The Effect of Different Non-linear Demand Response Models Considering Incentive and Penalty on Transmission Expansion Planning
The Transmission Expansion Planning (TEP) problem involves adding new lines to the existing electrical transmission network in order to meet the electrical demand requirements. Demand Response (DR) plays an important role in solving the TEP problem due to the delay in the investment costs. Researchers usually focus on the linear model of DR, while the focus on nonlinear models including power, exponential and logarithmic of DR is small. In this paper and in order to understand which model gives the realistic results, the linear model of DR is studied simultaneously with nonlinear models including power, exponential and logarithmic of DR. Moreover, the effect of incentive and penalty which has been neglected in the studies, is investigated. The study is investigated based on the viewpoint of different participants of the market including Independent System Operator (ISO), Customers and Utilities. In order to prioritize and select the most effective DR program, five characteristics including Peak Reduction, Energy Consumption, Load Factor, Peak to Valley and Customer’s Total Cost are extracted from the load curve. Then, using the weighting coefficients obtained by Entropy technique and implementing the TOPSIS and AHP technique, different DR programs are prioritized.
A. S. Zakeri, H. Askarian Abyaneh, “Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response Resources”, Energies10.9 (2017): 1376.
O. A. Gashteroodkhani, B. Vahidi, and A. Zaboli, "Time-time matrix z-score vector-based fault analysis method for series-compensated transmission lines," Turkish Journal of Electrical Engineering & Computer Sciences, vol. 25, pp. 2647-2659, 2017.
I. Niazazari, B. Vahidi, & H. A. Abyaneh, "Loss reduction of wind turbine with optimization of blade length using genetic algorithm." Science International, 25(4), pp. 807 -811, 2013
L. L. Garver, “Transmission network estimation using linear programming”, IEEE Transactions on Power Apparatus and Systems 7 (1970): 1688-1697.
G. Latorre-Bayona, I. J. Perez-Arriaga, “Chopin, a heuristic model for long term transmission expansion planning”, IEEE Transactions on Power systems9.4 (1994): 1886-1894.
M. V. Pereira, L. M. Pinto, “Application of sensitivity analysis of load supplying capability to interactive transmission expansion planning”, IEEE Transactions on Power Apparatus and Systems 2 (1985): 381-389.
A. Monticelli, A. Santos, M. V. F. Pereira, S. H. Cunha, B.J. Parker, J. C. G. Praca, “Interactive transmission network planning using a least-effort criterion”, IEEE Transactions on Power Apparatus and Systems 10 (1982): 3919-3925.
E. J. De Oliveira, I. C. da Silva, J. L. R. Pereira, S. Carneiro, “Transmission system expansion planning using a sigmoid function to handle integer investment variables”, IEEE Transactions on Power Systems20.3 (2005): 1616-1621.
V. Sarfi, I. Niazazari, and H. Livani, "Multiobjective fireworks optimization framework for economic emission dispatch in microgrids." North American Power Symposium (NAPS), 2016, pp. 1-6, Nov. 2016.
V. A. Levi, M. S. ?alovi?, “Linear-programming-based decomposition method for optimal planning of transmission network investments”, IEE Proceedings C (Generation, Transmission and Distribution). Vol. 140. No. 6. IET Digital Library, 1993.
I. Niazazari, H.A. Abyaneh, M. J. Farah, F. Safaei, andH. Nafisi,“Voltage profile and power factor improvement in PHEV charging station using a probabilistic model and flywheel,” In Electrical Power Distribution Networks (EPDC), 2014 19th Conference on pp. 100-105. May. 2014
M. V. F. Pereira, L. M. V. G. Pinto, S. H. F. Cunha, G. C. Oliveira, “A decomposition approach to automated generation/transmission expansion planning”, IEEE Transactions on Power Apparatus and Systems 11 (1985): 3074-3083.
O. A. Gashteroodkhani and B. Vahidi, "Application of Imperialistic Competitive Algorithm to Fault Section Estimation Problem in Power Systems," in The International Conference in New Research of Electrical Engineering and Computer Science, Iran, Sep 2015.
R. A. Gallego, A. B. Alves, A. Monticelli, R. Romero, “Parallel simulated annealing applied to long term transmission network expansion planning”, IEEE Transactions on Power Systems 12.1 (1997): 181-188.
