Kullback-Leibler-Quadratic Optimal Control of Flexible Power Demand

Neil Cammardella (1) , Ana Bušić (2, 3) , Yuting Ji (4) , Sean Meyn (5)

1 UF|ECE - Department of Electrical and Computer Engineering [Gainesville]
2 DYOGENE - Dynamics of Geometric Networks
3 LINCS - Laboratory of Information, Network and Communication Sciences
4 CEE - Department of Civil and Environmental Engineering [Stanford]
5 CSL - Coordinated Science Laboratory

A new stochastic control methodology is introduced for distributed control, motivated by the goal of creating virtual energy storage from flexible electric loads, i.e. Demand Dispatch. In recent work, the authors have introduced Kullback-Leibler-Quadratic (KLQ) optimal control as a stochastic control methodology for Markovian models. This paper develops KLQ theory and demonstrates its applicability to demand dispatch. In one formulation of the design, the grid balancing authority simply broadcasts the desired tracking signal, and the heterogeneous population of loads ramps power consumption up and down to accurately track the signal. Analysis of the Lagrangian dual of the KLQ optimization problem leads to a menu of solution options, and expressions of the gradient and Hessian suitable for Monte-Carlo-based optimization. Numerical results illustrate these theoretical results.

Domaines: Optimisation et contrôle [math.OC]; Energie électrique; Probabilités [math.PR]; Systèmes et contrôle [cs.SY]

Neil Cammardella, Ana Bušić, Yuting Ji, Sean Meyn. Kullback-Leibler-Quadratic Optimal Control of Flexible Power Demand. CDC 2019 - 58th IEEE Conference on Decision and Control, Dec 2019, Nice, France. ⟨hal-02425974⟩