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Heat Transfer Search Algorithm for Combined Heat and Power Economic Dispatch

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Iranian Journal of Science and Technology, Transactions of Electrical Engineering Aims and scope Submit manuscript

Abstract

This paper suggests heat transfer search (HTS) algorithm for solving complicated combined heat and power economic dispatch (CHPED) problem. The valve point effect, prohibited operating zones of conventional thermal generators and transmission loss are taken into consideration. The main objective of the CHPED problem is to minimize the total fuel cost for producing electricity and heat supplying to a load demand. HTS is a novel meta-heuristic optimization algorithm that is based on the law of thermodynamics and heat transfer. The efficiency of the suggested HTS algorithm has been confirmed on four test systems. Test results of the suggested HTS algorithm have been compared with those achieved by other evolutionary algorithms. It has been observed from the comparison that the suggested HTS algorithm has the ability to offer superior solution.

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Abbreviations

HTS:

Heat transfer search

CHPED:

Combined heat and power economic dispatch

PSO:

Particle swarm optimization

CPSO:

Classical particle swarm optimization

EP:

Evolutionary programming

GSO:

Group search optimization

OGSO:

Opposition-based group search optimization

OBL:

Opposition-based learning

PPS:

Powell’s pattern search

GA:

Genetic algorithm

HS:

Harmony search

CSA:

Cuckoo search algorithm

ECSA:

Effective cuckoo search algorithm

CSO:

Civilized swarm optimization

IAC:

Improved ant colony algorithm

TLBO:

Teaching learning-based optimization

OBTLBO:

Opposition-based teaching learning-based optimization

TVAC-PSO:

Time-varying acceleration coefficients particle swarm optimization

SARGA:

Self adaptive real-coded genetic algorithm

IGA-MU:

Improved genetic algorithm with multiplier updating

MBA:

Mine blast algorithm

FPA:

Flower pollination algorithm

GSA:

Gravitational search algorithm

KHA:

Kill herd algorithm

MPSO:

Modified particle swarm optimization

\(P_{{{\text{t}}i}}\) :

Power output of ith conventional thermal generator

\(P_{{{\text{t}}i}}^{\hbox{min} } ,\;P_{{{\text{t}}i}}^{\hbox{max} }\) :

Minimum and maximum power generation limits of ith conventional thermal generator

\(P_{{{\text{c}}i}} ,\;H_{{{\text{c}}i}}\) :

Power output and heat output of ith cogeneration unit

\(H_{{{\text{h}}i}}\) :

Heat output of ith heat-only unit

\(H_{{{\text{h}}i}}^{\hbox{min} } ,\;H_{{{\text{h}}i}}^{\hbox{max} }\) :

Minimum and maximum heat production limits of the ith heat-only unit

\(C_{\rm T}\) :

Total production cost

\(C_{{{\text{t}}i}} ,\;C_{{{\text{c}}i}} ,\;C_{{{\text{h}}i}}\) :

Fuel cost characteristics of the conventional thermal generator, cogeneration unit and heat-only unit, respectively

\(a_{i} ,b_{i} ,d_{i} ,e_{i} ,f_{i}\) :

Cost coefficients of ith conventional thermal generator

\(\alpha_{i} ,\beta_{i} ,\gamma_{i} ,\delta_{i} ,\varepsilon_{i} ,\xi_{i}\) :

Cost coefficients of ith cogeneration unit

\(\phi_{i} ,\eta_{i} ,\lambda_{i}\) :

Cost coefficients of ith heat-only unit

\(H_{\text{D}}\) :

Heat demand

\(P_{\text{D}}\) :

Power demand

\(P_{\text{L}}\) :

Transmission loss

\(N_{\text{t}} ,\;N_{\text{c}} ,\;N_{\text{h}}\) :

Numbers of conventional thermal generators, cogeneration units and heat-only units, respectively

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Authors and Affiliations

  1. Department of Power Engineering, Jadavpur University, Kolkata, 700098, India

    Jagat Kishore Pattanaik & Mousumi Basu

  2. Department of Electrical Engineering, Government College of Engineering, Kalahandi, Odisha, India

    Deba Prasad Dash

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  1. Jagat Kishore Pattanaik
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  2. Mousumi Basu
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  3. Deba Prasad Dash
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Correspondence to Jagat Kishore Pattanaik.

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Pattanaik, J.K., Basu, M. & Dash, D.P. Heat Transfer Search Algorithm for Combined Heat and Power Economic Dispatch. Iran J Sci Technol Trans Electr Eng 44, 963–978 (2020). https://doi.org/10.1007/s40998-019-00280-w

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  • DOI: https://doi.org/10.1007/s40998-019-00280-w

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