the feasibility and rationality of the dispatch strategy and the model are verified by a simulation example.

In this paper, the uncertainty of diesel generator (hereinafter referred to as DG) output and load demand is studied by multi scenario analysis. Firstly, this paper studies the timing characteristics of DG power generation and load demand, and describes the annual and daily distribution of photovoltaic power generation, wind power generation and load demand. Then it introduces the method of multi scene analysis, describes the process of dealing with the uncertainty in multi scene in detail, and generates enough scenes through the density function of classification probability to get the probability of each scene. Finally, H-K compound clustering algorithm is used to solve the above problems. The scale scene is compressed to get a typical “planning scene”.

In the intelligent distribution network environment, the demand side resources (DSR) are the electric vehicle, energy storage, controllable load and other resources located in different locations, showing the characteristics of small single capacity and decentralized layout. How to build a multi time scale integrated scheduling framework of demand side resources and renewable energy, to schedule the distributed demand side resources in an orderly manner, and to realize the efficient integration of demand side resources and renewable energy, are the key problems of demand side resources participating in grid scheduling. Based on this, this paper proposes a multi time scale integrated scheduling method based on hierarchical scheduling for DSR and renewable energy in intelligent distribution network, and uses the modified cuckoo search algorithm (MCS) to solve the problem. The effectiveness of the proposed model and algorithm is verified by the integrated scheduling of electric vehicles and renewable energy in intelligent distribution network.