|Title||Barriers to Increasing the Role of Demand Resources in Electricity Markets|
|Publication Type||Conference Paper|
|Year of Publication||2014|
|Authors||Alberto J Lamadrid, Timothy D Mount, Wooyoung Jeon, Hao Lu|
|Conference Name||2014 47th Hawaii International Conference on System Sciences (HICSS)|
|Conference Location||Waikoloa, HI|
|Keywords||ancillary services, electricity markets, load modeling, reliability and markets, RM12-004, smart grid, SuperOPF|
The objective of this paper is to show that customers can benefit from a smart grid if they become more active participants in electricity markets by 1) relying more on deferrable demand (e.g. electric vehicles and augmenting space conditioning with thermal storage) to shift demand away from peak periods and buy more electricity when prices are low at night, and 2) selling ancillary services such as ramping capacity to mitigate the inherent uncertainty of wind generation. These two factors, coupled with the lower operating cost of wind generation compared to conventional generation from fossil fuels, have the potential for reducing the cost of electricity to customers. However, these benefits will not be realized unless the rates charged to customers reflect the true costs of supply. This paper compares how the bills charged to different types of customer are affected by different rate structures with and without the correct economic incentives. The main savings in operating cost come from the displacement of conventional generation by wind generation, and the main savings in capital cost come from reducing the amount of installed conventional generating capacity needed to maintain System Adequacy by 1) reducing the peak system load, and 2) by using deferrable demand to provide ramping services and reduce the amount of conventional generating capacity needed for operating reserves. A new stochastic form of multi-period Security Constrained Optimal Power Flow is applied in a simulation using a reduction of the North Eastern Power Coordinating Council (NPCC) network for a representative summer day. This model treats potential wind generation as a stochastic input and determines the amount of conventional generating capacity needed to maintain reliability endogenously. The analysis assumes implicitly that all deferrable demand at a node is managed by an aggregator. If the rates are structured with the correct economic incentives (i.e. real-time nodal prices for energy- a demand charge determined by the demand during system peak periods, and compensation for providing ramping services), the results show that 1) the economic benefits for customers with thermal storage are substantial, and 2) the main benefits for customers with electric vehicles (without V2G capabilities in this application) come from buying less gasoline. In contrast, if customers pay conventional rates with a fixed price for energy and no demand charge, the economic incentives are perverse and customers with deferrable demand pay more and customers with no deferrable demand pay less.