A stochastic computer model for heating and cooling loads
TL;DR: In this article, the authors review the concept of demand-side management, particularly in regard to utility intervention into the setpoint adjustment of customers' thermostats for heating and cooling loads.
Abstract: The authors review the concept of demand-side management, particularly in regard to utility intervention into the setpoint adjustment of customers' thermostats for heating and/or cooling loads. As part of a larger effort to develop a large simulation to evaluate performance of various management strategies, they have created a simple, realistic, easily implementable model for the temperature of a house having a heater/air-conditioner which is regulated by a thermostat and operates in an environment that contains random elements. Two models previously given in the literature are reviewed before giving the details of the model, the feature of which is that it is a stochastic model operating in discrete time. Computer results show good agreement with basic physical principles, and suggest that the probability distributions of on-time and off-time are negative binomial. It is concluded that this model will provide a useful tool in the evaluation of load-management strategies. >
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TL;DR: In this paper, the authors develop new methods to model and control the aggregated power demand from a population of thermostatically controlled loads, with the goal of delivering services such as regulation and load following.
770 citations
01 Dec 2011
TL;DR: In this article, the available literature on demand response (DR) is categorized into general concept papers and papers on DR models applicable to the wholesale or retail markets, and are presented in a precise manner.
Abstract: Demand response (DR) has an important role to play in the electricity market for maintaining the balance between supply and demand by introducing load flexibility instead of only adjusting generation levels, at almost all operational time scales. There are many players in the market who benefit from DR, like the TSO, DSOs, retailers and end-customers themselves. The recent advent of smart grid technologies advanced the integration of DR by providing the needed information and communication infrastructure to the existing grid. Available literature on DR talks about the concept and definitions of DR, possible DR models for various region-specific market structures along with few DR implementation experiences in a system with ever increasing levels of loads along with evolution of innovative technologies like renewables, micro-grids, PEVs, etc. In this paper, the available literature on DR is categorized into general concept papers and papers on DR models applicable to the wholesale or retail markets, and are presented in a precise manner.
323 citations
Cites background from "A stochastic computer model for hea..."
...Reference [61] talks about a discrete time continuous state stochastic model of the temperature of a house having AC/heater regulated by a thermostat....
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TL;DR: In this article, the authors present the development of physical-based residential load models at the appliance level, i.e., space cooling/space heating, water heater, clothes dryer and electric vehicle.
Abstract: In order to support the growing interest in demand response (DR) modeling and analysis, there is a need for physical-based residential load models. The objective of this paper is to present the development of such load models at the appliance level. These include conventional controllable loads, i.e., space cooling/space heating, water heater, clothes dryer and electric vehicle. Validation of the appliance-level load models is carried out by comparing the models' output with the real electricity consumption data for the associated appliances. The appliance-level load models are aggregated to generate load profiles for a distribution circuit, which are validated against the load profiles of an actual distribution circuit. The DR-sensitive load models can be used to study changes in electricity consumption both at the household and the distribution circuit levels, given a set of customer behaviors and/or signals from a utility.
261 citations
Cites background from "A stochastic computer model for hea..."
...In order to study demand management, published work has focused on physical-based load models, especially on heating, ventilation, and air conditioning (HVAC) loads and water heating loads [3]–[7]....
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TL;DR: In this paper, the authors developed a new framework for designing and assessing such an advanced direct load control program with the objective of minimizing end-user discomfort and is formulated as an optimization problem.
Abstract: The advent of advanced sensor technology and the breakthroughs in telecommunication open up several new possibilities for demand-side management. More recently, there has been greater interest from utilities as well as system operators in utilizing load as a system resource through the application of new technologies. With the wider application of demand-side management, there is an increasing emphasis on control of loads with minimum disruption. This paper develops a new framework for designing as well as assessing such an advanced direct load control program with the objective of minimizing end-user discomfort and is formulated as an optimization problem. With a fairly general setup for demand-side management, a simulation-based framework is developed for the stochastic optimization problem. Next, using this framework, insights into the effect of different parameters and constraints in the model on load control are developed.
258 citations
Cites methods from "A stochastic computer model for hea..."
...This model when converted to a sample-data form as in [17] results in the following solution for the difference equation:...
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TL;DR: A linearized model of the response is derived, and a linear quadratic regulator (LQR) has been designed that enables aggregate power to track reference signals that exhibit step, ramp and sinusoidal variations.
