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Heuristic approach for transactive energy management in active distribution systems

机译：活性分配系统中透气能量管理的启发式方法

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摘要

The advent of distributed energy resources (DERs), which include small conventional and renewable generation units, energy storage, and flexible loads in distribution network needs distributed coordination for effective management. In this paper, a stochastic transactive management framework is proposed to minimize overall cost and avoid network constraints violation at the distribution network level. This framework includes day-ahead scheduling of electric vehicles and air conditioning loads under demand response aggregators (DRAs), and DERs under distributed generation owners (DGOs) into day-ahead wholesale market in a network managed by a distribution network operator (DNO). An agent called distribution independent system operator (DISO) is responsible for coordination among DRAs, DGOs, and DNO. A heuristic step-size update approach is proposed to calculate the Lagrange multiplier iteratively and improve the convergence speed. This framework is modeled as a quadratic constraint programming (QCP) problem and solved using the GAMS solver. Simulation results on a modified 33-bus system with considerable penetration of loads and DERs, shows that the suggested framework can efficiently reduce the iterations to converge and returns an optimal schedule. And demonstrate the effect of network congestion, demand, and generation uncertainties on the resulting objective values of the agents and magnitude of the Lagrange multiplier values.
机译：分布式能源（DERS）的出现，包括小型传统和可再生的生成单位，能量存储和分销网络中的灵活负载需要分布式协调以实现有效管理。在本文中，提出了一种随机的缩放管理框架，以最大限度地降低总成本并避免在分销网络级别违反网络限制。该框架包括在需求响应聚合器（DRA）下的电动车辆和空调负载的一天提前调度，以及分布式发电机（DGOS）下的DGOS中的DGES中，进入由分销网络运营商（DNO）管理的网络中的前方批发市场。称为分发独立系统运营商（DISO）的代理负责在DRA，DGOS和DNO之间进行协调。提出了一种启发式阶梯大小的更新方法来迭代地计算拉格朗日乘法器并提高收敛速度。该框架被建模为二次约束编程（QCP）问题，并使用Gams求解器进行解决。仿真结果对加载和DER具有相当渗透的修改的33母线系统，表明建议的框架可以有效地减少迭代来收敛并返回最佳的时间表。并展示网络拥塞，需求和产生不确定性对拉格朗日乘数值的产生物理值和幅度的产生的影响。

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