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In this paper, the interaction between the energy storage (ES) power distribution and system efficiency enhancement is researched based on the energy stored quasi-Z-source inverter. The corresponding current counteraction, stress reduction, power loss profile, and efficiency enhancement around the embedded energy storage units are studied in details. Firstly, the current counteraction effect on the device current is presented with the embedded ES source. The corresponding reduction in the device current stress is revealed. Then, the detailed device power loss expressions with current redistribution in the impedance network are explored mathematically. A quasi-inverted-trapezoidal power loss profile is found with the embedded source power distribution. To further increase the overall system efficiency, an optimal energy efficiency tracking strategy is proposed for the ES-qZSI (energy-stored quasi-Z-source inverter) based on the power distribution control. Both the simulation and the experiment verified that the power loss is reduced by over 40% through the proposed efficiency enhancement method. The device current and loss analysis for the embedding of energy storage can also be extended to the operating range optimization in other ES systems. [ABSTRACT FROM AUTHOR]

The rapid incorporation of wind power resources in electrical power networks has significantly increased the volatility of transmission systems due to the inherent uncertainty associated with wind power. This paper addresses this issue by proposing a transmission network expansion planning (TEP) model that integrates wind power resources, and that seeks to minimize the sum of investment costs and operation costs while accounting for the costs associated with the pollution emissions of generator infrastructure. Auxiliary relaxation variables are introduced to transform the established model into a mixed integer linear programming problem. Furthermore, the novel concept of extreme wind power scenarios is defined, theoretically justified, and then employed to establish a two-stage robust TEP method. The decision-making variables of prospective transmission lines are determined in the first stage, so as to ensure that the operating variables in the second stage can adapt to wind power fluctuations. A Benders’ decomposition algorithm is developed to solve the proposed two-stage model. Finally, extensive numerical studies are conducted with Garver’s 6-bus system, a modified IEEE RTS79 system and IEEE 118-bus system, and the computational results demonstrate the effectiveness and practicability of the proposed method. [ABSTRACT FROM AUTHOR]