The State Grid has proposed to construct a strong smart grid to solve the resource scarcity, environmental pollution and other social problems, which will certainly drive the development of green energy, such as wind energy, solar energy, tidal energy and biomass energy. The study will build a Green Power System Assessment Model (GPSAM) using multivariate statistical analysis to optimize the energy resources of a region and finally to provide reference for the construction of a new plant or the plant expansion to get the balance of environment benefit, economic benefit and social benefit.

Because of the characteristic of highly controllability and modularization, battery energy storage could be widely applied in the distributed renewable energy generation for improving the reliability of power supply and smoothing the load. The paper introduces the chemical energy storage technology especially the flow battery and designs the model of smart grid with the chemical energy storage devices. Then the paper gives the interface circuit between smart grid and energy storage, and simulates an actual distribution network with chemical energy storage device, the result shows that if the energy storage battery with proper capacity was connected to the distribution network at a proper position, it was effective in reducing the line loss.

Wind power is one of the cleanest and safest of all the renewable commercial methods of generating electricity. However, wind energy is difficult to use due to its stochastic variability. Energy storage can overcome the main drawback, allowing energy production to match energy demand. In this paper a new method is proposed to determine the Energy-storage Capacity in Grid-connected Wind Farm. Based on characteristic function of wind power output in wind farm, the method designs the minimum required storage capacity of the wind farm and realizes the stable output and the scheduling of wind farm. The results of this paper demonstrate the leading role of a well-optimized design for technical and economic viability of such systems.

No abstract