TY - JOUR
T1 - Distributed dynamic pricing based on demand-supply balance and voltage phase difference in power grid
AU - Okawa, Yoshihiro
AU - Namerikawa, Toru
N1 - Publisher Copyright:
© 2015, South China University of Technology, Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg.
PY - 2015/5/22
Y1 - 2015/5/22
N2 - This paper discusses a distributed decision procedure for determining the electricity price for a real-time electricity marketin an energy management system. The price decision algorithm proposed in this paper derives the optimal electricity pricewhile considering the constraints of a linearized AC power grid model. The algorithm is based on the power demand-supplybalance and voltage phase differences in a power grid. In order to determine the optimal price that maximizes the social welfare distributively and to improve the convergence speed of the algorithm, the proposed algorithm updates the price through the alternating decision making of market participants. In this paper, we show the convergence of the price derived from our proposed algorithm. Furthermore, numerical simulation results show that the proposed dynamic pricing methodology is effective and that there is an improvement in the convergence speed, as compared with the conventional method.
AB - This paper discusses a distributed decision procedure for determining the electricity price for a real-time electricity marketin an energy management system. The price decision algorithm proposed in this paper derives the optimal electricity pricewhile considering the constraints of a linearized AC power grid model. The algorithm is based on the power demand-supplybalance and voltage phase differences in a power grid. In order to determine the optimal price that maximizes the social welfare distributively and to improve the convergence speed of the algorithm, the proposed algorithm updates the price through the alternating decision making of market participants. In this paper, we show the convergence of the price derived from our proposed algorithm. Furthermore, numerical simulation results show that the proposed dynamic pricing methodology is effective and that there is an improvement in the convergence speed, as compared with the conventional method.
KW - AC model of power grid
KW - Smart gird
KW - real-time pricing
UR - http://www.scopus.com/inward/record.url?scp=84935015364&partnerID=8YFLogxK
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U2 - 10.1007/s11768-015-4131-5
DO - 10.1007/s11768-015-4131-5
M3 - Article
AN - SCOPUS:84935015364
SN - 2095-6983
VL - 13
SP - 90
EP - 100
JO - Control Theory and Technology
JF - Control Theory and Technology
IS - 2
ER -