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An approach to attain a balanced trade-off solution for dynamic economic emission dispatch problem on a microgrid system

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Abstract

Electricity generation involves the release of hazardous gases into the environment by fossil-fueled generators. Along with promoting the renewable energy sources, power engineers must come up with a compromise solution that results in reduced harmful gas emissions when electricity is generated economically. The goal of this paper is to structure a balanced trade-off approach for solving the problem of environment constrained economic dispatch (ECED).novel comparison of the proposed ECED method, existing price-penalty-factor (PPF), and fractional programming (FP) methods for solving CEED problems is carried out on a dynamic 3-unit test system to evaluate which technique provides a healthier trade-off solution in terms of cost as well as toxic gases emitted. By combining the greedy JAYA algorithm with an algorithm based on a crow’s food seeking approach, a robust hybrid algorithm is developed that used as the optimization tool. When comparing the suggested ECED technique to the PPF and FP based CEED solutions, the amount of released pollutants and generating cost were considerably nearer to the emission dispatch and economic dispatch respectively. Furthermore, statistical research backs up the suggested hybrid optimizer’s superiority over existing algorithms in the literature.

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Data are available from the corresponding author on reasonable request.

References

  • Anestis A, Georgios V (2019) Economic benefits of Smart Microgrids with penetration of DER and mCHP units for non-interconnected islands. Renew Energy 142:478–486

    Google Scholar 

  • Askarzadeh A (2016) A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Comput Struct 169:1–12

    Google Scholar 

  • Askarzadeh A (2017) A memory-based genetic algorithm for optimization of power generation in a microgrid. IEEE Trans Sustain Energy 9:1081–1089

    Google Scholar 

  • Bahmani-Firouzi B, Azizipanah-Abarghooee R (2014) Optimal sizing of battery energy storage for micro-grid operation management using a new improved bat algorithm. Int J Electr Power Energy Syst 56:42–54

    Google Scholar 

  • Basak S, Bhattacharyya B, Dey B (2022a) Dynamic economic dispatch using hybrid CSAJAYA algorithm considering ramp rates and diverse wind profiles. Intell Syst Appl 16:200116

    Google Scholar 

  • Basak S, Bhattacharyya B, Dey B (2022b) Combined economic emission dispatch on dynamic systems using hybrid CSA-JAYA Algorithm. Int J Syst Assur Eng Manag 13(5):2269–2290

    Google Scholar 

  • Basak S, Dey B, Bhattacharyya B (2022c) Uncertainty-based dynamic economic dispatch for diverse load and wind profiles using a novel hybrid algorithm. Environ Dev Sustain 25:1–41

    Google Scholar 

  • Basu M, Chowdhury A (2013) Cuckoo search algorithm for economic dispatch. Energy 60:99–108

    Google Scholar 

  • Bhattacharya A, Chattopadhyay PK (2010) Solving complex economic load dispatch problems using biogeography-based optimization. Expert Syst Appl 37:3605–3615

    Google Scholar 

  • Chen C, Duan S, Cai T, Liu B, Hu G (2011) Smart energy management system for optimal microgrid economic operation. IET Renew Power Gener 5:258–267

    Google Scholar 

  • Coelho VN, Coelho IM, Coelho BN, Cohen MW, Reis AJ, Silva SM et al (2016) Multi-objective energy storage power dispatching using plug-in vehicles in a smart-microgrid. Renew Energy 89:730–742

    Google Scholar 

  • Daniel L, Chaturvedi KT, Kolhe ML (2018) Dynamic economic load dispatch using Levenberg Marquardt algorithm. Energy Procedia 144:95–103

    Google Scholar 

  • Dey B, Bhattacharyya B (2022) Comparison of various electricity market pricing strategies to reduce generation cost of a microgrid system using hybrid WOA-SCA. Evol Intell 15(3):1587–1604

    Google Scholar 

  • Dey B, Roy SK, Bhattacharyya B (2019) Solving multi-objective economic emission dispatch of a renewable integrated microgrid using latest bio-inspired algorithms. Eng Sci Technol Int J 22:55–66

    Google Scholar 

  • Dey B, Bhattacharyya B, Márquez FPG (2021a) A hybrid optimization-based approach to solve environment constrained economic dispatch problem on microgrid system. J Clean Prod 307:127196

    Google Scholar 

  • Dey B, Bhattacharyya B, Devarapalli R (2021b) A novel hybrid algorithm for solving emerging electricity market pricing problem of microgrid. Int J Intell Syst 36(2):919–961

    Google Scholar 

  • Dey B, Basak S, Pal A (2022) Demand-side management based optimal scheduling of distributed generators for clean and economic operation of a microgrid system. Int J Energy Res 46(7):8817–8837

    Google Scholar 

  • Dhillon J, Parti S, Kothari D (1993) Stochastic economic emission load dispatch. Electr Power Syst Re 26:179–186

    Google Scholar 

  • Elattar EE (2018) Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources. Energy 159:496–507

    Google Scholar 

  • Gazijahani FS, Ravadanegh SN, Salehi J (2018) Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies. ISA Trans 73:100–111

    Google Scholar 

  • Ghasemi A, Enayatzare M (2018) Optimal energy management of a renewable-based isolated microgrid with pumped-storage unit and demand response. Renew Energy 123:460–474

    Google Scholar 

  • Gholami K, Dehnavi E (2019) A modified particle swarm optimization algorithm for scheduling renewable generation in a micro-grid under load uncertainty. Appl Soft Comput 78:496–514

