Allocation of solar units to reduce annual costs of the distribution system

It is widely accepted that renewable sources can find their significant role in power distribution systems. These non-pollutant resources have a lot of advantages such as reducing active power loss, increasing reliability, supplying the peak load duration time, etc. This paper presents a solar unit planning considering uncertainty of solar radiance in order to reduce the costs of the distribution system including costs of energy loss, energy not supplied costs and the purchased power costs. The uncertainty of solar radiance is modeled with Beta probability density function. The planning problem is formulated as mixed integer nonlinear programming (MINLP) and is tested on a 9 bus distribution system using GAMS software. The results show a significant reduction in costs of distribution system in presence of solar units.

[1]  E.F. El-Saadany,et al.  Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization , 2010, IEEE Transactions on Power Systems.

[2]  M. M. A. Salama,et al.  Distribution system loss minimization using optimal DG mix , 2009, 2009 IEEE Power & Energy Society General Meeting.

[3]  Ehab F. El-Saadany,et al.  Probabilistic approach for optimal allocation of wind-based distributed generation in distribution systems , 2011 .

[4]  Shahram Jadid,et al.  Promotion strategy of clean technologies in distributed generation expansion planning , 2009 .

[5]  Shahram Jadid,et al.  A fuzzy environmental-technical-economic model for distributed generation planning , 2011 .

[6]  Kostas Kalaitzakis,et al.  Methodology for optimal sizing of stand-alone photovoltaic/wind-generator systems using genetic algorithms , 2006 .

[7]  M.M.A. Salama,et al.  An integrated distributed generation optimization model for distribution system planning , 2005, IEEE Transactions on Power Systems.

[8]  Shahram Jadid,et al.  A hierarchical decision making model for the prioritization of distributed generation technologies: A case study for Iran , 2009 .

[9]  F. Pilo,et al.  A Multi-Objective Approach for the Optimal Distributed Generation Allocation with Environmental Constraints , 2008, Proceedings of the 10th International Conference on Probablistic Methods Applied to Power Systems.

[10]  Kai Zou,et al.  Distribution System Planning With Incorporating DG Reactive Capability and System Uncertainties , 2012, IEEE Transactions on Sustainable Energy.

[11]  C. Tautiva,et al.  Optimal placement of distributed generation on distribution networks , 2008, 2008 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America.

[12]  Mohamed A. H. El-Sayed,et al.  Dispersed generation impact on distribution network expansion planning , 2009, 2009 Power Systems Conference.

[13]  M.-R. Haghifam,et al.  ACO Based Algorithm for Distributed Generation Sources Allocation and Sizing in Distribution Systems , 2007, 2007 IEEE Lausanne Power Tech.

[14]  R. Chedid,et al.  Probabilistic performance assessment of autonomous solar-wind energy conversion systems , 1999 .

[15]  Hamidreza Zareipour,et al.  A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources , 2011 .