Email this article 
Open Access
Subscription or Fee Access
A Novel Algorithm for Smart Grids-Optimal Load Scheduling
(*) Corresponding author
DOI: https://doi.org/10.15866/iremos.v11i2.12841
Abstract
Load factor (LF) is a critical parameter that can greatly affect the efficiency of the power system and hence the cost of produced energy. For a power plant to operate economically, it must have a high LF. It is therefore considered useful and necessary to search for ways to match Demand and Supply as much as possible by implementing Demand Side Management (DSM) strategies on the consumer demand loads such as load profile reshaping. DSM practices have been implemented by the industry many years ago, mainly to manage large and predictable loads. Technical losses and other supply constraints caused by geopolitical changes, and the high cost of imported oil, may encourage the power utilities to find smart solutions within DSM strategies. The objective of this paper is to develop new universal algorithms for the load demand shifting. These algorithms were tested on real data and a comparison with Genetic Algorithms (GA) is shown to prove the validity of the obtained results. The study further aims at increasing the LF for different consuming sectors by exploring some applicable cases. Saving on the electricity bill is ultimately analyzed by referring to more than one sample of demand load objective and analyzing the cost reduction from the end user side.
Copyright © 2018 Praise Worthy Prize - All rights reserved.
Keywords
References
Intergouvernmental Panel on Climate change (IPCC) 2007: Synthesis report, tech rep. 2007.
Kinsey and Company, Pathways to a low-carbon economy, Tech. rep. 2009.
Martirano L., Habib E., Parise G., Greco G., Manganaelli M., Massarella F. and Parise L., " Smart Micro Grids for Nearly Zero Energy Buildings", 2016-ESC-0734.
http://dx.doi.org/10.1109/ias.2016.7731831
Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings.
Perez K., Baldea M.and Edgar T., " Integrated Smart Appliance Scheduling and HVAC Control for Peak Residential Load Management", 2016 American Control Conference, Boston, MA, USA, July, 2016.
http://dx.doi.org/10.1109/acc.2016.7525122
Paterakis G., pappi I., Erdinc O., Godina R., Rodrigues E. and Catalao J., "Consideration of the Impacts of aSmart Neighborhood Load onTransformer Aging", IEEE Transactionson Smart Grid, Vol. 7, No. 6, November 2016.
http://dx.doi.org/10.1109/pesgm.2017.8274502
A. D. Hilshey, P. D. H. Hines, P. Rezaei, and J. R. Dowds, "Estimating the impact of electric vehicle smart charging on distribution transformerageing," IEEE Transactions on Smart Grid, Vol. 4, No. 2, pp. 905–913, June 2013.
http://dx.doi.org/10.1109/tsg.2012.2217385
Byungchul K. and Lavrova O. “Two Hierarchy (Home and Local) Smart Grid Optimization by using Demand Response Scheduling”, IEEE paper, 2013.
http://dx.doi.org/10.1109/isgt-la.2013.6554403
Fang, X., “Engineering design using genetic algorithms”, Doctoral Thesis, Iowa State University, United States of America, 2007.
Logenthiran, T and Srinivasan D., “Demand Side Management in Smart Grid Using Heuristic Optimization”, IEEE Transactions on Smart Grid, Vol. 3, No. 3, September 2012.
http://dx.doi.org/10.1109/tsg.2012.2195686
Hansen T., Toche R., Suryanarayanan S. Maciejewski A. and Siegel H., “Heuristic Optimization for an Aggregator-Based Resource Allocation in the Smart Grid”, IEEE Transactions on Smart Grid, Vol. 6, No. 4, July 2015.
http://dx.doi.org/10.1109/tsg.2015.2399359
11Popovic, Z. and Popovic D., “Direct Load Control as a Market-based Program in Deregulated Power Industries”, IEEE Bologna PowerTech Conference, Bologna, Italy, June 2003.
http://dx.doi.org/10.1109/ptc.2003.1304491
L. Yao, W. C. Chang, and R. L. Yen, “An iterative deepening genetic algorithm for scheduling of direct load control,” IEEE Trans. Power Syst., Vol. 20, No. 3, August 2005.
http://dx.doi.org/10.1109/tpwrs.2005.852151
Chen Y., Ping Liu R., Wang C., De Groot M. and Zeng Z., “Consumer Operational Comfort Level Based Power Demand Management in the Smart Grid”, 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), Berlin, 2012.
http://dx.doi.org/10.1109/isgteurope.2012.6465829
S Ashok, R Banerjee,, Load-management applications for the industrial sector, Applied Energy, Volume 66, Issue 2, 2000, Pages 105-111.
http://dx.doi.org/10.1016/s0306-2619(99)00125-7
Bakr, S., “Design, Simulation, and emulation of a residential load management algorithm utilizing a proposed smart grid environment for the MENA region”, Master of Science, Cairo University, Egypt and Kassel University, Germany, March, 2012.
Paulus M. and Borggrefe F., “Economic potential of demand side management in an industrialized country- The case of Germany”, Institute of Energy Economics (EWI) at the university of Cologne, Albertus-Magnus-Paltz, 2009.
AboGaleela M., El Sobki M and El Marsafawy M, “Two level Optimal DSM Load Shifting Formulation using Genetic Algorithm - Case Study: Residential Loads”, IEEE PES Power Africa 2012 Conference and Exposition, July 2012.
http://dx.doi.org/10.1109/powerafrica.2012.6498651
Sulaiman, M., An Application of Differential Search Algorithm in Solving Non-Convex Economic Dispatch Problems with Valve-Point Effects, (2013) International Review on Modelling and Simulations (IREMOS), 6 (5), pp. 1593-1599.
Vennila, H., Prakash, T., Rajesh, R., A Solution to the Combined Economic and Emission Dispatch Using Hybrid HB-SA Algorithm on Large Scale Power System, (2013) International Review on Modelling and Simulations (IREMOS), 6 (4), pp. 1256-1263.
C Sengodan, B., Arunachalam, V., Dash, S., Comparison of Various Learning Algorithms for Artificial Neural Network Based On-Line Load Flow Analysis, (2014) International Review on Modelling and Simulations (IREMOS), 7 (2), pp. 323-330.
Refbacks
- There are currently no refbacks.
Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize
