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There is enormous flexibility potential in the power consumption of the majority of electric loads. This flexibility can be harnessed to obtain services for managing the grid: with carefully designed decision rules in place, power consumption for the population of loads can be ramped up and down, just like charging and discharging a battery, without any significant impact to consumers' needs. The concept is called Demand Dispatch, and the grid resource obtained from this design virtual energy storage (VES). In order to deploy VES, a balancing authority is faced with two challenges: 1. how to design local decision rules for each load given the target aggregate power consumption (distributed control problem), and 2. how to coordinate a portfolio of resources to maintain grid balance, given a forecast of net-load (resource allocation problem).Rather than separating resource allocation and distributed control, in this paper the two problems are solved simultaneously using a single convex program. The joint optimization model is cast as a finite-horizon optimal control problem in a mean-field setting, based on the new KLQ optimal control approach proposed recently by the authors.The simplicity of the proposed control architecture is remarkable: With a large portfolio of heterogeneous flexible resources, including loads such as residential water heaters, commercial water heaters, irrigation, and utility-scale batteries, the control architecture leads to a single scalar control signal broadcast to every resource in the domain of the balancing authority. Keywords: Smart grids, demand dispatch, distributed control, controlled Markov chains.
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Load-Level Control Design for Demand Dispatch With Heterogeneous Flexible Loads
Over the past decade, there has been significant progress on the science of load control for the creation of virtual energy storage. This is an alternative to demand response, and it is termed demand dispatch. Distributed control is used to manage millions of flexible loads to modify the power consumption of the aggregation, which can be ramped up and down, just like discharging and charging a battery. A challenge with distributed control is heterogeneity of the population of loads, which complicates control at the aggregate level. It is shown in this article that additional control at each load in the population can result in a far aggregate model. The local control is designed to flatten resonances and produce approximately all-pass response. Analysis is based on mean-field control for the heterogeneous population; the mean-field model is only justified because of the additional local control introduced in this article. Theory and simulations indicate that the resulting input--output dynamics of the aggregate has a nearly flat input--output response: the behavior of an ideal, multi-GW battery system.
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- Award ID(s):
- 1935389
- PAR ID:
- 10477030
- Editor(s):
- Andrea Serrani
- Publisher / Repository:
- IEEE Transactions on Control Systems Technology
- Date Published:
- Journal Name:
- IEEE Transactions on Control Systems Technology
- Edition / Version:
- 1
- Volume:
- 31
- Issue:
- 4
- ISSN:
- 1063-6536
- Page Range / eLocation ID:
- 1830 to 1843
- Subject(s) / Keyword(s):
- Demand Dispatch Power Systems
- Format(s):
- Medium: X Size: 1.3MB Other: pdf
- Size(s):
- 1.3MB
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/TCST.2023.3245287
