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3Rs for Power And Demand

Dynamic monitoring and decision systems maximize energy resources.

Fortnightly Magazine - December 2009

bids (supply and demand) according to the system-wide criteria, which in this case are the criteria of social welfare. 6

Take for example, the results of such a 3R-based self-commitment day-ahead dispatch for the IEEE RTS test system with more than 50-percent wind capacity (see Figures 2-5) . Figure 1 displays the generation mix with wind generation replacing the generation mix originally given for this system in Reference 3 . Shown in Figure 2 is the result of the generation dispatch with large-scale wind power. The system load (solid blue line) is smoother than the total load (green dotted line) when the demand is elastic. The difference between the two shows how much the demand was adjusted to accommodate wind while observing the ramping rates of all power plants. It shows that both coal and gas generation produced significantly less with elastic demand. As wind output suddenly drops, so does the elastic demand. 7

It’s interesting to observe that relatively little demand elasticity made possible large wind power utilization (see Figure 4) and, consequently, a reduction in polluting coal and gas power outputs. Also, Figure 3 plots the total generation cost difference with and without elastic demand. Finally, Figure 5 shows the strong negative correlation between the demand change and demand elasticity. 8 Further extensions of this work are needed to ensure feasible voltage support. It is widely recognized that significant efficiency and reliability enhancements, everything else being equal, would be brought about by systematic voltage management as real power is dispatched (see References 4 and 5) . Even blackouts could be prevented this way (see Reference 6) .

Software in Distributed Risk Management

The implementation of such a simple 3Rs design would go a very long way toward enabling choice by market participants and, at the same time, toward coordinating these choices according to the system-wide performance criteria enforced by the system operators. To ensure that system operators have incentives to deploy the most efficient clearing of bids without creating reliability problems, it’s necessary that the system operators be given the incentives to do their job to the best of their ability as well.

For example, reliability-related risks could be managed many different ways and have huge implications on the bids cleared and the overall system cost as well as on environmental pollution. Much monitoring and decision-making know-how by the system operators can be implemented to reduce some very quantifiable system-wide performance metrics without creating reliability problems (see Reference 6) .

Given the state of the software used today by system operators, the physical risks caused by highly variable resources would be very difficult to untangle and align with financial risks. Instead, an internalizing of the risk by those creating it would make the responsibilities much better understood. It might become possible to establish benchmarks for monitoring the performance of system operators when binding self-commitment is done by the market participants; this has been difficult when the system operators are responsible for managing major uncertainties caused by the highly variable resources. Allowing renewable resources to vary in highly unpredictable ways, and