Methodology for energy management strategies design based on predictive control techniques for smart grids

被引:11
作者
Pajares, A. [1 ]
Vivas, F. J. [2 ]
Blasco, X. [1 ]
Herrero, J. M. [1 ]
Segura, F. [2 ]
Andujar, J. M. [2 ]
机构
[1] Univ Politecn Valencia, Inst Univ Automat & Informat Ind, Valencia, Spain
[2] Univ Huelva, Ctr Invest Tecnol Energia & Sostenibil CITES, Huelva, Spain
关键词
Model predictive controller; Energy management system; Renewable microgrids; Hydrogen-hybridized backup systems; LEAD-ACID; EXERGOECONOMIC ANALYSIS; STORAGE; CELL; OPTIMIZATION; MICROGRIDS; BATTERY; SYSTEMS; DEGRADATION;
D O I
10.1016/j.apenergy.2023.121809
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This article focuses on the development of a general energy management system (EMS) design methodology using on model-based predictive control (MPC) for the control and management of microgrids. Different MPCbased EMS for microgrids have been defined in the literature; however, there is a lack of generality in the proposed that would facilitate adapting to new architectures, energy storage system technology, nature of the bus, application, or purpose. To fill this gap, a novel general formulation that is parameterizable, simple, easily interpretable, and reproducible in different microgrid architectures is presented. This is the result of the development of a novel methodology, which is also presented. It considers the state space formulation of the controller from the initial modelling phase, from the dynamics of the energy storage systems represented by their models to the subsequent definition of the optimisation problem. This is developed through the design of the general cost function and the formulation of constrains, by means of general guidelines and reference values. To evaluate the performance of the developed methodology, simulation tests were carried out for four different microgrid architectures, with different applications and objectives, also considering different generation conditions, demand profiles, and initial conditions. The results showed that, with some simple guidelines and regardless of the case study, the developed MPC controller design methodology can address the technical economic optimisation problem associated with energy management in microgrids in an easy and intuitive way.
引用
收藏
页数:19
相关论文
共 57 条
[1]  
A. E. M. Commission, 2015, Future energy storage trends: An assessment of the economic viability, potential uptake and impacts of electrical energy storage on the NEM 2015-2035
[2]  
Akhil A.A., 2013, SANDIA REPORT 2013 Electricity Storage Handbook in Collaboration with NRECA
[3]  
[Anonymous], About us
[4]   Comparison the economic analysis of the battery between lithium-ion and lead-acid in PV stand-alone application [J].
Anuphappharadorn, Suratsawadee ;
Sukchai, Sukruedee ;
Sirisamphanwong, Chatchai ;
Ketjoy, Nipon .
11TH ECO-ENERGY AND MATERIALS SCIENCE AND ENGINEERING (11TH EMSES), 2014, 56 :352-358
[5]  
Argyrou Maria C., 2018, 2018 53 INT U POWER
[6]   Control of systems integrating logic, dynamics, and constraints [J].
Bemporad, A ;
Morari, M .
AUTOMATICA, 1999, 35 (03) :407-427
[7]   Fault diagnosis methods for Proton Exchange Membrane Fuel Cell system [J].
Benmouna, A. ;
Becherif, M. ;
Depernet, D. ;
Gustin, F. ;
Ramadan, H. S. ;
Fukuhara, S. .
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2017, 42 (02) :1534-1543
[8]   Model-based predictive control of greenhouse climate for reducing energy and water consumption [J].
Blasco, X. ;
Martinez, M. ;
Herrero, J. M. ;
Ramos, C. ;
Sanchis, J. .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2007, 55 (01) :49-70
[9]  
Bordons C., 2020, MODEL PREDICTIVE CON, V1, P191, DOI [10.1007/978-3-030-24570-2, DOI 10.1007/978-3-030-24570-2]
[10]   Optimal Energy Management for Renewable Energy Microgrids [J].
Bordons, Carlos ;
Garcia-Torres, Felix ;
Valverde, Luis .
REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL, 2015, 12 (02) :117-132