Long-Run Network Pricing for Security of Supply in Distribution Networks

Abstract

Under the deregulated and privatized environment, network pricing is playing two crucial roles in electric power industry: 1) to recover network investment costs by operators, 2) to provide economic incentives to influence where and when network users will use and connect to the networks. It is desirable that network charging methodologies are able to truly reflect the degree of the use of systems by network users and price them accordingly. The aim is to influence the behaviors of prospective users especially distributed generators (DGs) so as to incentivize efficient utilization of existing networks thus minimize the investment cost for its future development.

Since 1980s, a vast number of pricing methodologies have been proposed. Most of them work at the transmission level to reflect the distance certain transactions have to travel from sources to sinkers and accordingly attribute the network cost. They are limited to how to attribute the existing network to existing customers, but do not look ahead of time to actively reduce the future network investment cost. In the UK, the distribution reinforcement model (DRM) has been the foundation for distribution charging since its introduction. It is based on year-ahead network investment from historical projection and allocates this to network users based on postage stamp, i.e. the same yardstick for the same voltage level. This approach is no longer able to effectively cope with increasing distributed generation and responsive demand. Hence, a revolutionary charging model for distribution networks pricing, long-run incremental cost pricing (LRIC), was proposed by University of Bath (UoB) in conjunction with the office of gas and electricity markets (Ofgem) in the UK and Western Power Distribution (WPD).

It is expected that network charging should be cost-reflective so as to price users in accordance with their actual use-of-system extent and thus, produce forward-looking signals to influence users’ prospective behaviors to benefit network efficiency, security and reduce its costs. Network security, as a major driver for network investment, however, has not been well recognized in charging models.

Therefore, this work has carried out intensive research in this area based on the existing LRIC charging model utilized in extra-high voltage (EHV) distribution networks in the UK. As noted by Ofgem, it represents the best available model to incentive appropriate connection of distributed generation and demand responses. The target of this work is to improve the cost-reflectivity of this original LRIC model in two accounts: 1) reflecting the impact that customers place on network security; 2) reflecting the impact that network security placed on network investment. The major work can be summarized as

-Improve the computational efficiency of the existing LRIC model;
-Examine customers’ impact on network components in contingencies and incorporate it into network charging;
-Devise a new model that can price customers according to their different security preference;
-Improve the existing LRIC model to make it able to capture the probabilistic characteristic of networks and nodal unreliability tolerance.

These concepts are firstly illustrated on simple two-busbar or three-bushar systems for simplicity and clarity. They are then demonstrated on practical distribution systems taken from the UK networks and compared with the original LRIC model in terms of cost-reflectivity, transparency and their potential impact on customer behaviors and on the network security and reliability. Test system demonstrations prove the effectiveness of the new philosophies and their advantages in better reflecting customers’ impact on networks and their potential in influencing users’ activities for enhancing network security and reducing the otherwise needed investment.

Date of Award	1 Oct 2010
Original language	English
Awarding Institution	University of Bath
Supervisor	Furong Li (Supervisor)