S. Binato, G. C. De Oliveira, J. L. De Araújo, “A greedy randomized adaptive search procedure for transmission expansion planning”, IEEE Transactions on Power Systems 16.2 (2001): 247-253.
O. A. Gashteroodkhani, M. Majidi, M. Etezadi-Amoli, A. F. Nematollahi, "A hybrid SVM-TT transform-based method for fault location in hybrid transmission lines with underground cables" Electric Power Systems Research, vol. 170, pp. 205-214, 2019.
S. Aznavi, P. Fajri and A. Asrari, "Smart Home Energy Management Considering Real-Time Energy Pricing of Plug-in Electric Vehicles," in 2018 IEEE Energy Conversion Congress and Exposition (ECCE), Portland, OR, USA, 2018, pp. 67-72.
S. Aznavi, P. Fajri, M. Benidris and B. Falahati, "Hierarchical droop controlled frequency optimization and energy management of a grid-connected microgrid," in 2017 IEEE Conference on Technologies for Sustainability (SusTech), Phoenix, AZ, USA, 2017, pp. 1-7.
A. Vahid, Sh. Jadid, M. Ehsan, “Optimal Planning of a Multi-Carrier Microgrid (MCMG) Considering Demand-Side Management”,. International Journal of Renewable Energy Research (IJRER) 8.1 (2018): 238-249.
Ö. Özdemir, F. D. Munoz, J. L. Ho, B. F. Hobbs, “Economic analysis of transmission expansion planning with price-responsive demand and quadratic losses by successive LP”, IEEE Transactions on Power Systems 31.2 (2016): 1096-1107.
K. S. Stille, J. Böcker, “Local demand response and load planning system for intelligent domestic appliances”, Renewable Energy Research and Applications (ICRERA), 2015.
I. Konstantelos, G. Strbac, “Valuation of flexible transmission investment options under uncertainty”, IEEE Transactions on Power systems 30.2 (2015): 1047-1055.
Albadi, Mohamed H., and Ehab F. El-Saadany. "A summary of demand response in electricity markets." Electric power systems research 78.11 (2008): 1989-1996.
Cappers P, Goldman C, Kathan D. Demand response in U.S. electricity markets: empirical evidence. Energy April 2010;35(4). Demand response resources: the US and International Experience.
Charles River Associates. Primer on demand-side management with an Emphasis on price-Responsive programs, Report prepared for The World Bank. Washington, DC, CRA No. D06090, 2005. Available online: <http://www.worldbank.org>, [accessed 11.10].
M. Mirmozaffari, "Eco-Efficiency Evaluation in Two-Stage Network Structure: Case Study: Cement Companies," Iranian Journal of Optimization. vol.11, Issue 2, 2018.
M. Mirmozaffari, A. Alinezhad, "Ranking of Heart Hospitals Using Cross-efficiency and Two-stage DEA," 7th International Conference on Computer and Knowledge Engineering (ICCKE) 26-27, Ferdowsi University of Mashhad, 978-1-5386-0804-31/17$31.00©2 IEEE, October 2017.
H. A. Aalami, M. Parsa Moghaddam, and G. R. Yousefi. "Evaluation of nonlinear models for time-based rates demand response programs." International Journal of Electrical Power & Energy Systems 65 (2015): 282-290.
A. S. Zakeri, H. Askarian-Abyaneh. "Investigation of Wind Power Uncertainty on Transmission Network Expansion Planning." International Journal of Renewable Energy Research (IJRER) 8.4 (2018): 1903-1912.
K. Nigim, N. Munier, J. Green, Prefeasibility MCDM tools to aid communities in prioritizing local viable renewable energy sources, Elsevier, Renewable energy 29 (September (11)) (2004) 1775–1791.
D. Cirio, G. Demartini, S. Massucco, A. Monni, P. Scaler, F. Silvestvo, G. Vimercati, Load control for improving system security and economics, in: IEEE, Power Tech Conference, vol. 4, June 2003, 2003.
M. Parsa moghaddam, M.K. Sheik-El-Eslami, S. Jadid, A MADM framework for generation expansion planning in small electricity firms, IEEE, Transaction on Power System (2005).
H. A. Aalami, M. P. Moghaddam, and G. R. Yousefi. "Modeling and prioritizing demand response programs in power markets." Electric Power Systems Research 80.4 (2010): 426-435.