Office building participation in demand response programs supported by intelligent lighting management

被引:0
作者
Khorram M. [1 ]
Abrishambaf O. [1 ]
Faria P. [1 ]
Vale Z. [1 ]
机构
[1] GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Institute of Engineering – Polytechnic of Porto (ISEP/IPP), Rua Dr. António Bernardino de Almeida, 431, Porto
关键词
Aggregation; Demand response; Optimization; SCADA;
D O I
10.1186/s42162-018-0008-4
中图分类号
学科分类号
摘要
According to importance of demand response programs in smart grids and microgrids, many efforts have been made to change the consumption patterns of the users, and the use of renewable resources has also increased. Significant part of energy consumption belongs to buildings such as residential, commercial, and office buildings. Many buildings are equipping with components that can be used for the participation in demand response programs. The SCADA system plays a key role in this context, which enables the building operator to have control and monitor the consumption and generation. This paper presents a real implementation of an optimization based SCADA system, which employs several controlling and monitoring methods in order to manage the consumption and generation of the building for decision support and participating in demand response events. Since the air conditioning devices are suitable controllable appliances for direct load control demand response, and lighting system as flexible loads for reduction and curtailment, they can play a key role in the scope of demand response programs. In this system, several real controller components manage the consumption of lighting system and air conditioning of the building based on an optimization model. In the case study of the paper, the SCADA system is considered as a player of an aggregation model, which is considered as demand response managing entity, and its performance during demand response events will be surveyed. The obtained results show that with adequate small reduction in the lighting system and air conditioning devices, the electricity customers are able to actively participate in the electricity markets using demand response programs and also for internal efficient use of electricity. © 2018, The Author(s).
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共 24 条
[1]  
Abrishambaf O., Faria P., Gomes L., Spinola J., Vale Z., Corchado J., Implementation of a real-time microgrid simulation platform based on centralized and distributed management, Energies, 10, 6, (2017)
[2]  
Abrishambaf O., Ghazvini M., Gomes L., Faria P., Vale Z., Corchado J., Application of a Home Energy Management System for Incentive-Based Demand Response Program Implementation, (2016)
[3]  
Erdinc O., Tascikaraoglu A., Paterakis N., Catalao J., An energy credit based incentive mechanism for the direct load control of residential HVAC systems incorporation in day-ahead planning, (2017)
[4]  
Faria P., Pinto A., Vale Z., Khorram M., Lighting Consumption Optimization using Fish School Search Algorithm, (2017)
[5]  
Faria P., Soares J., Vale Z., Morais H., Sousa T., Modified particle swarm optimization applied to integrated demand response and DG resources scheduling, IEEE Trans Smart Grid, 4, 1, pp. 606-616, (2013)
[6]  
Faria P., Spinola J., Vale Z., Aggregation and remuneration of electricity consumers and producers for the definition of demand-response programs, IEEE Trans Ind Inf, 12, 3, pp. 952-961, (2016)
[7]  
Faria P., Vale Z., Demand response in electrical energy supply: an optimal real time pricing approach, Energy, 36, 8, pp. 5374-5384, (2011)
[8]  
Fotouhi Ghazvini M., Soares J., Abrishambaf O., Castro R., Vale Z., Demand response implementation in smart households, Energ Buildings, 143, pp. 129-148, (2017)
[9]  
Hao H., Corbin C., Kalsi K., Pratt R., Transactive control of commercial buildings for demand response, IEEE Trans Power Sys, 32, 1, pp. 774-783, (2017)
[10]  
Hasan M., Mouftah H., Optimal trust system placement in smart grid SCADA networks, IEEE Access, 4, pp. 2907-2919, (2016)