Analysis of Data Generated by an Automated Platform for Aggregation of Distributed Energy Resources

被引:2
作者
Aguilar, Juan [1 ]
Arce, Alicia [2 ]
机构
[1] Univ Seville, Dept Syst Engn & Automat Control, Seville, Spain
[2] Ayesa, Control Syst Lab, Seville, Spain
来源
OPTIMIZATION AND LEARNING | 2020年 / 1173卷
基金
欧盟地平线“2020”;
关键词
Energy; Intelligent system; Optimization; Mathematical programming;
D O I
10.1007/978-3-030-41913-4_23
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The irruption of Distributed Energy Resources (DER) in the power system involves new scenarios where domestic consumers (end-users) would participate aggregated in energy markets, acting as prosumers. Amongst the different possible scenarios, this work is focused on the analysis of the results of a case study which is composed by 40 homes equipped with energy generation units including Li-Ion batteries, HESS systems and second life vehicle batteries to hydrogen storages. Software tools have been developed and deployed in the pilot to allow the domestic prosumers to participate into wholesale energy markets so that operations would be aggregated (all DERs acting as single instance), optimal (optimizing profit and reducing penalties) and smart managed (helping operators in the decision making process). Participating in energy markets is not trivial due to different technical requirements that every participant must comply. Amongst the different existent markets, this paper is focused on the participation in the day-ahead market and the grid operation during the following day to reduce penalties and comply with the energy profile committed. This paper presents an analysis of the data generated during the pilot operation deployed in a real environment. This valuable analysis will be developed in Sect. 4 Results, which raises important conclusions that will be presented. Netfficient is a project funded by the European Union's Horizon 2020 research and innovation program, with the main objective of the deployment and testing of heterogeneous storages at different levels of the grid on the German Island of Borkum.
引用
收藏
页码:282 / 294
页数:13
相关论文
共 9 条
  • [1] Andini C, 2018, RENEW ENERG
  • [2] Energy storage technologies and real life applications - A state of the art review
    Aneke, Mathew
    Wang, Meihong
    [J]. APPLIED ENERGY, 2016, 179 : 350 - 377
  • [3] Optimal Economical Schedule of Hydrogen-Based Microgrids With Hybrid Storage Using Model Predictive Control
    Garcia-Torres, Felix
    Bordons, Carlos
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2015, 62 (08) : 5195 - 5207
  • [4] Najafi-Ghalelou A, 2018, OPTIMAL SCHEDULING M
  • [5] Pattern recognition in building energy performance over time using energy benchmarking data
    Papadopoulos, Sokratis
    Bonczak, Bartosz
    Kontokosta, Constantine E.
    [J]. APPLIED ENERGY, 2018, 221 : 576 - 586
  • [6] A Model Predictive Control Approach to Microgrid Operation Optimization
    Parisio, Alessandra
    Rikos, Evangelos
    Glielmo, Luigi
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2014, 22 (05) : 1813 - 1827
  • [7] A review on buildings energy consumption information
    Perez-Lombard, Luis
    Ortiz, Jose
    Pout, Christine
    [J]. ENERGY AND BUILDINGS, 2008, 40 (03) : 394 - 398
  • [8] A review of optimization approaches for hybrid distributed energy generation systems: Off-grid and grid-connected systems
    Twaha, Ssennoga
    Ramli, Makbul A. M.
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2018, 41 : 320 - 331
  • [9] Energy storage system: Current studies on batteries and power condition system
    Zhang, Chao
    Wei, Yi-Li
    Cao, Peng-Fei
    Lin, Meng-Chang
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 82 : 3091 - 3106