Abstract
In this paper, cuckoo optimization algorithm is implemented to solve energy production cost minimization in a combined heat and power (CHP) generation system. This problem is also known as combined heat and power economic dispatch problem, which looks for optimal values of power and heat generation of each CHP unit to minimize the total production cost. Cuckoo optimization algorithm is a new metaheuristic algorithm. It is inspired by the life of a bird family, called cuckoo, that special lifestyle of these birds and their characteristics in egg laying and breeding has been the basic motivation for development of this algorithm. Unlike of the some previous approaches, the effect of valve point is considered in the cost function and clearly formulated in the conventional polynomial cost function as absolute sinusoidal term. The proposed method is applied to three small (with three different test cases), medium, and large test systems in order to evaluate its efficiency and feasibility. The obtained results demonstrated a higher quality solution and superior performance of the proposed cuckoo optimization algorithm method in comparison with many existing methodologies.
Similar content being viewed by others
Abbreviations
 i :

Index for conventional thermal units
 j :

Index for cogeneration units
 k :

Index for heatonly units
 N _{ p } :

Number of conventional thermal units
 N _{ c } :

Number of cogeneration units
 N _{ h } :

Number of heatonly units
 α _{ i }, β _{ i }, and γ _{ i } :

The cost coefficients of the i th conventional thermal units
 λ _{ i } and ρ _{ i } :

The cost coefficients for modeling valvepoint effects
 P _{demand} and H _{demand} :

System power and thermal demands
 a _{ j }, b _{ j }, c _{ j }, d _{ j }, e _{ j } and f _{ j } :

The cost coefficients of the j th cogeneration unit
 a _{ k }, b _{ k }, and c _{ k } :

The cost coefficients of the k th heatonly unit
 \( {P}_i^{p_{\min }}\ \mathrm{and}\ {P}_i^{p_{\max }} \) :

Minimum and maximum power outputs of the i th conventional poweronly unit in megawatt
 \( {H}_k^{h_{\min }}\ \mathrm{and}\ {\mathrm{H}}_k^{h_{\max }} \) :

Minimum and maximum thermal outputs of the k th heatonly unit
 \( {P}_i^{c_{\min }}\left({\mathrm{H}}_j^c\right)\ \mathrm{and}\ {P}_i^{c_{\max }}\left({\mathrm{H}}_j^c\right) \) :

Minimum and maximum power limit of CHP unit j which are functions of generated heat H ^{c}_{ j }
 \( {H}_j^{c_{\min }}\left({\mathrm{P}}_j^c\right)\ \mathrm{and}\ {H}_i^{c_{\max }}\left({\mathrm{P}}_j^c\right) \) :

Heat generation limits which are functions of generated power P ^{c}_{ j }
 H :

Heat output of unit
 P :

Power output of unit
 C _{ i }(P ^{p}_{ i } ):

Fuel cost of conventional thermal unit i
 C _{ j }(P ^{c}_{ j } , H ^{c}_{ j } ):

Cost function of the cogeneration unit j
 C _{ k }(H ^{h}_{ k } ):

