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Topological considerations on peer-to-peer energy exchange and distributed energy generation in the smart grid

机译：智能电网对等能源交换和分布能源发电的拓扑考虑

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The vision of the future Smart Grid considers end-users connected to it as both consuming and generating energy. Equipped with small-scale renewable energy generators and storage systems, end-users, also known as prosumers, engage in a local energy market for procuring and selling energy, in turn disrupting the traditional utility model. The appeal of this vision lies in the engagement of end-users, in facilitating the introduction and optimization of renewable energy sources, with the overall expectation of optimizing the global energy generation and distribution process. To handle the peer-to-peer energy exchange and distributed energy generation in the digitalized Smart Grid, we proposed an optimization strategy. In the present work, we propose a Monte Carlo based simulation model to investigate the role of the topology in facilitating the peer-to-peer energy exchanges and distributed energy generation. We consider a 37-node distribution network and evaluate four topological models: radial, complete graph, random graph, and small-world. The results indicate that the random graph model is better than other models in reducing the average delivery path length and energy losses in the energy transfer between providers and consumers. The small-world model has higher efficiency than other models in reducing the maximum power load in the distribution network and the cost of buying energy for end-users. We scale up the investigation by considering a 100-node network and evaluate the random graph and the small-world models by varying the rewiring probabilities. The results show that the small-world model outperforms the random graph model on most efficiency metrics, even when considering infrastructural costs. This work provides the foundation for a decision support system for analysis and high level planning of the distribution network.
机译：未来智能电网的愿景考虑了将其连接到它的最终用户，因为消耗和产生能量。配备小规模可再生能源发电机和储存系统，最终用户，也被称为制度，从事当地的能源市场，用于扰乱传统的实用新型。这一愿景的上诉在于促进可再生能源的引入和优化的终端用户的参与，总体期待优化全球能源发电和分配过程。为了处理数字化智能电网中的点对点能量交换和分布式能源，我们提出了一种优化策略。在目前的工作中，我们提出了一种基于蒙特卡罗的仿真模型，来研究拓扑在促进对等能量交换和分布能量产生的作用。我们考虑一个37节点分发网络并评估四种拓扑模型：径向，完整的图形，随机图和小世界。结果表明，随机图模型比其他模型更好地降低提供商和消费者之间的能量转移中的平均传送路径长度和能量损失。小世界模型的效率高于其他模型，减少了分销网络中的最大功率负载以及为最终用户购买能源的成本。我们通过考虑100节点网络来扩大调查，并通过改变重新加热概率来评估随机图和小世界模型。结果表明，即使考虑基础设施成本，小世界模型也在大多数效率指标上表现出随机图模型。这项工作为分配网络的分析和高级规划提供了决策支持系统的基础。

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