The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform

Alton D. Patton - One of the best experts on this subject based on the ideXlab platform.

  • A production costing methodology for evaluation of Direct Load Control
    IEEE Transactions on Power Systems, 1991
    Co-Authors: Hossein Salehfar, Alton D. Patton
    Abstract:

    Direct Load Control (DLC) is a form of Load management in which portions of the system Load are under the Direct operational Control of the utility. Thus, the Load can be modified, within limits, to match the available generating capacity, thereby minimizing events of unControlled Load loss. It is shown that operating cost reductions produced by exogeneous models of DLC are different from those produced by dynamic models of DLC. The dynamics of DLC and an equal incremental cost scheme are described and then coupled with a Monte Carlo simulation model of the operation of thermal-based electric utilities. Various production cost measures produced by exogeneous and dynamic models of DLC are presented and discussed.

  • Effects of Direct Load Control on power system reliability and production cost
    1990
    Co-Authors: Hossein Salehfar, Alton D. Patton
    Abstract:

    It is no longer advantageous for electric utilities to encourage and serve unControlled Load growth. Thus, the concept of Load Management has become important and is increasingly practiced in various forms as an alternative to or in conjunction with system capacity additions to satisfy Load requirements. Accordingly, a need exists for accurate and efficient methods which incorporate Load Management to assess and evaluate the effects of Load Control in context with system supply-side variables. Direct Load Control is a form of Load Management in which portions of the system Load are under the Direct operational Control of the utility. Thus, the Load can be modified, within limits, to match the available generating capacity thereby minimizing events of unControlled Load loss. In this research, it is shown that system reliability improvements and operating cost reductions afforded by exogenous models of Direct Load Control are different from those given by dynamic models of Direct Load Control. To this end, this research report describes the dynamics of Direct Load Control and an equal incremental cost scheme coupled with a Monte Carlo simulation model of the operation of thermal based electric utilities. Various system reliability indices and production measures produced by exogenous and dynamic models of Direct Load Control are computed, compared and discussed. It is shown that accurate modeling of Direct Load Control can not be made using exogenous Load models, but requires models which recognize the dynamics of operation and the temporal correlation of Load and available generating capacity.

Claire J Tomlin - One of the best experts on this subject based on the ideXlab platform.

  • risk limiting dynamic contracts for Direct Load Control
    arXiv: Optimization and Control, 2014
    Co-Authors: Insoon Yang, Duncan S Callaway, Claire J Tomlin
    Abstract:

    This paper proposes a novel continuous-time dynamic contract framework that has a risk-limiting capability. If a principal and an agent enter into such a contract, the principal can optimally manage its performance and risk with a guarantee that the agent's risk is less than or equal to a pre-specified level and that the agent's expected payoff is greater than or equal to another pre-specified threshold. We achieve such risk-management capabilities by formulating the contract design problem as mean-variance constrained risk-sensitive Control. A dynamic programming-based method is developed to solve the problem. The key idea of our proposed solution method is to reformulate the inequality constraints on the mean and the variance of the agent's payoff as dynamical system constraints by introducing new state and Control variables. The reformulations use the martingale representation theorem. The proposed contract method enables us to develop a new Direct Load Control method that provides the Load-serving entity with financial risk management solutions in real-time electricity markets. We also propose an approximate decomposition of the optimal contract design problem for multiple customers into multiple low-dimensional contract problems for one customer. This allows the Direct Load Control program to work with a large number of customers without any scalability issues. Furthermore, the contract design procedure can be completely parallelized. The performance and usefulness of the proposed contract method and its application to Direct Load Control are demonstrated using data on the electric energy consumption of customers in Austin, Texas as well as the Electricity Reliability Council of Texas' locational marginal price data.

  • Allerton - Direct Load Control for electricity market risk management via risk-limiting dynamic contracts
    2014 52nd Annual Allerton Conference on Communication Control and Computing (Allerton), 2014
    Co-Authors: Insoon Yang, Duncan S Callaway, Claire J Tomlin
    Abstract:

    This paper proposes a new Direct Load Control framework that provides financial risk management solutions for real-time electricity markets. In this program, a Load-serving entity makes risk-limiting dynamic contracts with its customers to optimally manage its revenue and risk. This risk is generated by both price volatility and demand uncertainty regarding distributed renewable generation as negative Load. The key feature of our contract method is its risk-limiting capability: the amount of risk transferred to each customer is less than or equal to a pre-specified threshold. This is achieved by formulating the contract design problem as mean-variance constrained risk-sensitive Control. We develop a dynamic programming-based solution approach. We demonstrate the performance of the proposed contracts by using locational marginal price (LMP) data from the Electricity Reliability Council of Texas and data on the electric energy consumption of customers in Austin, Texas. The numerical experiments suggest that the proposed Direct Load Control program efficiently manages the Load-serving entity's and its customers' risks even when the Load-serving entity passes the wholesale electricity price to the customers.

