Open AccessElectric power distribution system expansion planning considering cost elasticity of demand
Author(s) -
GholizadehRoshanagh Reza,
Zare Kazem
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.6740
Subject(s) - price elasticity of demand , time horizon , demand response , elasticity (physics) , mathematical optimization , peak demand , total cost , market demand schedule , derived demand , microeconomics , computer science , economics , demand curve , electricity , mathematics , engineering , materials science , composite material , electrical engineering
Demand side participation is a fundamental property of modern power distribution networks. Time‐of‐use pricing is a common strategy to persuade customers to shift a part of their consumption to low consumption hours. In flat time‐of‐use pricing, it is not the price that changes over a period, it is the cost of energy. The aim of this paper was to quantify impact of cost elasticity of demand on investment plans over a multi‐stage horizon, where the time‐of‐use pricing was taken into account. On one hand, time‐of‐use pricing was modeled with three load levels as peak, medium‐peak and off‐peak. On the other hand, the tendency of customers to participate in reduction of demand was modeled where it shows rate of response of customers to change in cost of energy and it determines maximum demand response penetration. So, it was examined how time‐of‐use pricing and responsive customers can postpone the investments. Mixed integer linear programming method was utilized to solve the optimal distribution expansion planning problem. Simulations were performed on an 18‐node distribution network. Results revealed effectiveness of the proposed model and showed that consideration of cost elasticity of demand in expansion planning, changes optimal configuration of network and significantly influences total costs.