基于教与学模式改进一致性算法的电—气能量流协同优化

在综合能源网背景下,需考虑将多能量流进行分布式协同优化。针对电力、天然气多主体分布式自治决策的特点,考虑电—气耦合关系,建立了含新能源的多能流局域网优化模型,并通过能源路由器建立了一种合理的规划机制,从而保证各个能源局域网之间能量的有序流动。基于教与学模式优化算法对常规一致性算法进行了改进,并对该优化问题进行了求解,实现了电—气耦合系统的分布式协同优化。能源路由器既是能量装置,又是信息节点,能够将不同能量形式有机整合、协调优化。而基于教与学模式的改进一致性算法有更好的搜索能力和寻优能力,可获得更好的优化结果和计算效率。利用IEEE 118-GAS90电—气互联网络系统算例进行测试,结果验证了所述方法的有效性和可行性。

Collaborative Optimization of Electricity-Gas Energy Flow Using Improved Consensus Algorithm with Teaching-Learning Based Optimization

In the context of integrated energy network, it is necessary to consider distributed collaborative optimization of multiple energy flow. Based on the characteristics of multi-agent distributed autonomy of decision-making for electric power and natural gas, an optimization model of multi-flow local area network with new energy is established considering the relationship of electricity and gas coupling. And a reasonable energy planning mechanism is established based on energy routers to ensure the orderly flow of energy between individual energy local area networks. With the improved consensus optimization algorithm using teaching-learning based optimization, the optimization problem is solved and the distributed collaborative optimization of the electricity-gas coupling system is realized. Energy router is not only an energy device but also an information node, in which different forms of energy are organically integrated and coordinately optimized. The improved consensus algorithm with teaching-learning based optimization has better exploration and exploitation ability, and can obtain better optimization results and calculation efficiency. The IEEE 118-GAS90 electricity-gas interconnected network system is tested as an example and the results verify the effectiveness and feasibility of the proposed method.