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

Abstract

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 onemore » 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.« less

Authors:

Feng, Xiaochun ^[1]; Chen, Yang  ^[2];

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

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+ Show Author Affiliations

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

Publication Date:

Tue Feb 22 00:00:00 EST 2022

Research Org.:

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:

USDOE

OSTI Identifier:

1846529

Grant/Contract Number:  

AC05-00OR22725

Resource Type:

Accepted Manuscript

Journal Name:

Journal of Energy Resources Technology

Additional Journal Information:

Journal Volume: 144; Journal Issue: 7; Journal ID: ISSN 0195-0738

Publisher:

ASME

Country of Publication:

United States

Language:

English

Subject:

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; particle swarm algorithm; cubic topology; bilevel energy transaction; local energy market