首页> 外文会议>International Conference on Energy Sustainability >RUBIK'S CUBE TOPOLOGY BASED PARTICLE SWARM ALGORITHM FOR BILEVEL BUILDING ENERGY TRANSACTION
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RUBIK'S CUBE TOPOLOGY BASED PARTICLE SWARM ALGORITHM FOR BILEVEL BUILDING ENERGY TRANSACTION

机译:基于Rubik的立方体拓扑基于Bilevel建筑能源交易的粒子群算法

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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 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. 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 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, Rubiks 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 Rubiks 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.
机译:在分布式能源资源(例如可再生能源,电池)的快速增长之后,本地化的点对点能源交易正在接受多种效益的更多关注,例如减少功率损耗,稳定主电网等以促进分布式可再生能源在本地,本地交易价格通常设定为外部能源采购和销售价格范围。因此,建立法制通过当地交易中心进行贸易能量。此本地能源交易在Bilevel优化游戏中进行了建模。有一个自私的上层代理,有权设定内部能源交易价格,其目的是最大化其套利利润。同时,较低级别的建设法制将对这笔交易价格响应,并对电力交易金额作出决定。因此,这款非合作领导者贸易游戏正在寻求能源交易金额和价格均衡解决方案。此外,这里考虑了统一的本地交易价格结构(购买价格等于销售价格)。旨在减少古典karush-kuhn-tucker(kKt)转型和保护每个利益相关者(例如,建筑物)的私人信息的计算负担,基于群体智能的解决方案方法用于上层代理,以产生交易价格并协调缩放操作。一方面,为了减少全球最佳拓扑的过早收敛的机会,在本研究中提出了基于进一步改善二维方形格子模型的研究(即一个局部最佳拓扑 - von Neumann拓扑),提出了Rubiks立方体拓扑。引入多维数据集的旋转操作以动态地改变邻域并增强稍后搜索状态的信息流。几个实验旨在评估所提出的Rubiks立方体拓扑粒子群算法的性能。结果已验证了拓扑和运营商与全球最佳版本PSO和VON Neumann拓扑的PSO比较的有效性及其在较大尺度应用中的可扩展性。

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