Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island's power system

被引:111
作者
Chapaloglou, Spyridon [1 ,2 ]
Nesiadis, Athanasios [1 ]
Iliadis, Petros [1 ]
Atsonios, Konstantinos [1 ]
Nikolopoulos, Nikos [1 ]
Grammelis, Panagiotis [1 ]
Yiakopoulos, Christos [2 ]
Antoniadis, Ioannis [2 ]
Kakaras, Emmanuel [1 ]
机构
[1] Ctr Res & Technol Hellas, Chem Proc & Energy Resources Inst, 6th Km Charilaou Thermis, GR-57001 Thermi, Greece
[2] Natl Tech Univ Athens, Sch Mech Engn, Machine Design & Control Syst Sect, Dynam & Struct Lab, Athens, Greece
关键词
Battery energy storage system; Energy management system; Load forecast; Peak shaving; Renewable energy; Island power systems; STORAGE-SYSTEM; CAPACITY FADE; PV SYSTEM; BATTERY; OPTIMIZATION; GENERATION; MICROGRIDS; STRATEGY; PROFILE;
D O I
10.1016/j.apenergy.2019.01.102
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
In this study, a novel algorithm for the management of the power flows of an islanded power system was developed, capable of simultaneously achieving steadier conventional unit operation and shaving the demand peak values, for the days of the year that present a night peak in their load curve. The under investigation system is composed of Diesel Generators, a PV farm and a Battery Energy Storage System (BESS) with the power system's consumption to be relatively higher than its RES production. The proposed algorithm combines the use of a load forecasting methodology, a pattern recognition procedure and a custom optimal power flow scheduling algorithm. The prediction module was based on a feedforward artificial neural network, capable of short-term day ahead load forecasting. The forecasted day ahead load profile was then used as an input to the developed pattern recognition algorithm, in order to be classified based on its load curve shape (pattern). Subsequently, in case that the classification resulted in a clear night peak pattern, it was possible to estimate an hourly based trajectory for the diesel generators operation and derive the BESS charging setpoints, which result in the desired peak shaving and smoothing level simultaneously. In this way, it is possible to replace or substitute the highest power demand with stored renewable energy and to operate the diesel engines as steady as possible, diminishing the ramp up and the steep gradients before the night hours' peak. The algorithm was integrated in the overall system model in APROS software, where dynamic simulations were performed. The simulation results proved that by applying the proposed algorithm, a combined effect of smoother diesel generator operation and peak shaving with renewable energy is achievable even with the absence of PV overproduction, diminishing the variability of the load to be covered from the conventional units. Such an operation aims at enabling diesel engines to be rated at a lower, than currently, maximum capacity while increasing the share of the renewable energy penetration into the grid.
引用
收藏
页码:627 / 642
页数:16
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