On the Death and Possible Rebirth of Energy-Only Markets

Our previous research has shown that distributed storage capacity at load centers (e.g. deferrable demand) can lower total system costs by smoothing out and flattening the daily dispatch profile of conventional generating units. The main savings in cost come from the price arbitrage caused by shifting load and from the reduction in the amount of installed conventional generating capacity needed to maintain operating reliability and generation adequacy at the peak system load. However, the full capacity of deferrable demand will not be used to reduce the peak system load whenever the price arbitrage between the peak and off-peak periods is too small to cover the round-trip inefficiency of the storage. If this situation occurs on the peak load day, the outcome is inefficient. The reason is that the presence of deferrable demand makes the peak load endogenous. Since system operators determine the optimal dispatch by minimizing the expected operating costs, they implicitly ignore the potential savings in capital costs associated with reducing the peak system load. This paper presents a mechanism for augmenting the nodal prices during peak load periods to reflect the capital cost of a peaking unit that we call "Peak-System-Load" (PSL) pricing. The first objective is to show that PSL pricing can reduce the total system costs and increase efficiency. However, the relative unpredictability of wind generation makes it harder to identify the timing of the peak net-generation accurately. Since PSL pricing also implies that customers pay higher wholesale prices during peak-load periods, the second objective is to show that paying this extra revenue to generators reduces the amount of missing money caused by the lower wholesale prices associated with generating more from renewable sources. In this sense, PSL pricing may lead to a viable energy-only market. An empirical application illustrates our proposed mechanism using a stochastic form of multi-period Security Constrained Optimal Power Flow (the mops model) and a reduction of the Northeast Power Coordinating Council (NPCC) network to simulate operations on representative days.

I. Introduction

Storage capacity on an electric grid is a valuable resource for maintaining the reliability of supply, particularly when a substantial amount of the generation comes from renewable sources that are inherently uncertain and variable. Basically, storage can be discharged when the generation from wind, for example, is lower than expected and charged if the generation is higher than expected. In addition, storage can flatten the daily pattern of generation from conventional generators by shifting load from peak to off-peak periods. Compared to utility-scale storage at wind farms, the additional advantage of distributed storage, such as Deferrable Demand (DD), ¹

DD decouples the purchase of electric energy from the grid from the delivery of an energy service to customers. For example, using compressors to make ice at night and melting this ice during the day for space cooling, instead of running air conditioners when needed, is an example of DD. There is, however, an additional cost of DD because of the inherent inefficiency of using thermal storage for space cooling. With thermal storage, more electric energy must be purchased from the grid to provide the same level of cooling services to customers.

is that there is less congestion on the grid because the peak amount of electric energy delivered to load centers can be reduced. From this perspective, DD storage is more effective than an equivalent amount of storage at wind farms even though the latter does a better job of mitigating the uncertainty and variability of wind generation.