Section: New Results

Distributed control design for balancing the grid using flexible loads

Inexpensive energy from the wind and the sun comes with unwanted volatility, such as ramps with the setting sun or a gust of wind. Controllable generators manage supply-demand balance of power today, but this is becoming increasingly costly with increasing penetration of renewable energy. It has been argued since the 1980s that consumers should be put in the loop: “demand response” will help to create needed supply-demand balance. However, consumers use power for a reason and expect that the quality of service (QoS) they receive will lie within reasonable bounds. Moreover, the behavior of some consumers is unpredictable, while the grid operator requires predictable controllable resources to maintain reliability.

The goal of the book chapter [31] is to describe an emerging science for demand dispatch that will create virtual energy storage from flexible loads. By design, the grid-level services from flexible loads will be as controllable and predictable as a generator or fleet of batteries. Strict bounds on QoS will be maintained in all cases. The potential economic impact of these new resources is enormous. California plans to spend billions of dollars on batteries that will provide only a small fraction of the balancing services that can be obtained using demand dispatch. The potential impact on society is enormous: a sustainable energy future is possible with the right mix of infrastructure and control systems.

In [17], presented at IEEE CDC 2018, a natural notion of energy capacity is proposed for the special case of thermostatically controlled loads (TCLs). It is shown that this quantity is closely approximated by thermal energy capacity, which is a component of the “leaky battery model” introduced in prior work. Simulation experiments in a distributed control setting show that these energy limits, and accompanying power capacity limits, are reliable indicators of online capacity, even for a heterogeneous population of loads. A feedforward/feedback control scheme is proposed for a large collection of heterogeneous loads. At the local level, control loops are used to create cooperative responses from each load in a given class of homogeneous loads. This simplifies control of the aggregate based on two pieces of information: aggregate power consumption from each class of loads and the state of charge surrogate that is a part of the leaky battery model. This information is required at a slow time-scale (say, 5 minute sampling).

In [18], we study the problem of coordination of a collection of on/off thermostatically controlled loads (TCLs) to act as a “virtual battery”. Virtual Energy Storage (VES) is provided by the collection by either consuming more (charging) or less (discharging) power than the baseline. VES can be an inexpensive alternative to batteries when a large share of the electricity comes from volatile sources such as solar and wind. Almost all prior work has assumed that the outside weather - which significantly effects a TCLs behavior - is constant. We combine the above distributed load control design with a grid level MPC (model predictive control) that uses predictions of disturbances (weather) over a planning horizon. Additionally, irrespective of the choice of control architecture, there is a fundamental limit to the power and energy capacity of the collection of TCLs. We partially address this issue by scaling the reference signal by a function of the outside air temperature.