860 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
COHORT: Coordination of Heterogeneous Thermostatically Controlled Loads for Demand Flexibility
Demand flexibility is increasingly important for power grids. Careful
coordination of thermostatically controlled loads (TCLs) can modulate energy
demand, decrease operating costs, and increase grid resiliency. We propose a
novel distributed control framework for the Coordination Of HeterOgeneous
Residential Thermostatically controlled loads (COHORT). COHORT is a practical,
scalable, and versatile solution that coordinates a population of TCLs to
jointly optimize a grid-level objective, while satisfying each TCL's end-use
requirements and operational constraints. To achieve that, we decompose the
grid-scale problem into subproblems and coordinate their solutions to find the
global optimum using the alternating direction method of multipliers (ADMM).
The TCLs' local problems are distributed to and computed in parallel at each
TCL, making COHORT highly scalable and privacy-preserving. While each TCL poses
combinatorial and non-convex constraints, we characterize these constraints as
a convex set through relaxation, thereby making COHORT computationally viable
over long planning horizons. After coordination, each TCL is responsible for
its own control and tracks the agreed-upon power trajectory with its preferred
strategy. In this work, we translate continuous power back to discrete on/off
actuation, using pulse width modulation. COHORT is generalizable to a wide
range of grid objectives, which we demonstrate through three distinct use
cases: generation following, minimizing ramping, and peak load curtailment. In
a notable experiment, we validated our approach through a hardware-in-the-loop
simulation, including a real-world air conditioner (AC) controlled via a smart
thermostat, and simulated instances of ACs modeled after real-world data
traces. During the 15-day experimental period, COHORT reduced daily peak loads
by an average of 12.5% and maintained comfortable temperatures.Comment: Accepted to ACM BuildSys 2020; 10 page
From Packet to Power Switching: Digital Direct Load Scheduling
At present, the power grid has tight control over its dispatchable generation
capacity but a very coarse control on the demand. Energy consumers are shielded
from making price-aware decisions, which degrades the efficiency of the market.
This state of affairs tends to favor fossil fuel generation over renewable
sources. Because of the technological difficulties of storing electric energy,
the quest for mechanisms that would make the demand for electricity
controllable on a day-to-day basis is gaining prominence. The goal of this
paper is to provide one such mechanisms, which we call Digital Direct Load
Scheduling (DDLS). DDLS is a direct load control mechanism in which we unbundle
individual requests for energy and digitize them so that they can be
automatically scheduled in a cellular architecture. Specifically, rather than
storing energy or interrupting the job of appliances, we choose to hold
requests for energy in queues and optimize the service time of individual
appliances belonging to a broad class which we refer to as "deferrable loads".
The function of each neighborhood scheduler is to optimize the time at which
these appliances start to function. This process is intended to shape the
aggregate load profile of the neighborhood so as to optimize an objective
function which incorporates the spot price of energy, and also allows
distributed energy resources to supply part of the generation dynamically.Comment: Accepted by the IEEE journal of Selected Areas in Communications
(JSAC): Smart Grid Communications series, to appea
Incentive Design for Direct Load Control Programs
We study the problem of optimal incentive design for voluntary participation
of electricity customers in a Direct Load Scheduling (DLS) program, a new form
of Direct Load Control (DLC) based on a three way communication protocol
between customers, embedded controls in flexible appliances, and the central
entity in charge of the program. Participation decisions are made in real-time
on an event-based basis, with every customer that needs to use a flexible
appliance considering whether to join the program given current incentives.
Customers have different interpretations of the level of risk associated with
committing to pass over the control over the consumption schedule of their
devices to an operator, and these risk levels are only privately known. The
operator maximizes his expected profit of operating the DLS program by posting
the right participation incentives for different appliance types, in a publicly
available and dynamically updated table. Customers are then faced with the
dynamic decision making problem of whether to take the incentives and
participate or not. We define an optimization framework to determine the
profit-maximizing incentives for the operator. In doing so, we also investigate
the utility that the operator expects to gain from recruiting different types
of devices. These utilities also provide an upper-bound on the benefits that
can be attained from any type of demand response program.Comment: 51st Annual Allerton Conference on Communication, Control, and
Computing, 201
Demand response from thermostatically controlled loads: modelling, control and system-level value
The research area of this thesis concerns the efficient and secure operation of the future low-carbon power system, where alternative sources of control and flexibility will progressively replace the traditional providers of ancillary services i.e. conventional generators. Various options are engaged in this challenge and suit the innovative concept of Smart Grid. Specifically, this thesis investigates the potential of demand side response support by means of thermostatically controlled loads (TCLs).
This thesis aims to quantify the impact that a population of thermostatically controlled loads has on the commitment and dispatch of a future power system characterized by a large penetration of renewable energy sources (e.g. wind) that are variable and intermittent. Thanks to their relative insensitivity to temperature fluctuations, thermostatic loads would be able to provide frequency response services and other forms of system services, such as energy arbitrage and congestion relief. These actions in turn enhance the power system operation and support the strict compliance with system security standards.
However, the achievement of this transition requires addressing two challenges. The first deals with the design of accurate device models. Significant differences affect the devices’ design included in the same class, leading to different system-level performances. In addition, the flexibility associated to TCLs would be handled more easily by means of models that describes the TCLs dynamics directly as a cluster rather than considering the appliances individually. Second, it is not straightforward achieving satisfactory controllability of a cluster of TCLs for the considered applications. The complexity lies in the typical operation of these devices that has only two power states (on and off) whereas the desired response is continuous. Moreover the control strategy has always to comply with strict device-level temperature constraints as the provision of ancillary services cannot affect the quality of the service of the primary function of TCLs.
This thesis addresses the challenges exhibited. Detailed thermal dynamic models are derived for eight classes of domestic and commercial refrigeration units. In addition, a heterogeneous population of TCLs is modelled as a leaky storage unit; this unit describes the aggregate flexibility of a large population of TCLs as a single storage unit incorporating the devices’ physical thermal models and their operational temperature limits. The control problem is solved by means of an initial hybrid controller for frequency response purposes that is afterwards replaced by an advanced controller for various applications. Provided these two elements, a novel demand side response model is designed considering the simultaneous provision of a number of system services and taking into account the effect of the load energy recovery. The model, included in a stochastic scheduling routine, quantifies the system-level operational cost and wind curtailment savings enabled by the TCLs support.Open Acces
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