“Without integrating operational data with traditional IT data, I don’t think the industry would be any further along than it was five or 10 years ago.”
~Steve Ehrlich, Space Time Insight...
3Rs for Power And Demand
Dynamic monitoring and decision systems maximize energy resources.
developing a market in which users are paid for not being served when this occurs, is much harder to implement at present (see Reference 7 ). Instead, risks should be internalized by system users ( e.g., power producers, end users and aggregators), and once the bid is made the financial penalty for deviating from the predicted and self-committed bid should be high. 9
The main reason for designing the 3Rs for effective coordination of variable resources, including responsive demand, is to reduce information rents between the system operators, the portfolios of market participants, and ultimately between the portfolio creators and the individual resources. This can be done only when the self-commitments are binding. Failure to meet the obligation communicated should result in much higher costs to those who deviate from the pre-specified self-commitments. This basic framework could take care of major misalignments and today’s lack of incentives. It would begin to compensate the demand adequately for its contribution to the reduced reserves when managing variable wind, for example. This would give incentives to the LSEs to aggregate and reduce volatilities seen by the system. This would be in sharp contrast with what customers are paid today for participating in demand programs by making themselves available for direct load control by the utilities during emergencies. It would incentivize variable resources to reduce the volatilities of their outputs by either making better predictions or installing technologies that can do this, such as storage; otherwise, they would have to pay for the costs borne by the system to manage them as negative loads. Much can be gained by continuous demand response within its constraints even during normal operation. The total cost and pollution will decrease. Customers will be in control of how proactively they wish to participate, and they’d be given signals about how their bills would change. Notably, binding mid-and long-term self-commitments are likely to improve the overall performance much more than very short-term self-commitments (see Figure 1) .
Much gets accomplished through such self-commitment. Instead of overwhelming the system operators with the requirement to predict system demand, to know in detail ramping rates and start-up and shut-down costs, and to decide on behalf of power producers the risks the latter are willing to take due to uncertainty in prices, these tasks are performed by the power producers themselves. The system operator, instead, is in charge of posting cleared prices and also, even better, forward electricity prices. 10 Similarly, responsive demand internalizes its own physical constraints and the value of the electricity service at various hours, and creates demand functions which are no longer inter-temporally dependent.
Quite importantly, this self commitment leads to risk distribution among all the power producers and customers over time. The system operator no longer takes the major risks of predicting system demand, as this is no longer predictable due to the high variability of resources that aren’t directly controlled.
Even more real benefits could be obtained by introducing the 3Rs to medium- and long-term forward markets. A more accurate forecast of the needs and resources available becomes possible only