Real-time stochastic power management strategies in hybrid renewable energy systems: A review of key applications and perspectives

被引:83
作者
Ciupageanu, Dana-Alexandra [1 ,2 ]
Barelli, Linda [1 ]
Lazaroiu, Gheorghe [2 ]
机构
[1] Univ Perugia, Dept Engn, Via G Duranti 93, I-06125 Perugia, Italy
[2] Univ Politehn Bucuresti, Power Engn Fac, Splaiul Independentei 313, Bucharest 060042, Romania
关键词
Energy storage; Real-time power management; Renewable energy; Stochastic optimization; Gradient-based optimization; MODEL-PREDICTIVE CONTROL; STORAGE SYSTEMS; SMART GRIDS; OPTIMIZATION; OPERATION; WIND; INTEGRATION; NETWORKS; DEMAND; DISPATCH;
D O I
10.1016/j.epsr.2020.106497
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Given their highly stochastic features, the hasten increase of renewable energy sources contribution in the global energy balance issues a strong impact on power systems operating conditions. In order to overcome drawbacks related to supply reliability and systems stability, real-time power management strategies able to achieve optimal targets in uncertain frameworks are currently of great interest. This paper aims to overview for the first time the latest progresses in the field of real-time power management algorithms designed for hybrid renewable energy systems. The findings of this research provide a comprehensive review of the state-of-the-art, individuating specific fields of application and focusing on the gaps that should be further investigated. Several approaches for real-time stochastic power management are presented from both theoretical and applicative points of view. A wide range of applications in terms of installed power, multi-objective optimization formulation and energy storage technologies hybridization result as the main challenges for real-time power management. To this regard, gradient-based optimization algorithms show the highest potential for real-time power management strategies implementation. In particular, their reduced computational cost if compared to other approaches, as well as the high adaptability to various configurations, make this kind of algorithms worthy of further investigation.
引用
收藏
页数:12
相关论文
共 85 条
[1]  
Alqurashi A., 2016, ELECT POWER SYST RES
[2]  
[Anonymous], IET RENEW POWER GENE
[3]  
[Anonymous], 2013, P 2013 IEEE PES INN
[4]  
[Anonymous], 2011, P ACM SIGMETRICS JOI
[5]   A probabilistic economic dispatch model and methodology considering renewable energy, demand and generator uncertainties [J].
Arriagada, E. ;
Lopez, E. ;
Lopez, M. ;
Blasco-Gimenez, R. ;
Roa, C. ;
Poloujadoff, M. .
ELECTRIC POWER SYSTEMS RESEARCH, 2015, 121 :325-332
[6]   Economics of innovative high capacity-to-power energy storage technologies pointing at 100% renewable micro-grids [J].
Baldinelli, Arianna ;
Barelli, Linda ;
Bidini, Gianni ;
Discepoli, Gabriele .
JOURNAL OF ENERGY STORAGE, 2020, 28
[7]  
Barelli L., 2019, P 2019 IEEE PES INN, P1, DOI [10.1109/ ISGTEurope.2019.8905775, DOI 10.1109/ISGTEUROPE.2019.8905519]
[8]   A novel energy scheduling framework for reliable and economic operation of islanded and grid-connected microgrids [J].
Bashir, Arslan Ahmad ;
Pourakbari-Kasmaei, Mahdi ;
Contreras, Javier ;
Lehtonen, Matti .
ELECTRIC POWER SYSTEMS RESEARCH, 2019, 171 :85-96
[9]   A compromise solution for the multiobjective stochastic linear programming under partial uncertainty [J].
Ben Abdelaziz, Fouad ;
Masri, Hatem .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2010, 202 (01) :55-59
[10]  
BenTal A, 2009, PRINC SER APPL MATH, P1