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| Distributed Non-Convex Optimization Method for System-Wide Voltage of Large-Scale Renewable Energy Power Plants |
| Li Haixiao1,2, Cheng Qiang1, Zhou Lin3, Jiang Jincheng4, Bao Shiyuan1,2 |
1. School of Electrical and Electronic Engineering Chongqing University of Technology Chongqing 400054 China;
2. Chongqing Engineering Technology Research Center of Energy Internet Chongqing University of Technology Chongqing 400054 China;
3. School of Electrical Engineering Chongqing University Chongqing 400044 China;
4. School of Automation Chongqing University of Posts and Telecommunications Chongqing 400065 China |
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Abstract Large renewable energy power plants, characterized by “large-scale topology and integration into weak grids”, are susceptible to operational risks such as excessive voltage differentials and overvoltage. These challenges arise due to the high impedance of both internal and external transmission lines, posing significant threats to the plant’s safe and stable operation. This paper proposes a distributed nonconvex optimization framework for voltage regulation in large-scale renewable energy power plants, ensuring accurate voltage computation and mitigating communication overhead. Specifically, a nonconvex voltage optimization model is formulated based on nonlinear standard power flow constraints, and the augmented lagrangian-based alternating direction inexact newton (ALADIN) algorithm is employed to solve the problem in a distributed manner. This approach enables the optimal dispatch of reactive power from renewable energy units, effectively regulating the system-wide voltage profile, thereby enhancing the overall operational security and stability of the power plant.
Numerical experiments were conducted on a representative large-scale renewable energy power plant system. The necessity of employing a nonconvex voltage optimization model was analyzed. The numerical results demonstrate that the linearized voltage optimization model introduces significant errors in power flow calculations. The convergence performance of the ALADIN distributed optimization algorithm was validated. Compared to the traditional alternating direction method of multipliers (ADMM), ALADIN exhibits convergence behavior that is largely insensitive to the penalty parameter ρ. It achieves convergence within approximately 10 iterations, which is significantly fewer than the number of iterations required by ADMM. The optimality of the distributed optimization solution obtained via ALADIN was verified. The reactive power compensation results for each node in the collection lines closely matched those from centralized optimization, with a maximum relative error of less than0.3%. Moreover, the optimized voltage profile of the large-scale renewable energy power plant remained effectively constrained within the acceptable range of 0.95~1.05(pu). The flexibility of the ALADIN algorithm in handling communication delays in practical network environments was demonstrated. The algorithm supports both synchronous and asynchronous update strategies.
The following conclusions can be drawn. (1) Linearized approximation methods, such as LinDistFlow, introduce substantial errors in voltage calculations. The nonconvex distributed voltage optimization model based on nonlinear standard power flow constraints provides more accurate voltage calculations, making it suitable for large-scale layouts and long-distance power transmission scenarios. (2) The ALADIN distributed optimization algorithm is proposed. ALADIN converges quickly, producing results nearly identical to those of centralized optimization, thereby significantly improving optimization performance. (3) The reactive power output derived from ALADIN effectively optimizes node voltages within a safe range throughout the extensive enewable energy power plant system. (4) For the ALADIN algorithm, the choice between synchronous and asynchronous updates to handle information delays can be flexibly determined based on the actual degree of communication delay.
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Received: 04 November 2024
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2025, Vol. 40 
