Published November 2019 | Version v1
Journal article

Contract design of direct-load control programs and their optimal management by genetic algorithm

  • 1. Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City (Viet Nam)
  • 2. Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City (Viet Nam)
  • 3. Triangle Research and Development Center (Israel)
  • 4. Department of Electrical Engineering, Universidad de Zaragoza, Calle María de Luna 3, 50018, Zaragoza (Spain)
  • 5. INESC TEC and Faculty of Engineering of the University of Porto, R. Dr. Roberto Frias, 4200-465, Porto (Portugal)

Description

A computational model for designing direct-load control (DLC) demand response (DR) contracts is presented in this paper. The critical and controllable loads are identified in each node of the distribution system (DS). Critical loads have to be supplied as demanded by users, while the controllable loads can be connected during a determined time interval. The time interval at which each controllable load can be supplied is determined by means of a contract or compromise established between the utility operator and the corresponding consumers of each node of the DS. This approach allows us to reduce the negative impact of the DLC program on consumers' lifestyles. Using daily forecasting of wind speed and power, solar radiation and temperature, the optimal allocation of DR resources is determined by solving an optimization problem through a genetic algorithm where the energy content of conventional power generation and battery discharging energy are minimized. The proposed approach was illustrated by analyzing a system located in the Virgin Islands. Capabilities and characteristics of the proposed method in daily and annual terms are fully discussed, as well as the influence of forecasting errors.

Additional details

Identifiers

DOI
10.1016/j.energy.2019.07.137;
PII
S0360544219314793;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
186
Journal Page Range
vp.
ISSN
0360-5442
CODEN
ENEYDS

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55014875
Subject category
S29: ENERGY PLANNING, POLICY AND ECONOMY;
Descriptors DEI
CONTRACTS; DESIGN; ELECTRIC UTILITIES; ENERGY DEMAND; ENERGY MANAGEMENT; ERRORS; GENETIC ALGORITHMS; LIFE CYCLE ASSESSMENT; OPTIMIZATION; SOLAR RADIATION
Descriptors DEC
ALGORITHMS; DEMAND; MANAGEMENT; MATHEMATICAL LOGIC; PUBLIC UTILITIES; RADIATIONS; STELLAR RADIATION

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.