Cost of heatonly unit k
References
Alipour, M., MohammadiIvatloo, B., & Zare, K. (2014). Stochastic riskconstrained shortterm scheduling of industrial cogeneration systems in the presence of demand response programs. Applied Energy, 136, 393–404.
Ameryan, M., Akbarzadeh Totonchi, M. R., & Seyyed Mahdavi, S. J. (2014). Clustering based on Cuckoo optimization algorithm. In Intelligent Systems (ICIS), 2014 Iranian Conference on 2014 (pp. 1–6): IEEE.
Ferreira, V. R., Augusto, C. M., Ribeiro, J. B., Gaspar, A. R., & Costa, J. J. (2015). Increasing the efficiency of high temperature furnaces through a topping cycle cogeneration—a case study. Energy Efficiency, 8(1), 85–95.
Fister, I., & Yang, X.S. (2015). A short discussion about “Economic optimization design of shellandtube heat exchangers by a cuckoosearchalgorithm”. Applied Thermal Engineering, 76, 535–537.
Gandomi, A. H., Yang, X.S., & Alavi, A. H. (2013). Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering With Computers, 29(1), 17–35.
Huang, S.H., & Lin, P.C. (2013). A harmonygenetic based heuristic approach toward economic dispatching combined heat and power. International Journal of Electrical Power & Energy Systems, 53, 482–487.
Johansson, M. T., & Soderstrom, M. (2014). Electricity generation from lowtemperature industrial excess heatan opportunity for the steel industry. Energy Efficiency, 7(2), 203–215.
Khorram, E., & Jaberipour, M. (2011). Harmony search algorithm for solving combined heat and power economic dispatch problems. Energy Conversion and Management, 52(2), 1550–1554.
Le Anh, T. N., Vo, D. N., Ongsakul, W., Vasant, P., & Ganesan, T. (2015). Cuckoo optimization algorithm for optimal power flow. In Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Volume 1, (pp. 479–493): Springer.
Mellal, M. A., & Williams, E. J. (2014). Parameter optimization of advanced machining processes using cuckoo optimization algorithm and hoopoe heuristic. Journal of Intelligent Manufacturing, 116.
Mellal, M. A., Adjerid, S., Williams, E. J., & Benazzouz, D. (2012). Optimal replacement policy for obsolete components using cuckoo optimization algorithm basedapproach: dependability context. Journal of Scientific and Industrial Research, 71(11), 715–721.
Mellal, M. A., Adjerida, S., & Williamsb, E. J. (2013). Optimal selection of obsolete tools in manufacturing systems using cuckoo optimization algorithm. Chemical Engineering, 33.
Meng, K., Wang, H. G., Dong, Z., & Wong, K. P. (2010). Quantuminspired particle swarm optimization for valvepoint economic load dispatch. Power Systems, IEEE Transactions on, 25(1), 215–222.
MohammadiIvatloo, B., Rabiee, A., Soroudi, A., & Ehsan, M. (2012). Iteration PSO with time varying acceleration coefficients for solving nonconvex economic dispatch problems. International Journal of Electrical Power & Energy Systems, 42(1), 508–516.
MohammadiIvatloo, B., MoradiDalvand, M., & Rabiee, A. (2013a). Combined heat and power economic dispatch problem solution using particle swarm optimization with time varying acceleration coefficients. Electric Power Systems Research, 95, 9–18.
MohammadiIvatloo, B., Rabiee, A., & Soroudi, A. (2013b). Nonconvex dynamic economic power dispatch problems solution using hybrid immunegenetic algorithm. IEEE Systems Journal, 7(4), 777–785.
Nguyen, T. T., & Truong, A. V. (2015). Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm. International Journal of Electrical Power & Energy Systems, 68, 233–242.
Piperagkas, G., Anastasiadis, A., & Hatziargyriou, N. (2011). Stochastic PSObased heat and power dispatch under environmental constraints incorporating CHP and wind power units. Electric Power Systems Research, 81(1), 209–218.
Rajabioun, R. (2011). Cuckoo optimization algorithm. Applied Soft Computing, 11(8), 5508–5518.
Ramesh, V., Jayabarathi, T., Shrivastava, N., & Baska, A. (2009). A novel selective particle swarm optimization approach for combined heat and power economic dispatch. Electric Power Components and Systems, 37(11), 1231–1240.
Roy, P. K., Paul, C., & Sultana, S. (2014). Oppositional teaching learning based optimization approach for combined heat and power dispatch. International Journal of Electrical Power & Energy Systems, 57, 392–403.
Salgado, F., & Pedrero, P. (2008). Shortterm operation planning on cogeneration systems: a survey. Electric Power Systems Research, 78(5), 835–848.
Song, Y., Chou, C., & Stonham, T. (1999). Combined heat and power economic dispatch by improved ant colony search algorithm. Electric Power Systems Research, 52(2), 115–121.
Su, C.T., & Chiang, C.L. (2004). An incorporated algorithm for combined heat and power economic dispatch. Electric Power Systems Research, 69(2), 187–195.
Subbaraj, P., Rengaraj, R., & Salivahanan, S. (2009). Enhancement of combined heat and power economic dispatch using self adaptive realcoded genetic algorithm. Applied Energy, 86(6), 915–921.
Vasebi, A., Fesanghary, M., & Bathaee, S. (2007). Combined heat and power economic dispatch by harmony search algorithm. International Journal of Electrical Power & Energy Systems, 29(10), 713–719.
Wang, L., & Singh, C. (2008). Stochastic combined heat and power dispatch based on multiobjective particle swarm optimization. International Journal of Electrical Power & Energy Systems, 30(3), 226–234.
Wong, K. P., & Algie, C. (2002). Evolutionary programming approach for combined heat and power dispatch. Electric Power Systems Research, 61(3), 227–232.
Yang, X.S., & Deb, S. (2009). Cuckoo search via Lévy flights. In Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, 2009 (pp. 210214): IEEE.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mehdinejad, M., MohammadiIvatloo, B. & DadashzadehBonab, R. Energy production cost minimization in a combined heat and power generation systems using cuckoo optimization algorithm. Energy Efficiency 10, 81–96 (2017). https://doi.org/10.1007/s1205301694396
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s1205301694396