Distributed Optimal Energy Management for Energy Internet
Heating systems, Heuristic algorithms, Peer-to-peer computing, Energy resources, Renewable energy sources, Informatics
Daniel Felix Ritchie School of Engineering and Computer Science, Electrical and Computer Engineering
In this paper, a novel energy management framework for energy Internet with many energy bodies is presented, which features multicoupling of different energy forms, diversified energy roles, and peer-to-peer energy supply/demand, etc. The energy body as an integrated energy unit, which may have various functionalities and play multiple roles at the same time, is formulated for the system model development. Forecasting errors, confidence intervals, and penalty factor are also taken into account to model renewable energy resources to provide tradeoff between optimality and possibility. Furthermore, a novel distributed-consensus alternating direction method of multipliers (ADMM) algorithm, which contains a dynamic average consensus algorithm and distributed ADMM algorithm, is presented to solve the optimal energy management problem of energy Internet. The proposed algorithm can effectively handle the problems of power-heat-gas-coupling, global constraint limits, and nonlinear objective function. With this effort, not only the optimal energy market clearing price but also the optimal energy outputs/demands can be obtained through only local communication and computation. Simulation results are presented to illustrate the effectiveness of the proposed distributed algorithm.
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Huaguang Zhang, et al. “Distributed Optimal Energy Management for Energy Internet.” IEEE Transactions on Industrial Informatics, vol. 13, no. 6, 2017, pp. 3081–3097. doi: 10.1109/tii.2017.2714199.