<p>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, stabilizing the main power grid, etc. 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 local transaction operator (LTO) is assumed to be at the upper level 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. In addition, 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 LTO 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. On the other hand, to increase the chance of jumping out of local minimum, historical information of evaluated particles (price) is utilized by kernel density estimation to estimate the probability density function for each dimension of particles, which will be used for potential particle resampling in mutation stage. Several groups of experiments are designed to evaluate the performance of proposed Rubik’s Cube topology based particle swarm algorithm (rc-PSO). The results have validated the effectiveness of rc-PSO comparing with global-best version PSO (g-PSO) and Von Neumann topology based PSO (vn-PSO) and its scalability on larger scale applications.</p>

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

Paper Proceedings: https://asmedigitalcollection.asme.org/ES/ES2021/volume/84881

ASME 2021 Energy Sustainability (ES2021)

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