Economic dispatch strategy for virtual power plants considering privacy protection

doi:10.3969/j.issn.2097-0706.2025.01.010

Abstract

Abstract:

To address the issue that existing distributed economic dispatch algorithms for virtual power plants focus solely on convergence and optimality while neglecting privacy protection，a privacy-protecting strategy that adds zero-sum noise to the edges of discrete systems was proposed. This strategy concealed the original transmitted signal by injecting a set of zero-sum disturbance signals into the communication channel. In the first iteration，each agent generated a pre-designed set of disturbance signals and added them to the network's communication links. Starting from the second iteration，all agents simply followed the traditional economic dispatch algorithm. Compared to existing economic dispatch algorithms，this strategy achieved precise consensus convergence without revealing the true values of the original transmitted information and did not require additional communication bandwidth. From the perspective of privacy protection，the algorithm prevented internal honest-but-curious nodes and external eavesdroppers from stealing private information. Furthermore，compared to existing research，it relaxed the topological constraints for privacy protection against internal honest-but-curious nodes. Finally，the effectiveness of the proposed privacy-preserving mechanism was validated through simulations.

Key words: virtual power plant, zero-sum disturbance, multi-agent systems, distributed economic dispatch, privacy protection

CLC Number:

TK31：TM73

HU Jie, ZHAN Qiaorong, TIAN Deshuo, LI Wenwei. Economic dispatch strategy for virtual power plants considering privacy protection[J]. Integrated Intelligent Energy, 2025, 47(1): 79-87.

Figures/Tables 7

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Table 1

Node-related parameters

节点	DG1	DG2	DG3	DG4	DG5	DG6
a_i	0.001 42	0.001 94	0.004 82	0.001 58	0.001 63	0.003 75
b_i	7.20	7.85	7.97	7.35	7.77	7.58
c_i	510	310	310	450	375	165
$P i m i n$ /kW	40	40	50	50	45	45
$P i m a x$ /kW	200	180	150	250	300	200

Table 1

Fig.4

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