  • Direct Load Control for electricity market risk management via risk-limiting dynamic contracts
    2014 52nd Annual Allerton Conference on Communication Control and Computing (Allerton), 2014
    Co-Authors: Insoon Yang, Duncan S Callaway, Claire J Tomlin
    Abstract:

    This paper proposes a new Direct Load Control framework that provides financial risk management solutions for real-time electricity markets. In this program, a Load-serving entity makes risk-limiting dynamic contracts with its customers to optimally manage its revenue and risk. This risk is generated by both price volatility and demand uncertainty regarding distributed renewable generation as negative Load. The key feature of our contract method is its risk-limiting capability: the amount of risk transferred to each customer is less than or equal to a pre-specified threshold. This is achieved by formulating the contract design problem as mean-variance constrained risk-sensitive Control. We develop a dynamic programming-based solution approach. We demonstrate the performance of the proposed contracts by using locational marginal price (LMP) data from the Electricity Reliability Council of Texas and data on the electric energy consumption of customers in Austin, Texas. The numerical experiments suggest that the proposed Direct Load Control program efficiently manages the Load-serving entity's and its customers' risks even when the Load-serving entity passes the wholesale electricity price to the customers.

Haider A F Almurib - One of the best experts on this subject based on the ideXlab platform.

  • Load Shedding and Smart-Direct Load Control Using Internet of Things in Smart Grid Demand Response Management
    IEEE Transactions on Industry Applications, 2017
    Co-Authors: H. Mortaji, Siew Hock Ow, Mahmoud Moghavvemi, Haider A F Almurib
    Abstract:

    IEEE This paper proposes the use of a novel algorithm for smart Direct Load Control and Load shedding to minimize power outages in sudden grid Load changes and reduce the Peak-to-Average Ratio (PAR). The algorithm utilizes forecasting, shedding, and smart Direct Load Control. It also uses the Internet of Things and stream analytics to provide real-time Load Control, and generates a daily schedule for customers & #x0027; equipped with Intelligent Electronic Device (IED)s, based on their demands, thermal comfort, and the forecasted Load model. The demand response techniques are utilized for real time Load Control and optimization. To test the algorithm, a simulation system was developed, which takes into account one-hundred customers owning randomly selected appliances. The results indicated that Load shedding using ARIMA time series prediction model and applying smart Direct Load Control (S-DLC) and Internet of Things can significantly reduce customers & #x0027; power outage.

  • IAS Annual Meeting - Smart grid demand response management using internet of things for Load shedding and smart-Direct Load Control
    2016 IEEE Industry Applications Society Annual Meeting, 2016
    Co-Authors: H. Mortaji, O.s. Hock, Mahmoud Moghavvemi, Haider A F Almurib
    Abstract:

    This paper proposes the use of a novel algorithm for smart Direct Load Control and Load shedding to minimize the power outage in sudden grid Load changes, as well as reduce the Peak-to-Average Ratio (PAR). The algorithm uses forecasting, shedding, and smart Direct Load Control. The algorithm also uses the Internet of Things and stream analytics to provide real-time Load Control, and generates a daily schedule for customers' equipped with IEDs, based on their demands, comfort, and the forecasted Load model. The demand response techniques are utilized for real time Load Control and optimization. To test the algorithm, a simulation system was developed that takes into account one hundred customers owning randomly selected appliances. The results indicated that Load shedding using ARIMA time series prediction model and applying smart Direct Load Control (S-DLC) and Internet of Things can remarkably reduce customers' power outage.

  • Smart grid demand response management using internet of things for Load shedding and smart-Direct Load Control
    IEEE Industry Application Society 52nd Annual Meeting: IAS 2016, 2016
    Co-Authors: H. Mortaji, O.s. Hock, Mahmoud Moghavvemi, Haider A F Almurib
    Abstract:

    © 2016 IEEE.This paper proposes the use of a novel algorithm for smart Direct Load Control and Load shedding to minimize the power outage in sudden grid Load changes, as well as reduce the Peak-to-Average Ratio (PAR). The algorithm uses forecasting, shedding, and smart Direct Load Control. The algorithm also uses the Internet of Things and stream analytics to provide real-time Load Control, and generates a daily schedule for customers' equipped with IEDs, based on their demands, comfort, and the forecasted Load model. The demand response techniques are utilized for real time Load Control and optimization. To test the algorithm, a simulation system was developed that takes into account one hundred customers owning randomly selected appliances. The results indicated that Load shedding using ARIMA time series prediction model and applying smart Direct Load Control (S-DLC) and Internet of Things can remarkably reduce customers' power outage.

Christhina Candido - One of the best experts on this subject based on the ideXlab platform.

