Authors: I. Savelli and T. Morstyn
Published in: Omega Volume 103, September 2021, 102450 https://doi.org/10.1016/j.omega.2021.102450
Date Published: 23 March 2021
Some consumers, particularly households, are unwilling to face volatile electricity prices, and they can perceive as unfair price differentiation in the same local area. For these reasons, nodal prices in distribution networks are rarely employed. However, the increasing availability of renewable resources and emerging price-elastic behaviours pave the way for the effective introduction of marginal nodal pricing schemes in distribution networks. The aim of the proposed framework is to show how traditional non-flexible consumers can coexist with flexible users in a local distribution area. Flexible users will pay nodal prices, whereas non-flexible consumers will be charged a fixed price derived from the underlying nodal prices. Moreover, the developed approach shows how a distribution system operator should manage the local grid by optimally determining the lines to be expanded, and the collected network tariff levied on grid users, while accounting for both congestion rent and investment costs. The proposed model is formulated as a non-linear integer bilevel program, which is then recast as an equivalent single optimization problem, by using integer algebra and complementarity relations. The power flows in the distribution area are modelled by resorting to a second-order cone relaxation, whose solution is exact for radial networks under mild assumptions. The final model results in a mixed-integer quadratically constrained program, which can be solved with off-the-shelf solvers. Numerical test cases based on both 5-bus and 33-bus networks are reported to show the effectiveness of the proposed method.
Keywords: Network tariff; Fixed cost recovery; Nodal price; Distribution network; Bilevel programming
Insights for EnergyREV:
We demonstrate how different pricing schemes (e.g. fixed, nodal) can coexist in distribution networks, and how a network operator who manages the local grid can optimally recover the overall investment costs. Our findings also show that having more customers on nodal prices improves the system efficiency and reduces network charges required to recover network investment costs.