Two-level Capacity Optimization Strategy for Generations in Multi-energy Gathering Center Considering the Flexibility

Li, Lingfang; Gao, Mengping; Lin, Gao; Li, Wenyun; You, Guangzeng; Zhu, Tao; Wang, Jun

doi:10.1109/ei250167.2020.9347047

Cited by 1 publication

(1 citation statement)

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“…A certain objective of the solution may be optimal, while another objective may be weaker than the other solutions. The decision maker can select one solution or part of the solution from the Pareto optimal solution set as the final solution for the requested multi-objective optimization problem in accordance with the requirements of the actual problem and the convenience of operation [20].…”

Section: Solution Strategy For the Inner-layer Modelmentioning

confidence: 99%

Multiple-Zone Synchronous Voltage Regulation and Loss Reduction Optimization of Distribution Networks Based on a Dual Rotary Phase-Shifting Transformer

Shao,

Yan,

Yang

et al. 2024

Sustainability

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For the problem in which accessing a high proportion of renewable energy results in exceeding the limit in distribution network voltage, the existing regulating method experiences difficulty in considering the two-way voltage regulation and loss reduction optimization function. This study proposes a series-type dual rotary phase-shifting transformer (DRPST) based on the principle of phase volume synthesis. This transformer exhibits bidirectional voltage regulation, high reliability, and low cost. First, the topology, operating principle, and equivalent circuit of DRPST are introduced, and its simplified circuit model is established. On the basis of this model, the causes of voltage exceeding the limits are analyzed and the active distribution network model that contains DRPST is constructed. A real-time rolling two-layer optimization strategy based on DRPST is proposed. The inner layer model is solved using the multi-objective particle swarm optimization algorithm with the objective of minimizing voltage deviation and line loss. The optimal compromise solution of the Pareto solution set of the inner layer model is determined using the fuzzy subordinate degree function method. The outer model is based on the optimal compromise solution of the inner model, and the DRPST output rotor angle is controlled without deviation through double closed-loop proportional–integral regulation. Finally, the correctness and effectiveness of the proposed topology and control method are verified via simulation and experimental analysis.

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Section: Solution Strategy For the Inner-layer Modelmentioning

confidence: 99%