Probabilistic dynamic multi-objective model for renewable and non-renewable distributed generation planning

Soroudi, A ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1049/iet-gtd.2011.0173
  3. Publisher: 2011
  4. Abstract:
  5. This study proposes a probabilistic dynamic model for multi-objective distributed generation (DG) planning, which also considers network reinforcement at presence of uncertainties associated with the load values, generated power of wind turbines and electricity market price. Monte Carlo simulation is used to deal with the mentioned uncertainties. The planning process is considered as a two-objective problem. The first objective is the minimisation of total cost including investment and operating cost of DG units, the cost paid to purchase energy from main grid and the network reinforcement costs. The second objective is defined as the minimisation of technical risk, including the probability of violating the safe operating technical limits. The Pareto optimal set is found using non-dominated sorting genetic algorithm method and the final solution is selected using a max-min method. The model is applied on two distribution networks and compared with other models to demonstrate its effectiveness
  6. Keywords:
  7. DG unit ; Distributed generations ; Electricity market ; Max-min method ; Monte Carlo Simulation ; Multi objective ; Multiobjective models ; Network reinforcements ; Non-dominated sorting genetic algorithms ; Non-renewable ; Pareto-optimal sets ; Planning process ; Probabilistic dynamics ; Technical limits ; Technical risks ; Total costs ; Computer simulation ; Distributed power generation ; Investments ; Monte Carlo methods ; Multiobjective optimization ; Reinforcement ; Costs
  8. Source: IET Generation, Transmission and Distribution ; Volume 5, Issue 11 , 2011 , Pages 1173-1182 ; 17518687 (ISSN)
  9. URL: http://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2011.0173