With the fact of harmfulness, X-ray radiation dose reduction received more and more attention in CT research field nowadays. As Compressed Sensing theory applied into Computed Tomography reconstruction algorithms make it possible to reconstruct high-quality CT images with the requirement of low radiation dose. One of research hot point in CS-based CT reconstruction algorithms is Total Variation, using the information of x-coordinate and y-coordinate gradients to reconstruct CT images, which implies that it will reconstruct better CT images by using gradients of more directions. In this paper, a CT reconstruction algorithm based on Multi-directional Total Variation (MdTV) was proposed, by using the information of x-coordinate, y-coordinate and diagonal gradient together to reconstruct CT images, which theoretically will reconstruct images with higher quality. Experimental results shows that, MdTV based reconstruction algorithm reconstruct better images than TV based algorithm, which is more helpful to reduce X-ray radiation dose as much as possible.

As the low-carbon economy continues to expand, wind power, as one form of clean energy, promotes the low-carbon power development process. In this paper, a multi-objective environmental economic dispatch (EED) model is proposed considering multiple uncertainties of the system. Carbon trading costs and green certificate trading costs are introduced into the economic costs. Meanwhile, the objective function of pollutant emissions is taken into account in the model, which can further promote the reduction of pollutant emissions in the system scheduling. The output of wind turbines is uncertain and volatile, so it brings new challenges to the power system EED once the large-scale wind power accesses the power grid. For the multiple uncertainties of the system, fuzzy chance-constrained programming is introduced, and the output of the wind turbines and the load are regarded as fuzzy variables. We use the clear equivalence forms to clarify the fuzzy chance constraints. The improved multi-objective standard particle swarm optimization (SPSO) algorithm is used to solve the optimization problem effectively. The feasibility and effectiveness of the proposed model and algorithm are verified by an example of a 10-unit system with two wind farms.

As a representative form of new energy generation, wind power has effectively alleviated environmental pollution and energy shortages. This paper constructs a green economic indicator to measure the degree of coordinated development of environmental and social benefits. To increase the amount of wind power consumption, an economic dispatch model based on the coordinated operation of cogeneration units and electric boilers was established; we also introduced the green certificate transaction cost, which effectively meets the strategic needs of China’s energy low-carbon transformation top-level system design. Wind power output has instability and volatility, so it puts higher requirements on the stable operation of thermal power units. To solve the stability problem, this paper introduces the output index of the thermal power unit and rationally plans the unit combination strategy, as well as introducing the concept of chance-constrained programming due to the uncertainty of load and wind power in the model. Uncertainty factors are transformed into load forecasting errors and wind power prediction errors for processing. Based on the normal distribution theory, the uncertainty model is transformed into a certain equivalence class model, and the improved disturbance mutated particle swarm optimization algorithm is used to solve the problem. Finally, the validity and feasibility of the proposed model are verified based on the IEEE30 node system.

The maximum flow model proposed analyzes the power system from the perspective of "flow", which shows certain superiority on some issues. This paper studies the renewable energy consumption through the network maximum flow model. The traditional node voltage equation as well as the branch current equation are used to establish that flow model with the branch current used as a state variable. The linear relationship between the branch current and the node voltage plays a key role in simplifying the model. The model is analyzed through the IEEE-33 system and the IEEE-30 system and the validity and convergence of it are verified.