Abstract: As the penetration of intermittent energy sources grows substantially, loads will be required to play an increasingly important role in compensating the fast time-scale fluctuations in generated power. Recent numerical modeling of thermostatically controlled loads (TCLs) has demonstrated that such load following is feasible, but analytical models that satisfactorily quantify the aggregate power consumption of a group of TCLs are desired to enable controller design. We develop such a model for the aggregate power response of a homogeneous population of TCLs to uniform variation of all TCL setpoints. A linearized model of the response is derived, and a linear quadratic regulator (LQR) has been designed. Using the TCL setpoint as the control input, the LQR enables aggregate power to track reference signals that exhibit step, ramp and sinusoidal variations. Although much of the work assumes a homogeneous population of TCLs with deterministic dynamics, we also propose a method for probing the dynamics of systems where load characteristics are not well known.
147 citations
Cites background from "A stochastic computer model for hea..."
...In [5], a discrete-time model of the dynamics of the temperatures of individual thermostats was derived, assuming no external random influence....
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References
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TL;DR: The paper reviews the progress of research on parameter estimation for continuous-time models of dynamic systems over the period 1958-1980 and includes a classification system which conforms as closely as possible to that which has arisen naturally over the past two decades.
553 citations
TL;DR: In this article, a statistical approach is used to model the dynamics of the electric demand of large aggregates of electric space heaters or air conditioners, and the homogeneons group aggregrate load model is a system of coupled ordinary, and partial differential equations (Fokker-Planck equations).
Abstract: A statistical approach is used to model the dynamics of the electric demand of large aggregates of electric space heaters or air conditioners. The importance of such loads is twofold. First, they account for a significant portion of power system dynamics following a power outage. Second, because they are associated with energy storage, they are often selected for load shedding within a load management program. The derivation of the aggregate electrical dynamics is considered first for a homogeneous group of devices. Subsequently, a perturbation analysis yields the dynamics for a nonhomogeneous group. The homogeneons group aggregrate load model is a system of coupled ordinary, and partial differential equations (Fokker-Planck equations). It is obtained by writing evolution equations for the probability density of a hybrid-state Markov system used to model the switching dynamics of individual devices. This result is new and could give a clue to the analysis of a broad class of hybrid-state stochastic systems. In turn, this could provide a new impetus not only in the area of electric load modeling but other areas such as power system reliability and the design of relay control systems, where stochastic hybrid-state models occur frequently. Simulation results which illustrate the dynamical properties of the model are presented.
320 citations
TL;DR: In this paper, a general, physically based, probabilistic model of power system load has been developed for short-term prediction of system demand by composition, and accounts for lifestyle dependency and weather dependency as well as effects of other exogenous processes.
Abstract: A general, physically based, probabilistic model of power system load has been developed [1]. The model is suitable for short-term prediction of system demand by composition, and accounts for lifestyle dependency and weather dependency as well as effects of other exogenous processes. The conceptual framework and notation applicable to a wide range of load modeling problems have been the key issues in developing a general model.
276 citations
TL;DR: In this paper, the authors introduce the engineer to the area of stochastic differential equations, and point out the mathematical techniques and pitfalls in this area Topics discussed include continuous-time Markov processes, the Fokker-Planck-Kolmogorov equations, the Ito and Stratonovich stochastically calculi, and the problem of modeling physical systems.
Abstract: The purpose of this report is to introduce the engineer to the area of stochastic differential equations, and to point out the mathematical techniques and pitfalls in this area Topics discussed include continuous-time Markov processes, the Fokker-Planck-Kolmogorov equations, the Ito and Stratonovich stochastic calculi, and the problem of modeling physical systems
138 citations
01 Oct 1985
TL;DR: An overview of DSM alternatives can be found in this article, where the authors provide a historical reference and an understanding of the types of needs DSM can address and the benefits they can provide.
Abstract: This paper provides an overview of demand-side management (DSM) alternatives. It covers the general state of the art, projected developments, and the application of DSM alternatives. It starts with a background discussion of DSM which provides the reader with a historical reference and an understanding of the types of needs DSM alternatives can address and the benefits they can provide. Categories of DSM alternatives are then described. General design, application, and issues involved are discussed. Although it is not possible to discuss DSM alternatives in complete detail, specific information based on actual installations is presented. Also, typical values, costs, and load impacts are given in most cases.
55 citations