Abstract
This paper considers hydrogen and renewable electricity from power-to-gas (PtG) facilities supplied to a gas grid, a mobility sector, and a power grid. The PtG facilities are equipped with hydrogen buffers and fuel cells. The goal is to maximize the expected profit of PtG facilities without exceeding the grid capacities. The decisions on the supply levels are done in a distributed fashion, yet some coordination with the multiple energy grid operators is necessary to obey the grid capacity constraints. The distributed supply coordination is developed using a model predictive control approach based on a dual decomposition combined with the projected gradient method. The approach results in a two-layer optimization problem experienced by each PtG facility and each grid operator. In this way, the grid operators can manage the PtG facilities via dynamic distribution pricing. We study the fairness of the corresponding algorithm and discuss its practical implementation. Simulation results are provided to evaluate the algorithm performance and to investigate the evolution of distribution prices.
Original language | English |
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Pages (from-to) | 1012-1022 |
Number of pages | 11 |
Journal | IEEE Transactions on Smart Grid |
Volume | 9 |
Issue number | 2 |
DOIs | |
Publication status | Published - Mar-2018 |
Keywords
- Distributed model predictive control
- distributed generators
- energy storage
- intelligent control
- modeling
- MODEL-PREDICTIVE CONTROL
- HOLDING COST
- STABILITY
- STORAGE
- DECOMPOSITION
- PRICES