Improved Particle Swarm Algorithm Using Rubik’s Cube Topology for Bilevel Building Energy Transaction

Feng, Xiaochun; Chen, Yang; Zhang, Jian; Cho, Heejin; Shi, Xin

doi:10.1115/1.4053768

Title: Improved Particle Swarm Algorithm Using Rubik’s Cube Topology for Bilevel Building Energy Transaction

Journal Article · 21 February 2022 · Journal of Energy Resources Technology

DOI: https://doi.org/10.1115/1.4053768 · OSTI ID:1846529

Feng, Xiaochun ^[1];

^[2]; Zhang, Jian ^[3]; Cho, Heejin ^[4]; Shi, Xin ^[5]

Northwest A&F University, Yangling (China)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
University of Wisconsin, Green Bay, WI (United States)
Mississippi State Univ., Mississippi State, MS (United States)
Lehigh Univ., Bethlehem, PA (United States)

Following the rapid growth of distributed energy resources (e.g., renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as reducing power loss and stabilizing the main power grid. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. Additionally, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush–Kuhn–Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence-based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubik’s Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubik’s Cube topology-based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology-based PSO and its scalability on larger scale applications.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1846529

Journal Information:: Journal of Energy Resources Technology, Journal Name: Journal of Energy Resources Technology Journal Issue: 7 Vol. 144; ISSN 0195-0738

Publisher:: ASMECopyright Statement

Country of Publication:: United States

Language:: English

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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
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local energy market
particle swarm algorithm

Title: Improved Particle Swarm Algorithm Using Rubik’s Cube Topology for Bilevel Building Energy Transaction

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