A bilevel approach for optimal contract pricing of independent dispatchable DG units in distribution networks

Summary Distributed generation (DG) units are increasingly installed in the power systems. Distribution companies (DisCo) can opt to purchase the electricity from DG in an energy purchase contract to supply the customer demand and reduce energy loss. This paper proposes a framework for optimal contract pricing of independent dispatchable DG units considering competition among them. While DG units tend to increase their profit from the energy purchase contract, DisCo minimizes the demand supply cost. Multi-leader follower game theory concept is used to analyze the situation in which competing DG units offer the energy price to DisCo and DisCo determines the DG generation. A bi-level approach is used to formulate the competition in which each DG problem is the upper-level problem and the DisCo problem is considered as the lower-level one. Combining the optimality conditions of all upper-level problems with the lower-level problem results in a multi-DG equilibrium problem formulated as an equilibrium problem with equilibrium constraints. Using a nonlinear approach, the equilibrium problem with equilibrium constraints problem is reformulated as a single nonlinear optimization model, which is simultaneously solved for all independent DG units. The proposed framework was applied to the modified IEEE 34-bus distribution test system. Performance and robustness of the proposed framework in determining econo-technically fair DG contract price has been demonstrated through a series of analyses. Copyright © 2016 John Wiley & Sons, Ltd.

[1]  Shahram Jadid,et al.  A two-stage robust model to determine the optimal selling price for a distributed generation-owning retailer , 2015 .

[2]  P. Sotkiewicz,et al.  Nodal pricing for distribution networks: efficient pricing for efficiency enhancing DG , 2006, IEEE Transactions on Power Systems.

[3]  Rahmat-Allah Hooshmand,et al.  A new simultaneous placement of distributed generation and demand response resources to determine virtual power plant , 2016 .

[4]  Hamed Mohsenian-Rad,et al.  Price-Maker Economic Bidding in Two-Settlement Pool-Based Markets: The Case of Time-Shiftable Loads , 2016, IEEE Transactions on Power Systems.

[5]  Sven Leyffer,et al.  Solving multi-leader–common-follower games , 2010, Optim. Methods Softw..

[6]  Swapan Kumar Goswami,et al.  Optimum allocation of distributed generations based on nodal pricing for profit, loss reduction, and voltage improvement including voltage rise issue , 2010 .

[7]  K. Shaloudegi,et al.  A Novel Policy for Locational Marginal Price Calculation in Distribution Systems Based on Loss Reduction Allocation Using Game Theory , 2012, IEEE Transactions on Power Systems.

[8]  Peng Peng,et al.  An optimal purchase and sale power model considering microgrids , 2015 .

[9]  R. Ramakumar,et al.  An approach to quantify the technical benefits of distributed generation , 2004, IEEE Transactions on Energy Conversion.

[10]  Jorge J. Moré,et al.  The NEOS Server , 1998 .

[11]  Ashkan Sadeghi-Mobarakeh,et al.  A game theoretic framework for DG optimal contract pricing , 2013, IEEE PES ISGT Europe 2013.

[12]  J. I. Muñoz,et al.  Optimal Contract Pricing of Distributed Generation in Distribution Networks , 2011, IEEE Transactions on Power Systems.

[13]  G. Joós,et al.  Models for Quantifying the Economic Benefits of Distributed Generation , 2008, IEEE Transactions on Power Systems.

[14]  Dheeraj Kumar Khatod,et al.  Optimal planning of distributed generation systems in distribution system: A review , 2012 .

[15]  Marcos J. Rider,et al.  Bilevel approach for optimal location and contract pricing of distributed generation in radial distribution systems using mixed-integer linear programming , 2013 .

[16]  H. Haghighat,et al.  A Bilevel Approach to Operational Decision Making of a Distribution Company in Competitive Environments , 2012, IEEE Transactions on Power Systems.

[17]  Anthony Vannelli,et al.  Formulation of oligopolistic competition in AC power networks: An NLP approach , 2012, 2012 IEEE Power and Energy Society General Meeting.

[18]  J. Pang,et al.  Strategic gaming analysis for electric power systems: an MPEC approach , 2000 .

[19]  Kankar Bhattacharya,et al.  A generic operations framework for discos in retail electricity markets , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[20]  Nikos D. Hatziargyriou,et al.  Optimal Distributed Generation Placement in Power Distribution Networks : Models , Methods , and Future Research , 2013 .

[21]  Hassan Monsef,et al.  Market power analysis for the Iranian electricity market , 2010 .

[22]  Chandrasekhar Yammani,et al.  Optimal placement and sizing of distributed generations using shuffled bat algorithm with future load enhancement , 2016 .

[23]  A. Jofré,et al.  A distribution company energy acquisition market model with integration of distributed generation and load curtailment options , 2005, IEEE Transactions on Power Systems.

[24]  M. Anjos,et al.  Numerical Study of Affine Supply Function Equilibrium in AC Network-Constrained Markets , 2007, IEEE Transactions on Power Systems.