  • thermal comfort during temperature cycles induced by Direct Load Control strategies of peak electricity demand management
    Building and Environment, 2016
    Co-Authors: Fan Zhang, Richard De Dear, Christhina Candido
    Abstract:

    Direct Load Control (DLC) is a utility-sponsored demand response program which allows a utility to cycle specific appliances on and off during peak demand periods. Direct Load Control of air conditioners induces temperature cycles that might potentially compromise occupants' thermal comfort. In two separate experiments, 56 subjects' thermal comfort was closely examined during 6 DLC conditions and 2 Control conditions simulated in a climate chamber, representing typical DLC-induced thermal environments in university lecture theatres. Results show that half of the DLC conditions were clearly accepted by subjects. Multilevel linear modelling of thermal sensation demonstrates that operative temperature, vapour pressure and the rate of temperature change are the three most important predictors during DLC events. Multilevel logistic regression indicates that in DLC conditions with lower adapting temperatures, thermal acceptability is significantly predicted by air speed and its interaction with operative temperature whereas in DLC conditions with higher adapting temperatures, by air speed, operative temperature and the rate of temperature change. Subjects' thermal comfort zone during DLC events is wider than predicted by Fanger's PMV/PPD model in that the former is more tolerant of cooler temperatures. Results from this study suggest that ASHRAE 55-2013 is overly conservative in defining the limits for temperature cycles, ramps and drifts.

  • Impacts of Direct Load Control Events on Cognitive Performance
    2015
    Co-Authors: Fan Zhang, Richard De Dear, Christhina Candido
    Abstract:

    Direct Load Control (DLC) strategy is one of the most common approaches to cope with peak electricity Loads. Application of DLC in residential and small business buildings has achieved promising results, yet there are few studies on DLC in university educational buildings that are commonly susceptible to large peak Loads and associated penalty tariffs. University students’ learning performance, as represented by four fundamental cognitive skills— memory, concentration, reasoning and planning, was closely examined in a climate chamber during three simulated DLC events and one Control condition. Results reveal that DLC events, generally, do not significantly affect students’ scores across eight cognitive performance tests. In the simulated DLC conditions, cognitive performance was relatively stable or even slightly improved. Results confirm that human cognitive performance can remain near-optimal across a range of temperature. DLC strategies to manage peak electricity Load are clearly feasible in university lecture theatres if DLC algorithms are judiciously designed.

  • Thermal comfort during Direct Load Control events in university lecture theatres
    Indoor Air, 2014
    Co-Authors: Fan Zhang, R. De Dear, Christhina Candido
    Abstract:

    As a common approach to cope with air-conditioning peak demand, Direct Load Control (DLC) strategy has yielded positive results in Australian residential buildings. However, in university lecture theatres with high occupancy density and ventilation rate, thermal comfort impacts of DLC remain unclear. Designbuilder and Energyplus software were used to simulate thermal environments in a typical university lecture theatre during DLC events induced by different cycling schemes and building envelope thermal performance conditions. The analysis explores thermal comfort impacts by applying the PMV/PPD Index and the ASHRAE 55-2013 80% acceptability limit to simulated indoor climates. Results show that for the same DLC event, the ASHRAE adaptive 80% acceptability limit indicates less adverse thermal comfort impacts than the PMV/PPD index. For lecture theatres with poorer envelope thermal performance, DLC algorithms with high cycling levels (≥ 50%) should be avoided since they are very likely to induce unacceptable thermal environments.

Paolo Dini - One of the best experts on this subject based on the ideXlab platform.

  • Optimal Direct Load Control of renewable powered small cells: Performance evaluation and bounds
    2018 IEEE Wireless Communications and Networking Conference (WCNC), 2018
    Co-Authors: Nicola Piovesan, Marco Miozzo, Paolo Dini
    Abstract:

    In this paper, we propose an optimal Direct Load Control of renewable powered small base stations based on Dynamic Programming. The optimization is represented using Graph Theory and the problem is stated as a Shortest Path problem. The proposed optimal algorithm is able to adapt to the varying conditions of renewable energy sources and traffic demands. We analyze the optimal ON/OFF policies considering different energy and traffic scenarios. Then, we evaluate network performance in terms of system drop rate and grid energy consumption. The obtained results are compared with a greedy approach. This study allows to elaborate on the behavior and performance bounds of the system and gives a guidance for approximated policy search methods.

  • WCNC - Optimal Direct Load Control of renewable powered small cells: Performance evaluation and bounds
    2018 IEEE Wireless Communications and Networking Conference (WCNC), 2018
    Co-Authors: Nicola Piovesan, Marco Miozzo, Paolo Dini
    Abstract:

    In this paper, we propose an optimal Direct Load Control of renewable powered small base stations based on Dynamic Programming. The optimization is represented using Graph Theory and the problem is stated as a Shortest Path problem. The proposed optimal algorithm is able to adapt to the varying conditions of renewable energy sources and traffic demands. We analyze the optimal ON/OFF policies considering different energy and traffic scenarios. Then, we evaluate network performance in terms of system drop rate and grid energy consumption. The obtained results are compared with a greedy approach. This study allows to elaborate on the behavior and performance bounds of the system and gives a guidance for approximated policy search methods.