scholarly journals Scheduling model of power system with renewable energy and transaction mode of direct electricity purchase by large consumers considering network security constraints

2019 ◽  
Vol 2019 (16) ◽  
pp. 899-904
Author(s):  
Yan Li ◽  
Xiuli Wang ◽  
Wentao Zhang ◽  
Yu Zuo ◽  
Qianwen Zhang
Energies ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 144 ◽  
Author(s):  
Gerardo Osório ◽  
Miadreza Shafie-khah ◽  
Juan Lujano-Rojas ◽  
João Catalão

2019 ◽  
Vol 11 (10) ◽  
pp. 2829 ◽  
Author(s):  
Jun Dong ◽  
Peiwen Yang ◽  
Shilin Nie

With renewable energy sources (RESs) highly penetrating into the power system, new problems emerge for the independent system operator (ISO) to maintain and keep the power system safe and reliable in the day-ahead dispatching process under the fluctuation caused by renewable energy. In this paper, considering the small hydropower with no reservoir, different from the other hydro optimization research and wind power uncertain circumstances, a day-ahead scheduling model is proposed for a distributed power grid system which contains several distributed generators, such as small hydropower and wind power, and energy storage systems. To solve this model, a two-stage stochastic robust optimization approach is presented to smooth out hydro power and wind power output fluctuation with the aim of minimizing the total expected system operation cost under multiple cluster water inflow scenarios, and the worst case of wind power output uncertainty. More specifically, before dispatching and clearing, it is necessary to cluster the historical inflow scenarios of small hydropower into several typical scenarios via the Fuzzy C-means (FCM) clustering method, and then the clustering comprehensive quality (CCQ) method is also presented to evaluate whether these scenarios are representative, which has previously been ignored by cluster research. It can be found through numerical examples that FCM-CCQ can explain the classification more reasonably than the common clustering method. Then we optimize the two stage scheduling, which contain the pre-clearing stage and the rescheduling stage under each typical inflow scenario after clustering, and then calculate the final operating cost under the worst wind power output scenario. To conduct the proposed model, the day-ahead scheduling procedure on the Institute of Electrical and Electronics Engineers (IEEE) 30-bus test system is simulated with real hydropower and wind power data. Compared with traditional deterministic optimization, the results of two-stage stochastic robust optimization structured in this paper, increases the total cost of the system, but enhances the conservative scheduling strategy, improves the stability and reliability of the power system, and reduces the risk of decision-making simultaneously.


2014 ◽  
Vol 134 (10) ◽  
pp. 1515-1523
Author(s):  
Akihiro Ogawa ◽  
Kazunari Maki ◽  
Kiyoshi Hata ◽  
Yasunori Takeuchi ◽  
Fumio Ishikawa

2011 ◽  
Vol 131 (8) ◽  
pp. 670-676 ◽  
Author(s):  
Naoto Yorino ◽  
Yutaka Sasaki ◽  
Shoki Fujita ◽  
Yoshifumi Zoka ◽  
Yoshiharu Okumoto

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