基于元胞自动机和有向网络的风火多元发电权交易报价动态模拟

针对目前发电权交易市场未能完全处于信息公开透明的局面,交易个体需要在把控有限的交易信息下开展利于己方的报价决策.本文运用元胞自动机和有向网络建立了各交易个体参与风火多元发电权交易的动态报价模拟模型.首先,个体各历史时段的评估增益和当前时段内邻域个体之间评估的风险增益:其次,分别建立历史报价策略转移矩阵和邻域报价策略转移矩阵,结合二者形成新一轮各交易个体的报价策略;最后,利用重标极差法(R/S)和其参数H对报价模拟结果进行评价.论文对具体算例定量分析各交易元胞报价策略及对风险的敏感度,仿真结果表明.在目前权交易信息不对称的环境下,运用本文所建立的模拟方法可为各交易成员提供一个有效、可行的报价决策.

The bidding dynamic simulation of multivariate generation right trading among wind farms and thermal units based on CA and directed networks

Since the information of the generation right trading market is not completely public, a trading individual need develop his advantageous bidding strategies in terms of limited information. This paper makes full use of cellular automata (CA) and directed networks to model dynamic bidding simulation for each which participates in the multivariate generation right trading market among wind farms and thermal units. Firstly, it analyzes the evaluation gains of each trading individual in historical periods and the risk gains of neighborhood individuals in the current period. Secondly, it put forwards transfer matrixes of historical bidding strategies and neighborhood bidding strategies and forms the organic combination of both, leading to a new round bidding strategy among trading individuals. Finally, bidding simulation results are evaluated through R/S analysis and its Hurst parameter. Further, bidding strategies and risk sensitivity are quantitatively analyzed based on an example. The results show that this proposed method can provide an effective and feasible bidding decision in the case of asymmetric information of generation right trading.