DocumentCode :
3587731
Title :
Statistical scheduling of economic dispatch and energy reserves of hybrid power systems with high renewable energy penetration
Author :
Yi Gu ; Huaiguang Jiang ; Yingchen Zhang ; Gao, David Wenzhong
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Denver, Denver, CO, USA
fYear :
2014
Firstpage :
530
Lastpage :
534
Abstract :
A statistical scheduling approach to economic dispatch and energy reserves is proposed in this paper. The proposed approach focuses on minimizing the overall power operating cost with considerations of renewable energy uncertainty and power system security. In such a system, it is challenging and yet an open question on the scheduling of economic dispatch together with energy reserves, due to renewable energy generation uncertainty, and spatially wide distribution of energy resources. The hybrid power system scheduling is formulated as a convex programming problem to minimize power operating cost, taking considerations of renewable energy generation, power generation-consumption balance and power system security. A genetic algorithm based approach is used for solving the minimization of the power operating cost. The IEEE 24-bus reliability test system (IEEE-RTS), which is commonly used for evaluating the price stability of power system and reliability, is used as the test bench for verifying and evaluating system performance of the proposed scheduling approach.
Keywords :
IEEE standards; convex programming; cost reduction; genetic algorithms; hybrid power systems; minimisation; power consumption; power generation dispatch; power generation economics; power generation reliability; power generation scheduling; power system security; renewable energy sources; IEEE 24-bus RTS; IEEE 24-bus reliability test system; convex programming problem; economic dispatch statistical scheduling approach; energy reserves; energy resource distribution; genetic algorithm; power generation-consumption balancing; power operating cost minimization; power system reliability; power system security; power system stability; renewable energy generation uncertainty; Economics; Generators; Optimal scheduling; Renewable energy sources; Wind power generation; Wind turbines; Gaussian Distribution; Genetic Algorithm; IEEE-RTS; Operating cost;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2014 48th Asilomar Conference on
Print_ISBN :
978-1-4799-8295-0
Type :
conf
DOI :
10.1109/ACSSC.2014.7094501
Filename :
7094501
Link To Document :
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