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Electric power industry is a key to achieve the low-carbon social and economic development. Distributed generation (DG) has great potential in the development of low-carbon power grid because of its non-polluting property and large reserves. Therefore, it is of great importance to have a comprehensive investigation on low-carbon impact of DG on power grids. In this paper, regional power grids are focused as they are crucial supporters of regional economic and social activities and the primary undertakers of low-carbon development. Specifically, first, the carbon dioxide emission coefficient and energy consumption of DG are evaluated from the aspect of its life cycle. Then, the wind farm and photovoltaic power station are compared in terms of carbon dioxide emissions and energy consumption, indicated that wind power is superior in reducing the carbon dioxide emissions. Finally, the carbon intensity of provincial power grid is evaluated by grey prediction model with historical data such as electricity consumption, gross domestic product (GDP), carbon dioxide emission coefficient. Taking Jiangxi provincial power grid as the example, the results demonstrate that the proposed prediction method is of high accuracy and the integration of DGs can effectively reduce carbon dioxide emissions and carbon intensity, thus, DG should be widely integrated into provincial power grids. [ABSTRACT FROM AUTHOR]

• The analytical expression of failure rates is derived. • The penalty cost of power shortages can be expressed as an explicit function. • A bi-level coordinated configuration programming model is built. • The bi-level model is transformed to a mixed-integer nonlinear programming problem. Improving system reliability and voltage profiles in distribution networks requires the simultaneous installation of distributed generations and automation devices. This paper builds a bi-level programming model for the coordinated configuration of distributed generations and automation devices. The upper-level problem is to minimize the total investment cost of distributed generations and automation devices and the penalty cost of power shortages, and the lower-level problem is to minimize the voltage deviation during typical operation mode. To explicitly represent the relationship between the penalty cost of power shortages and installation locations of distributed generations and automation devices, an analytical expression of the failure rates of load nodes with respect to installation locations of distributed generations and automation devices is derived. The bi-level model can be transformed to a mixed-integer nonlinear programming problem by applying the Karush–Kuhn–Tucker theorem because the lower-level problem is a quadratically constrained linear programming problem. Case studies on an IEEE 33-bus distribution system and a practical 110-bus distribution system in China are used to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]