Cooperative Distributed Energy Scheduling in Microgrids
Cooperative Distributed Energy Scheduling in Microgrids
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DOI：
10.1007/978-981-10-7001-3_9
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发表时间：
2018
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影响因子：
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通讯作者：
M. Rahmani-Andebili
中科院分区：
文献类型：
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作者：
M. Rahmani-Andebili
本章介绍了一种多时间尺度模型预测控制（MPC）方法，并将其随机应用于微电网（MG）的分布式能源协调调度问题。协作分布式方法是首选，因为集中式方法不适用于竞争性电力市场环境，因为它需要所有MG的所有数据，这是不切实际的。在本章中，为了处理与可再生能源（RES）的输出功率和负荷需求的可变性和不确定性，随机MPC应用于分布式能源调度问题的MG。此外，在随机MPC中考虑多时间尺度方法能够同时具有对优化时间范围的广阔视野和对问题变量的精确分辨率。在此，具有不同组源的每个MG能够与电力市场和相邻MG交易电力。数值研究表明，在分布式能源调度问题中的MG的合作是有益的，也是多时间尺度MPC相比，单时间尺度MPC在非合作和合作的分布式能源调度问题的优势。
This chapter introduces a multi-time scale model predictive control (MPC) approach which is stochastically applied in the cooperative distributed energy scheduling problem of the microgrids (MG). The cooperative distributed approach is preferred, since a centralized one is not applicable in a competitive power market environment because it requires all the data of all the MGs, which is impractical. In this chapter, in order to deal with the variability and uncertainties associated with output power of the renewable energy resources (RES) and load demand, stochastic MPC is applied in distributed energy scheduling problem of MGs. Additionally, considering multi-time scale approach in the stochastic MPC is capable of simultaneously having vast vision for the optimization time horizon and precise resolution for the problem variables. Herein, each MG with a different set of sources is able to transact power with the electricity market and the neighboring MGs. The numerical study demonstrates that cooperation of the MGs in the distributed energy scheduling problem is beneficial, and also the multi-time scale MPC is advantageous compared to the single-time scale MPC in both non-cooperative and cooperative distributed energy scheduling problems.