Energy and CO2 efficient scheduling of smart appliances in active houses equipped with batteries

K. Paridari; A. Parisio; Henrik Sandberg; K.H. Johansson

doi:10.1109/CoASE.2014.6899394

Energy and CO2 efficient scheduling of smart appliances in active houses equipped with batteries

K. Paridari, A. Parisio, Henrik Sandberg, K.H. Johansson

EEE - Academic & Research

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we present a novel method for scheduling smart appliances and batteries, in order to reduce both the electricity bill and the CO 2 emissions. Mathematically, the scheduling problem is posed as a multi-objective Mixed Integer Linear Programming (MILP), which can be solved by using standard algorithms. A case study is performed to assess the performance of the proposed scheduling framework. Numerical results show that the new formulation can decrease both the CO 2 emissions and the electricity bill. Furthermore, a survey of studies that deal with scheduling of smart appliances is provided. These papers use methods based on MILP, Dynamic Programming (DP), and Minimum Cut Algorithm (MCA) for solving the scheduling problem. We discuss their performance in terms of computation time and optimality versus time discretization and number of appliances.

Original language	English
Title of host publication	2014 IEEE International Conference on Automation Science and Engineering (CASE)
Place of Publication	Piscataway
Publisher	IEEE
Pages	632-639
Number of pages	8
ISBN (Electronic)	978-1-4799-5283-0
DOIs	https://doi.org/10.1109/CoASE.2014.6899394
Publication status	Published - 30 Oct 2014
Event	Automation Science and Engineering (CASE). IEEE International Conference on - Taipei, Taiwan Duration: 18 Aug 2014 → 22 Aug 2014

Conference

Conference	Automation Science and Engineering (CASE). IEEE International Conference on
Country/Territory	Taiwan
City	Taipei
Period	18/08/14 → 22/08/14

Keywords

domestic appliances
dynamic programming
environmental management
graph theory
integer programming
linear programming
power system economics
scheduling
secondary cells
MILP
active houses
batteries
carbon dioxide efficient scheduling
carbon dioxide emission reduction
electricity bill reduction
energy scheduling
minimum cut algorithm
multiobjective mixed integer linear programming
smart appliances
Automation
Batteries
Electricity
Home appliances
Optimal scheduling
Power demand
Scheduling

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/CoASE.2014.6899394

Cite this

@inproceedings{7c6c7213b1604f19936450649ff4ecf1,

title = "Energy and CO2 efficient scheduling of smart appliances in active houses equipped with batteries",

abstract = "In this paper, we present a novel method for scheduling smart appliances and batteries, in order to reduce both the electricity bill and the CO 2 emissions. Mathematically, the scheduling problem is posed as a multi-objective Mixed Integer Linear Programming (MILP), which can be solved by using standard algorithms. A case study is performed to assess the performance of the proposed scheduling framework. Numerical results show that the new formulation can decrease both the CO 2 emissions and the electricity bill. Furthermore, a survey of studies that deal with scheduling of smart appliances is provided. These papers use methods based on MILP, Dynamic Programming (DP), and Minimum Cut Algorithm (MCA) for solving the scheduling problem. We discuss their performance in terms of computation time and optimality versus time discretization and number of appliances.",

keywords = "domestic appliances, dynamic programming, environmental management, graph theory, integer programming, linear programming, power system economics, scheduling, secondary cells, MILP, active houses, batteries, carbon dioxide efficient scheduling, carbon dioxide emission reduction, electricity bill reduction, energy scheduling, minimum cut algorithm, multiobjective mixed integer linear programming, smart appliances, Automation, Batteries, Electricity, Home appliances, Optimal scheduling, Power demand, Scheduling",

author = "K. Paridari and A. Parisio and Henrik Sandberg and K.H. Johansson",

year = "2014",

month = oct,

day = "30",

doi = "10.1109/CoASE.2014.6899394",

language = "English",

pages = "632--639",

booktitle = "2014 IEEE International Conference on Automation Science and Engineering (CASE)",

publisher = "IEEE",

address = "United States",

note = "Automation Science and Engineering (CASE). IEEE International Conference on ; Conference date: 18-08-2014 Through 22-08-2014",

}

Paridari, K, Parisio, A, Sandberg, H & Johansson, KH 2014, Energy and CO2 efficient scheduling of smart appliances in active houses equipped with batteries. in 2014 IEEE International Conference on Automation Science and Engineering (CASE). IEEE, Piscataway, pp. 632-639, Automation Science and Engineering (CASE). IEEE International Conference on, Taipei, Taiwan, 18/08/14. https://doi.org/10.1109/CoASE.2014.6899394

TY - GEN

T1 - Energy and CO2 efficient scheduling of smart appliances in active houses equipped with batteries

AU - Paridari, K.

AU - Parisio, A.

AU - Sandberg, Henrik

AU - Johansson, K.H.

PY - 2014/10/30

Y1 - 2014/10/30

N2 - In this paper, we present a novel method for scheduling smart appliances and batteries, in order to reduce both the electricity bill and the CO 2 emissions. Mathematically, the scheduling problem is posed as a multi-objective Mixed Integer Linear Programming (MILP), which can be solved by using standard algorithms. A case study is performed to assess the performance of the proposed scheduling framework. Numerical results show that the new formulation can decrease both the CO 2 emissions and the electricity bill. Furthermore, a survey of studies that deal with scheduling of smart appliances is provided. These papers use methods based on MILP, Dynamic Programming (DP), and Minimum Cut Algorithm (MCA) for solving the scheduling problem. We discuss their performance in terms of computation time and optimality versus time discretization and number of appliances.

AB - In this paper, we present a novel method for scheduling smart appliances and batteries, in order to reduce both the electricity bill and the CO 2 emissions. Mathematically, the scheduling problem is posed as a multi-objective Mixed Integer Linear Programming (MILP), which can be solved by using standard algorithms. A case study is performed to assess the performance of the proposed scheduling framework. Numerical results show that the new formulation can decrease both the CO 2 emissions and the electricity bill. Furthermore, a survey of studies that deal with scheduling of smart appliances is provided. These papers use methods based on MILP, Dynamic Programming (DP), and Minimum Cut Algorithm (MCA) for solving the scheduling problem. We discuss their performance in terms of computation time and optimality versus time discretization and number of appliances.

KW - domestic appliances

KW - dynamic programming

KW - environmental management

KW - graph theory

KW - integer programming

KW - linear programming

KW - power system economics

KW - scheduling

KW - secondary cells

KW - MILP

KW - active houses

KW - batteries

KW - carbon dioxide efficient scheduling

KW - carbon dioxide emission reduction

KW - electricity bill reduction

KW - energy scheduling

KW - minimum cut algorithm

KW - multiobjective mixed integer linear programming

KW - smart appliances

KW - Automation

KW - Batteries

KW - Electricity

KW - Home appliances

KW - Optimal scheduling

KW - Power demand

KW - Scheduling

UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-84939633153&partnerID=MN8TOARS

U2 - 10.1109/CoASE.2014.6899394

DO - 10.1109/CoASE.2014.6899394

M3 - Conference contribution

SP - 632

EP - 639

BT - 2014 IEEE International Conference on Automation Science and Engineering (CASE)

PB - IEEE

CY - Piscataway

T2 - Automation Science and Engineering (CASE). IEEE International Conference on

Y2 - 18 August 2014 through 22 August 2014

ER -

Energy and CO2 efficient scheduling of smart appliances in active houses equipped with batteries

Abstract

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this