Multi-Stage Stochastic Programming to Joint Economic Dispatch for Energy and Reserve With Uncertain Renewable Energy

To address the uncertain renewable energy in the day-ahead optimal dispatch of energy and reserve, a multi-stage stochastic programming model is established in this paper to minimize the expected total costs. The uncertainties over the multiple stages are characterized by a scenario tree and the opt...

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Vydáno v:IEEE transactions on sustainable energy Ročník 11; číslo 3; s. 1140 - 1151
Hlavní autoři: Lu, Runzhao, Ding, Tao, Qin, Boyu, Ma, Jin, Fang, Xin, Dong, Zhaoyang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.07.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Convergence
Criteria
Decision trees
Dynamic programming
Economic dispatch
Electric power grids
Energy
Indexes
Iterative methods
Load modeling
Optimization
Power dispatch
Programming
Renewable energy
Renewable energy sources
Renewable resources
stochastic dual dynamic programming (SDDP)
Stochastic processes
Stochastic programming
Uncertainty
ISSN:1949-3029, 1949-3037
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Shrnutí:To address the uncertain renewable energy in the day-ahead optimal dispatch of energy and reserve, a multi-stage stochastic programming model is established in this paper to minimize the expected total costs. The uncertainties over the multiple stages are characterized by a scenario tree and the optimal dispatch scheme is cast as a decision tree which guarantees the flexibility to decide the reasonable outputs of generation and the adequate reserves accounting for different realizations of renewable energy. Most importantly, to deal with the "Curse of Dimensionality" of stochastic programming, stochastic dual dynamic programming (SDDP) is employed, which decomposes the original problem into several sub-problems according to the stages. Specifically, the SDDP algorithm performs forward pass and backward pass repeatedly until the convergence criterion is satisfied. At each iteration, the original problem is approximated by creating a linear piecewise function. Besides, an improved convergence criterion is adopted to narrow the optimization gaps. The results on the IEEE 118-bus system and real-life provincial power grid show the effectiveness of the proposed model and method.
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ISSN:1949-3029
1949-3037
DOI:10.1109/TSTE.2019.2918269