Tapping the energy storage potential in electric loads to deliver load following and regulation, with application to wind energy

(1966). Mathematical Theory of Reliability. Journal of the Operational Research Society: Vol. 17, No. 2, pp. 213-215.

https://link.springer.com/content/pdf/10.1057%2Fjors.1966.43.pdf

Mathematical Theory of Reliability

This paper explores methods to coordinate aggregations of thermostatically controlled loads (TCLs; including air conditioners and refrigerators) to manage frequency and energy imbalances in power systems. We focus on opportunities to centrally control loads with high accuracy but low requirements for sensing and communications infrastructure. We compare cases when measured load state information (e.g., power consumption and temperature) is 1) available in real time; 2) available, but not in real time; and 3) not available. We use Markov chain models to describe the temperature state evolution of populations of TCLs, and Kalman filtering for both state and joint parameter/state estimation. A look-ahead proportional controller broadcasts control signals to all TCLs, which always remain in their temperature dead-band. Simulations indicate that it is possible to achieve power tracking RMS errors in the range of 0.26%-9.3% of steady state aggregated power consumption. We also report results in terms of the generator compliance threshold which is commonly used in industry. Results depend upon the information available for system identification, state estimation, and control. Depending upon the performance required, TCLs may not need to provide state information to the central controller in real time or at all.

State Estimation and Control of Electric Loads to Manage Real-Time Energy Imbalance

This paper presents mathematical optimization models of residential energy hubs which can be readily incorporated into automated decision making technologies in smart grids, and can be solved efficiently in a real-time frame to optimally control all major residential energy loads, storage and production components while properly considering the customer preferences and comfort level. Novel mathematical models for major household demand, i.e., fridge, freezer, dishwasher, washer and dryer, stove, water heater, hot tub, and pool pumps are formulated. Also, mathematical models of other components of a residential energy system including lighting, heating, and air-conditioning are developed, and generic models for solar PV panels and energy storage/generation devices are proposed. The developed mathematical models result in Mixed Integer Linear Programming (MILP) optimization problems with the objective functions of minimizing energy consumption, total cost of electricity and gas, emissions, peak load, and/or any combination of these objectives, while considering end-user preferences. Several realistic case studies are carried out to examine the performance of the mathematical model, and experimental tests are carried out to find practical procedures to determine the parameters of the model. The application of the proposed model to a real household in Ontario, Canada is presented for various objective functions. The simulation results show that savings of up to 20% on energy costs and 50% on peak demand can be achieved, while maintaining the household owner's desired comfort levels.

Optimal Operation of Residential Energy Hubs in Smart Grids

Statistics: an introduction.

Neuro-adaptive cooperative tracking control of unknown higher-order affine nonlinear systems

Several sequential Preventive Maintenance (PM) models for predetermined PM interval policies currently exist in the literature, however, much less effort has been devoted to age-based policies. The purpose of this paper is to develop a hybrid age-based model for imperfect PM involving maintainable and non-maintainable failure modes. The proposed hybrid model incorporates adjustment factors in both the hazard rate and effective age. PM is assumed to be imperfect. It reduces the age of the system and changes its hazard rate. The system undergoes a certain number of such PM actions before replacement. The problem is to determine the number of PM actions and the length of PM intervals that minimize the total long-term expected cost per unit time. Model analysis relating to the existence and uniqueness of optimal solutions is provided. Numerical examples are presented for illustrative purposes.

Age-based hybrid model for imperfect preventive maintenance

This paper is concerned with the design of a distributed cooperative synchronisation controller for a class of higher-order nonlinear multi-agent systems. The objective is to achieve synchronisatio...

Neuro-adaptive cooperative tracking control with prescribed performance of unknown higher-order nonlinear multi-agent systems

Economic production lot-sizing for an unreliable machine under imperfect age-based maintenance policy

This paper proposes an adaptive tracking control with prescribed performance function for distributive cooperative control of highly nonlinear multi-agent systems. The use of such approach confines the tracking error within a large predefined set to a predefined smaller set. The key idea is to transform the constrained system into unconstrained one through the transformation of the output error. Agents’ dynamics are assumed unknown, and the controller is developed for a strongly connected structured network. The proposed controller allows all agents to follow the trajectory of the leader node, while satisfying the necessary dynamic requirements. The proposed approach guarantees uniform ultimate boundedness for the transformed error as well as a bounded adaptive estimate of the unknown parameters and dynamics. Simulations include two examples to validate the robustness and smoothness of the proposed controller against highly nonlinear heterogeneous multi-agent system with uncertain time-variant parameters and external disturbances.

Sami El-Ferik

Papers

Neuro-adaptive cooperative tracking control of unknown higher-order affine nonlinear systems

Age-based hybrid model for imperfect preventive maintenance

Neuro-adaptive cooperative tracking control with prescribed performance of unknown higher-order nonlinear multi-agent systems

Economic production lot-sizing for an unreliable machine under imperfect age-based maintenance policy

Adaptive synchronisation of unknown nonlinear networked systems with prescribed performance