1. A Multiobjective Minimax Regret Robust VAr Planning Model
- Author
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Jose Roberto Sanches Mantovani, Javier Contreras, David Pozo, Julio López, Univ Cuenca, Pontifical Catholic Univ Rio de Janeiro, Univ Castilla La Mancha, and Universidade Estadual Paulista (Unesp)
- Subjects
Risk ,Mathematical optimization ,020209 energy ,Regular polygon ,Discrete Tap Settings ,Load Shedding ,Energy Engineering and Power Technology ,Efficient frontier ,Regret ,02 engineering and technology ,AC power ,Multi-Objective ,Uncertainties ,law.invention ,Electric power system ,law ,Regret Optimization ,0202 electrical engineering, electronic engineering, information engineering ,Programming paradigm ,Quadratically-Constrained ,Electrical and Electronic Engineering ,Transformer ,Linear equation ,Mathematics - Abstract
Made available in DSpace on 2018-11-28T09:41:41Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-05-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Programa CSF-PAJT, Brazil This paper proposes a risk-based mixed integer quadratically-constrained programming model for the long-term VAr planning problem. Risk aversion is included in the proposed model by means of regret-based optimization to quantify the load shedding risk because of a reactive power deficit. The expected operation and expansion costs of new installed reactive power sources and load shedding risk are jointly minimized. Uncertainty in the active and reactive load demands has been included in the model. An epsilon-constraint approach is used to characterize the optimal efficient frontier. Also, discrete tap settings of tap-changing transformers are modeled as a set of mixed integer linear equations which are embedded into an ac optimal convex power flow. Computational results are obtained from a realistic South and South-East Brazilian power system to illustrate the proposed methodology. Finally, conclusions are duly drawn. Univ Cuenca, Sch Elect Engn, Fac Engn, Cuenca 010150, Ecuador Pontifical Catholic Univ Rio de Janeiro, Dept Elect Engn, BR-22430060 Rio De Janeiro, Brazil Univ Castilla La Mancha, Escuela Tecn Super Ingn Ind, E-13071 Ciudad Real, Spain Sao Paulo State Univ, Dept Elect Engn, Elect Power Syst Planning Lab, BR-18618000 Sao Paulo, Brazil Sao Paulo State Univ, Dept Elect Engn, Elect Power Syst Planning Lab, BR-18618000 Sao Paulo, Brazil FAPESP: 2014-24287-0 Programa CSF-PAJT, Brazil: 88887.064092-2014-00
- Published
- 2017