Efficient Distribution Grid Optimal Power Flow with Discrete Control of Legacy Grid Devices

Author(s):  
Alper Savasci ◽  
Adedoyin Inaolaji ◽  
Sumit Paudyal ◽  
Sukumar Kamalasadan
Author(s):  
C. M. WANKHADE ◽  
A. P. VAIDYA

This paper presents an efficient genetic algorithm for solving non-convex optimal power flow (OPF) problems with bus voltage constraints for practical application. In this method, the individual is the binary-coded representation that contains a mixture of continuous and discrete control variables, and crossover and mutation schemes are proposed to deal with continuous/discrete control variables, respectively. The objective of OPF is defined that not only to minimize total generation cost but also to improve the bus voltage profile.. The proposed method is demonstrated for a IEEE 30-bus four generator ystem, and it is compared with conventional method.The experimental results show that the GA OPF method is superior to the conventional.


Author(s):  
Adrian Hauswirth ◽  
Tyler Summers ◽  
Joseph Warrington ◽  
John Lygeros ◽  
Andreas Kettner ◽  
...  

2018 ◽  
Vol 33 (2) ◽  
pp. 1461-1472 ◽  
Author(s):  
Zhifang Yang ◽  
Haiwang Zhong ◽  
Anjan Bose ◽  
Qing Xia ◽  
Chongqing Kang

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3290
Author(s):  
Bharath Varsh Rao ◽  
Mark Stefan ◽  
Roman Schwalbe ◽  
Roman Karl ◽  
Friederich Kupzog ◽  
...  

This paper presents control relationships between the low voltage distribution grid and flexibilities in a peer-to-peer local energy community using a stratified control strategy. With the increase in a diverse set of distributed energy resources and the next generation of loads such as electric storage, vehicles and heat pumps, it is paramount to maintain them optimally to guarantee grid security and supply continuity. Local energy communities are being introduced and gaining traction in recent years to drive the local production, distribution, consumption and trading of energy. The control scheme presented in this paper involves a stratified controller with grid and flexibility layers. The grid controller consists of a three-phase unbalanced optimal power flow using the holomorphic embedding load flow method wrapped around a genetic algorithm and various flexibility controllers, using three-phase unbalanced model predictive control. The control scheme generates active and reactive power set-points at points of common couplings where flexibilities are connected. The grid controller’s optimal power flow can introduce additional grid support functionalities to further increase grid stability. Flexibility controllers are recommended to actively track the obtained set-points from the grid controller, to ensure system-level optimization. Blockchain enables this control scheme by providing appropriate data exchange between the layers. This scheme is applied to a real low voltage rural grid in Austria, and the result analysis is presented.


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