Planning Smart Grid Functions in Residential Loads Using a Virtual Equivalent Battery Storage Unit

被引:10
作者
Saleh, Saleh A. [1 ]
Cardenas-Barrera, Julian Luciano [1 ]
Castillo-Guerra, Eduardo [1 ]
Meng, Julian [1 ]
Alsayid, Basim [2 ]
Chang, Liuchen [1 ]
机构
[1] Univ New Brunswick, Dept Elect & Comp Engn, Fredericton, NB, Canada
[2] Palestine Tech Univ Kadoorie, Tulkarm, Palestine
关键词
Smart grids; Planning; Thermal energy; Power demand; Thermostats; Power system stability; Load modeling; Deregulated power system operation; distribution power transformers; frequency stability; load-side control actions; residential load demands; smart grid functions; DEMAND RESPONSE; FREQUENCY CONTROL; ELECTRIC LOADS; MANAGEMENT; OPTIMIZATION;
D O I
10.1109/TIA.2021.3097293
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This article develops a method for planning smart grid functions (peak-demand management, direct load control, and demand response) for residential loads. The proposed planning method is developed based on modeling the thermal energy stored in thermostatically controlled appliances (TCAs) as energy charged into a virtual (fictitious) equivalent battery storage unit (VE-BSU) at the distribution transformer that feeds these TCAs. The thermal energy stored in TCAs can reduce their power demands during peak-demand times. These reductions in power demands of TCAs can be modeled as discharging energy from the VE-BSU. The energy charged and discharged by the VE-BSU can be used to plan smart grid functions to maximize storing thermal energy in TCAs during off-peak-demand times (short time horizons). This feature is due to the ability to store thermal energy in TCAs, and completely use it over short time intervals. The VE-BSU-based planning method is implemented and tested for residential loads fed by five different distribution transformers. Test results demonstrate the ability of the proposed method to plan effective and stable actions of smart grid functions, with minor sensitivity to the number of residential loads and/or seasonal variations in their power demands.
引用
收藏
页码:4441 / 4455
页数:15
相关论文
共 40 条
[1]  
Agalgaonkar Yashodhan P., 2017, IEEE Power and Energy Technology Systems Journal, V4, P24, DOI 10.1109/JPETS.2017.2683502
[2]  
[Anonymous], 2017, Power System Toolbox User Guide
[3]   Robust Tracking Commitment [J].
Bitlislioglu, Altug ;
Gorecki, Tomasz T. ;
Jones, Colin N. .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2017, 62 (09) :4451-4466
[4]   Distribution system reliability assessment using hierarchical Markov modeling [J].
Brown, RE ;
Gupta, S ;
Christie, RD ;
Venkata, SS ;
Fletcher, R .
IEEE TRANSACTIONS ON POWER DELIVERY, 1996, 11 (04) :1929-1934
[5]   A Demand Response Implementation in Tertiary Buildings Through Model Predictive Control [J].
Bruno, Sergio ;
Giannoccaro, Giovanni ;
La Scala, Massimo .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2019, 55 (06) :7052-7061
[6]   Achieving Controllability of Electric Loads [J].
Callaway, Duncan S. ;
Hiskens, Ian A. .
PROCEEDINGS OF THE IEEE, 2011, 99 (01) :184-199
[7]   Operating Reserves Provision From Residential Users Through Load Aggregators in Smart Grid: A Game Theoretic Approach [J].
Chen, Shibo ;
Cheng, Roger S. .
IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (02) :1588-1598
[8]   Reliability-Constrained Power System Expansion Planning: A Stochastic Risk-Averse Optimization Approach [J].
da Costa, Luiz Carlos ;
Thome, Fernanda Souza ;
Garcia, Joaquim Dias ;
Pereira, Mario V. F. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2021, 36 (01) :97-106
[9]  
Delgado G. M, IN PRESS
[10]   THE CONCEPT OF DEMAND-SIDE MANAGEMENT FOR ELECTRIC UTILITIES [J].
GELLINGS, CW .
PROCEEDINGS OF THE IEEE, 1985, 73 (10) :1468-1470