access icon openaccess Formulation and evaluation of long-term allocation problem for renewable distributed generations

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 31/01/2017, Accepted 19/06/2017, Revised 17/05/2017, Published 26/06/2017

The penetration rate of renewable energy into the power systems has been increasing in many countries. The governments and international energy organisations have announced the long-term visions such as power generation and penetration rate of renewable energy. However, the specific installation plans and scenarios have not been discussed and determined. Although plenty of researches related to optimal allocation problem of renewable energy-based distributed generations (DGs) have been proposed in past decade, most of the studies have considered only 1 year's allocation and daily annual system operation. Therefore, this study proposes a novel scenario-based two-stage stochastic programming problem for long-term allocation of DGs. Also, a scenario generation procedure is presented for solving the problem. Furthermore, few studies have focused on the evaluations and analyses of the optimal solutions in various aspects. Thus, this study shows the optimal allocation results on 34-bus distribution network, considering the different scenario generation methods and number of scenarios. The authors finally discuss the important points and indicate that decision makers have to consider several important issues. In addition, they developed and released a general-purpose framework for optimal allocation of DGs as an open source.

Inspec keywords: stochastic programming; distributed power generation; renewable energy sources; distribution networks

Other keywords: daily annual system operation; long-term allocation problem; general-purpose framework; penetration rate; 34-bus distribution network; power systems; scenario-based two-stage stochastic programming problem; governments; renewable energy-based distributed generations; scenario generation procedure; international energy organisations; power generation

Subjects: Distributed power generation; Optimisation techniques; Distribution networks; Energy resources

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