DocumentCode :
135658
Title :
Distributed storage operation in distribution network with stochastic renewable generation
Author :
Tianshu Chu ; Junjie Qin ; Jieming Wei
Author_Institution :
CEE, Stanford Univ., Stanford, CA, USA
fYear :
2014
fDate :
27-31 July 2014
Firstpage :
1
Lastpage :
5
Abstract :
The integration of distributed renewable energy generations and storages in the distribution system imposes new challenges on the paradigm of the operation. The resulting control problems are intrinsically hard because of nonlinearity in power flow equations, stochasticity in renewable generations, and inter-temporal coupling of decision problems due to energy storage. This paper provides an initial attempt to solve these nonlinear stochastic control problems numerically, within the framework of Markov decision processes (MDPs). Detailed MDPs are first designed for two-bus sub-networks of the distribution system. Optimal control policies for each sub-network are then combined to guide the design of a control policy to operate the entire storage system on a distribution network. The performance of this approach is demonstrated numerically by comparing with other typical operation policies.
Keywords :
Markov processes; control nonlinearities; energy storage; load flow control; nonlinear control systems; optimal control; power distribution control; renewable energy sources; stochastic systems; MDP; Markov decision processes; decision problems; distributed renewable energy generations; distributed renewable energy storages; distributed storage operation; distribution network; distribution system; intertemporal coupling; nonlinear stochastic control problems; nonlinearity; optimal control policies; power flow equations; stochastic renewable generation; Analytical models; Energy storage; Equations; Load modeling; Reactive power; Stochastic processes; Substations; Electric distribution system; distributed energy storage; distributed renewable integration; dynamic programming;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location :
National Harbor, MD
Type :
conf
DOI :
10.1109/PESGM.2014.6939512
Filename :
6939512
Link To Document :
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