Allocation of distributed generation using proposed DMSP approach based on utility and customers aspects under deregulated environment

Abstract Many methods were proposed in the literature for finding best allocations for DG placement considering various objectives. Sometimes, it becomes cumbersome task for system planners to select the objective for DG allocation based on utility and customer point of view. For this purpose, a set of optimization functions and sensitivity factors have been developed for allocation of DGs in the system. The optimization method consists of maximizing loadability, minimizing losses and cost while satisfying power system constraints. The sensitivity factor comprises voltage performance index and loss sensitivity factor for DG allocation. A decision made by system planner (DMSP) approach has been proposed to decide the allocation of DGs in the system based on utilities and customer demand. For this purpose, first DG locations have been planned in the system based on various objectives. Then, suitable objective has been decided from utility and customer necessities by DMSP. Having these in order, DMSP and analytic hierarchy process (AHP) has been used to make a decision over getting the appropriate locations for DGs placement in the system. A combined suitable option for DG allocations with equal weightage to the various objectives has also been studied in this work.

[1]  F. Pilo,et al.  A multiobjective evolutionary algorithm for the sizing and siting of distributed generation , 2005, IEEE Transactions on Power Systems.

[2]  K. Afshar,et al.  Application of IPSO-Monte Carlo for optimal distributed generation allocation and sizing , 2013 .

[3]  Om P. Malik,et al.  Risk-based distributed generation placement , 2008 .

[4]  Hadi Saadat,et al.  Power System Analysis , 1998 .

[5]  A. Akbarimajd,et al.  A Method for Placement of DG Units in Distribution Networks , 2008, IEEE Transactions on Power Delivery.

[6]  S. C. Choube,et al.  Distributed generation planning using differential evolution accounting voltage stability consideration , 2012 .

[7]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[8]  Faruk Ugranli,et al.  Multiple-distributed generation planning under load uncertainty and different penetration levels , 2013 .

[9]  Fabrizio Giulio Luca Pilo,et al.  Optimisation of embedded generation sizing and siting by using a double trade-off method , 2005 .

[10]  N. S. Rau,et al.  Optimum location of resources in distributed planning , 1994 .

[11]  G. Andersson,et al.  Evaluating congestion management schemes in liberalized electricity markets using an agent-based simulator , 2006, 2006 IEEE Power Engineering Society General Meeting.

[12]  D. Singh,et al.  Multiobjective Optimization for DG Planning With Load Models , 2009, IEEE Transactions on Power Systems.

[13]  João Tomé Saraiva,et al.  LONG TERM MARGINAL PRICES - SOLVING THE REVENUE RECONCILIATION PROBLEM OF TRANSMISSION PROVIDERS , 2005 .

[14]  Yasuhiro Hayashi,et al.  Application of tabu search to optimal placement of distributed generators , 2001, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[15]  Shahrokh Saadate,et al.  A novel optimal distribution system planning framework implementing distributed generation in a deregulated electricity market , 2010 .

[16]  A. David,et al.  Transmission congestion management in an electricity market , 1999 .

[17]  A. Keane,et al.  Optimal allocation of embedded generation on distribution networks , 2005, IEEE Transactions on Power Systems.

[18]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[19]  Mohammad Shahidehpour,et al.  The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee , 1999 .

[20]  Pierluigi Siano,et al.  Hybrid GA and OPF evaluation of network capacity for distributed generation connections , 2008 .

[21]  Jung-Wook Park,et al.  Selection of Optimal Location and Size of Multiple Distributed Generations by Using Kalman Filter Algorithm , 2009, IEEE Transactions on Power Systems.

[22]  Gheorghe Grigoras,et al.  Two-stage distributed generation optimal sizing with clustering-based node selection , 2012 .

[23]  A. David,et al.  Optimal dispatch under transmission contracts , 1999 .

[24]  Magdy M. A. Salama,et al.  Distributed generation technologies, definitions and benefits , 2004 .

[25]  I Pisica,et al.  Optimal Distributed Generation Location and Sizing Using Genetic Algorithms , 2009, 2009 15th International Conference on Intelligent System Applications to Power Systems.

[26]  Caisheng Wang,et al.  Analytical approaches for optimal placement of distributed generation sources in power systems , 2004 .

[27]  G. Sheblé,et al.  Power generation operation and control — 2nd edition , 1996 .

[28]  R. Jabr,et al.  Ordinal optimisation approach for locating and sizing of distributed generation , 2009 .

[29]  Chanan Singh,et al.  DG integrated multistage distribution system expansion planning , 2011 .