135 research outputs found
Improved Battery Models of an Aggregation of Thermostatically Controlled Loads for Frequency Regulation
Recently it has been shown that an aggregation of Thermostatically Controlled
Loads (TCLs) can be utilized to provide fast regulating reserve service for
power grids and the behavior of the aggregation can be captured by a stochastic
battery with dissipation. In this paper, we address two practical issues
associated with the proposed battery model. First, we address clustering of a
heterogeneous collection and show that by finding the optimal dissipation
parameter for a given collection, one can divide these units into few clusters
and improve the overall battery model. Second, we analytically characterize the
impact of imposing a no-short-cycling requirement on TCLs as constraints on the
ramping rate of the regulation signal. We support our theorems by providing
simulation results.Comment: to appear in the 2014 American Control Conference - AC
Optimal Ensemble Control of Loads in Distribution Grids with Network Constraints
Flexible loads, e.g. thermostatically controlled loads (TCLs), are
technically feasible to participate in demand response (DR) programs. On the
other hand, there is a number of challenges that need to be resolved before it
can be implemented in practice en masse. First, individual TCLs must be
aggregated and operated in sync to scale DR benefits. Second, the uncertainty
of TCLs needs to be accounted for. Third, exercising the flexibility of TCLs
needs to be coordinated with distribution system operations to avoid
unnecessary power losses and compliance with power flow and voltage limits.
This paper addresses these challenges. We propose a network-constrained,
open-loop, stochastic optimal control formulation. The first part of this
formulation represents ensembles of collocated TCLs modelled by an aggregated
Markov Process (MP), where each MP state is associated with a given power
consumption or production level. The second part extends MPs to a multi-period
distribution power flow optimization. In this optimization, the control of TCL
ensembles is regulated by transition probability matrices and physically
enabled by local active and reactive power controls at TCL locations. The
optimization is solved with a Spatio-Temporal Dual Decomposition (ST-D2)
algorithm. The performance of the proposed formulation and algorithm is
demonstrated on the IEEE 33-bus distribution model.Comment: 7 pages, 6 figures, accepted PSCC 201
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