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Reactive Power Constrained Locational Marginal Pricing using Loss Distribution Matrix


Affiliations
1 Electrical and Electronics Department, KL University, Vaddeswaram – 522502, Dist. Guntur, Andhra Pradesh, India
 

Objective: The objective of this paper is to obtain LMP with constrained reactive power by using optimal power flows. Methods: Loss distribution matrix method has been used to obtain loss distribution matrix. In this paper, by constraining reactive power to Matrix Loss Distribution methodology we obtain LMP. The benefit of Matrix Loss Distribution is illustrated through the case study IEEE 14 bus system and a numerical example on 5 Bus system has been discussed in detail. Findings: Matrix Loss Distribution method developed by V. Sarkar has been modified in this paper by considering reactive power.

Keywords

Fictitious Nodal Demand (FND), Locational Marginal Pricing (LMP), Loss Distribution Matrix (LDM), Vector Loss Distribution (VLD).
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  • Reactive Power Constrained Locational Marginal Pricing using Loss Distribution Matrix

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Authors

V. Jahnavi
Electrical and Electronics Department, KL University, Vaddeswaram – 522502, Dist. Guntur, Andhra Pradesh, India
A. Appa Rao
Electrical and Electronics Department, KL University, Vaddeswaram – 522502, Dist. Guntur, Andhra Pradesh, India

Abstract


Objective: The objective of this paper is to obtain LMP with constrained reactive power by using optimal power flows. Methods: Loss distribution matrix method has been used to obtain loss distribution matrix. In this paper, by constraining reactive power to Matrix Loss Distribution methodology we obtain LMP. The benefit of Matrix Loss Distribution is illustrated through the case study IEEE 14 bus system and a numerical example on 5 Bus system has been discussed in detail. Findings: Matrix Loss Distribution method developed by V. Sarkar has been modified in this paper by considering reactive power.

Keywords


Fictitious Nodal Demand (FND), Locational Marginal Pricing (LMP), Loss Distribution Matrix (LDM), Vector Loss Distribution (VLD).



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i28%2F132406