scholarly journals Automated Scheduling of Household Appliances Using Predictive Mixed Integer Programming

2019 ◽  
Author(s):  
Himanshu Nagpal ◽  
Andrea Staino ◽  
Biswajit Basu
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Peak Power ◽  
Mixed Integer ◽  
Consumption Pattern ◽  
Problem Model ◽  
Household Appliances ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Peak Power Consumption

In this work, an algorithm for the scheduling of household appliances to reduce the energy cost and the peak-power consumption is proposed. The system architecture of a home energy management system (HEMS) is presented to operate the appliances. The dynamics of thermal and non-thermal appliances is represented into state-space model to formulate the scheduling task into a mixed-integer-linear-programming (MILP) optimization problem. Model predictive control (MPC) strategy is used to operate the appliances in real-time. The HEMS schedules the appliances in a dynamic manner without any a priori knowledge of the load-consumption pattern. At the same time, HEMS responds to the real-time electricity market and the external environmental conditions (solar radiation, ambient temperature etc). Simulation results exhibit the benefits of proposed HEMS by showing the reduction of up to 47% in electricity cost and up to 48% in peak power consumption.

scholarly journals Application of Predictive Control in Scheduling of Domestic Appliances

2020 ◽  
Vol 10 (5) ◽  
pp. 1627 ◽  
Author(s):  
Himanshu Nagpal ◽  
Andrea Staino ◽  
Biswajit Basu
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Predictive Control ◽  
Peak Power ◽  
Mixed Integer ◽  
Consumption Pattern ◽  
Problem Model ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Peak Power Consumption

In this work, an algorithm for the scheduling of household appliances to reduce the energy cost and the peak-power consumption is proposed. The system architecture of a home energy management system (HEMS) is presented to operate the appliances. The dynamics of thermal and non-thermal appliances is represented into state-space model to formulate the scheduling task into a mixed-integer-linear-programming (MILP) optimization problem. Model predictive control (MPC) strategy is used to operate the appliances in real-time. The HEMS schedules the appliances in dynamic manner without any a priori knowledge of the load-consumption pattern. At the same time, the HEMS responds to the real-time electricity market and the external environmental conditions (solar radiation, ambient temperature, etc.). Simulation results exhibit the benefits of the proposed HEMS by showing the reduction of up to 70% in electricity cost and up to 57% in peak power consumption.

Operation Scheduling of Household Load, EV and BESS Using Real Time Pricing, Incentive Based DR and Peak Power Limiting Strategy

2018 ◽  
Vol 20 (1) ◽  
Author(s):  
Sandeep Kakran ◽  
Saurabh Chanana
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Cost Reduction ◽  
Management System ◽  
Peak Power ◽  
Base Case ◽  
Energy Management System ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Home Energy Management System

Abstract Demand response (DR) programs have become powerful tools of the smart grids, which provide opportunities for the end-use consumers to participate actively in the energy management programs. This paper investigates impact of different DR strategies in a home-energy management system having consumer with regular load, electric vehicle (EV) and battery-energy storage system (BESS) in the home. The EV is considered as a special type of load, which can also work as an electricity generation source by discharging the power in vehicle-to-home mode during high price time. BESS and a small renewable energy source in form of rooftop photovoltaic panels give a significant contribution in the energy management of the system. As the main contribution to the literature, a mixed integer linear programming based model of home energy management system is formulated to minimize the daily cost of electricity consumption under the effect of different DR programs; such as real time price based DR program, incentive based DR program and peak power limiting DR program. Finally, total electricity prices are analysed in the case studies by including different preferences of the household consumer under mentioned DR programs. A total of 26.93 % electricity cost reduction is noticed with respect to base case, without peak limiting DR and 19.93 % electricity cost reduction is noticed with respect to base case, with peak limiting DR.

scholarly journals Energy Optimization in Smart Urban Buildings Using Bio-Inspired Ant Colony Optimization

2021 ◽  
Author(s):  
Fakhri Alam Khan ◽  
Kifayat Ullah ◽  
Atta ur Rahman ◽  
Sajid Anwar
Keyword(s):  
Ant Colony Optimization ◽  
Real Time ◽  
Energy Management ◽  
Management System ◽  
Ant Colony ◽  
Consumption Pattern ◽  
Energy Management System ◽  
Electricity Cost ◽  
Home Appliances ◽  
Home Energy Management

Abstract Instead of planting new electricity generation units, there is a need to design an efficient energy management system to achieve a normalized trend of power consumption. Smart grid has been evolved as a solution, where Demand Response (DR) strategy is used to modify the nature of demand of consumer. In return, utility pay incentives to the consumer. The increasing load demand in residential area and irregular electricity load profile have encouraged us to propose an efficient Home Energy Management System (HEMS) for optimal scheduling of home appliances. In order to meet the electricity demand of the consumers, the energy consumption pattern of a consumer is maintained through scheduling the appliances in day-ahead and real-time bases. In this paper we propose a hybrid algorithm Bacterial foraging Ant colony optimization is proposed (HB-ACO) which contain both BFA and ACO properties. Primary objectives of scheduling is to shift load from On-peak hour to Off-peak hours to reduce electricity cost and peak to average ratio. A comparison of these algorithms is also presented in terms of performance parameters electricity cost, reduction of PAR and user comfort in term of waiting time. The proposed techniques are evaluated using two pricing scheme time of use and critical peak pricing. The HB-ACO shows better performance as compared to ACO and BFA which is evident from the simulation results Moreover the concept of coordination among home appliances is presented for real time scheduling. We consider this is knapsack problem and solve it through Ant colony optimization algorithm.

scholarly journals Planning of a distributed integrated cooling system in reducing the peak power consumption

2021 ◽  
Vol 7 ◽  
pp. 458-468
Author(s):  
Dongwen Chen ◽  
Xiao Hu ◽  
Yong Li ◽  
Jingcheng Chen ◽  
Ruzhu Wang
Keyword(s):  
Power Consumption ◽  
Peak Power ◽  
Cooling System ◽  
Peak Power Consumption

Flow shop scheduling with peak power consumption constraints

2013 ◽  
Vol 206 (1) ◽  
pp. 115-145 ◽  
Author(s):  
Kan Fang ◽  
Nelson A. Uhan ◽  
Fu Zhao ◽  
John W. Sutherland
Keyword(s):  
Power Consumption ◽  
Peak Power ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Shop Scheduling ◽  
Peak Power Consumption ◽  
Consumption Constraints

WEIGHTED AUTOMATA AND REGULAR EXPRESSIONS OVER VALUATION MONOIDS

2011 ◽  
Vol 22 (08) ◽  
pp. 1829-1844 ◽  
Author(s):  
MANFRED DROSTE ◽  
INGMAR MEINECKE
Keyword(s):  
Power Consumption ◽  
Average Cost ◽  
Peak Power ◽  
Regular Expressions ◽  
Infinite Words ◽  
New Class ◽  
Weighted Automata ◽  
Peak Power Consumption ◽  
Weight Structures

Quantitative aspects of systems like consumption of resources, output of goods, or reliability can be modeled by weighted automata. Recently, objectives like the average cost or the longtime peak power consumption of a system have been modeled by weighted automata which are not semiring weighted anymore. Instead, operations like limit superior, limit average, or discounting are used to determine the behavior of these automata. Here, we introduce a new class of weight structures subsuming a range of these models as well as semirings. Our main result shows that such weighted automata and Kleene-type regular expressions are expressively equivalent both for finite and infinite words.

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