    Google Scholar 

  • Goldberg DE, Holland JH (1988) Genetic algorithms and machine learning. Mach Learn 3:95–99. https://doi.org/10.1023/A:1022602019183

    Article  Google Scholar 

  • Hosseinnezhad V, Babaei E (2013) Economic load dispatch using θ-PSO. Int J Electr Power Energy Syst 49:160–169

    Google Scholar 

  • Kai S, Qing L, Jizhen L, Yuguang N, Ruifeng S, Yang B (2011) New combination strategy of genetic and tabu algorithm an economic load dispatching case study. In: 2011 Chinese control and decision conference (CCDC. pp. 1991–1995

  • Karmakar N, Bhattacharyya B (2020) Optimal reactive power planning in power transmission system considering FACTS devices and implementing hybrid optimisation approach. IET Gener Transm Distrib 14(25):6294–6305

    Google Scholar 

  • Kasaei MJ (2018) Energy and operational management of virtual power plant using imperialist competitive algorithm. Int Trans Electr Energy Syst 28:e2617

    Google Scholar 

  • Kumar KP, Saravanan B, Swarup K (2016) Optimization of renewable energy sources in a microgrid using artificial fish swarm algorithm. Energy Procedia 90:107–113

    Google Scholar 

  • Miao Di, Hossain S (2020) Improved gray wolf optimization algorithm for solving placement and sizing of electrical energy storage system in micro-grids. ISA Trans 102:376–387

    Google Scholar 

  • Moghaddam AA, Seifi A, Niknam T, Pahlavani MRA (2011) Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source. Energy 36:6490–6507

    Google Scholar 

  • Nwulu NI, Xia X (2017) Optimal dispatch for a microgrid incorporating renewables and demand response. Renew Energy 101:16–28

    Google Scholar 

  • Rabiee A, Sadeghi M, Aghaei J (2018) Modified imperialist competitive algorithm for environmental constrained energy management of microgrids. J Clean Prod 202:273–292

    Google Scholar 

  • Ramli MA, Bouchekara H, Alghamdi AS (2019) Efficient energy management in a microgrid with intermittent renewable energy and storage sources. Sustainability 11:3839

    Google Scholar 

  • Rao R (2016) Jaya: a simple and new optimization algorithm for solving constrained and unconstrained optimization problems. Int J Ind Eng Comput 7:19–34

    Google Scholar 

  • Sharma S, Bhattacharjee S, Bhattacharya A (2016) Grey wolf optimisation for optimal sizing of battery energy storage device to minimise operation cost of microgrid. IET Gener Transm Distrib 10:625–637

    Google Scholar 

  • Sharma S, Bhattacharjee S, Bhattacharya A (2018a) Operation cost minimization of a micro-grid using quasi-oppositional swine influenza model based optimization with quarantine. Ain Shams Eng J 9:45–63

    Google Scholar 

  • Sharma S, Bhattacharjee S, Bhattacharya A (2018b) Probabilistic operation cost minimization of micro-grid. Energy 148:1116–1139

    Google Scholar 

  • Sihna N (2001) Some studies on application of intelligent techniques to economic operation of power systems. Jadavpur University, Calcutta

    Google Scholar 

  • Sinha N, Chakrabarti R, Chattopadhyay P (2003) Evolutionary programming techniques for economic load dispatch. IEEE Trans Evol Comput 7:83–94

    Google Scholar 

  • Trivedi IN, Jangir P, Bhoye M, Jangir N (2018) An economic load dispatch and multiple environmental dispatch problem solution with microgrids using interior search algorithm. Neural Comput Appl 30:2173–2189

    Google Scholar 

  • Wang C, Shahidehpour S (1994) Ramp-rate limits in unit commitment and economic dispatch incorporating rotor fatigue effect. IEEE Trans Power Syst 9:1539–1545

    Google Scholar 

  • Yalcinoz T, Short M (1998) Neural networks approach for solving economic dispatch problem with transmission capacity constraints. IEEE Trans Power Syst 13:307–313

    Google Scholar 

  • Yang X, Leng Z, Xu S, Yang C, Yang L, Liu K et al (2021) Multi-objective optimal scheduling for CCHP microgrids considering peak-load reduction by augmented ε-constraint method. Renew Energy 172:408

    Google Scholar 

  • Zehra SS, Aqeel Ur R, Armghan H, Ahmad I, Ammara U (2021) Artificial intelligence-based nonlinear control of renewable energies and storage system in a DC microgrid. ISA Trans 121:217

    Google Scholar 

  • Zheng Y, Jenkins BM, Kornbluth K, Træholt C (2018) Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage. Renew Energy 123:204–217

    Google Scholar 

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Conceptualization, methodology and software: BD; validation and formal analysis: SR; visualization and data curation: RB; reviewing, editing & supervision: TC.

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Correspondence to Bishwajit Dey.

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Appendix

Appendix

See Tables 3 and 4.

Table 3 Generator parameters (Dey et al. 2021a)
Table 4 Predicted hourly output (day ahead) of wind and PV (Dey et al. 2021a)

See Fig. 8.

Fig. 8
figure 8

Dynamic load demand of the subject test system (Dey et al. 2021a)

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Dey, B., Raj, S., Babu, R. et al. An approach to attain a balanced trade-off solution for dynamic economic emission dispatch problem on a microgrid system. Int J Syst Assur Eng Manag 14, 1300–1311 (2023). https://doi.org/10.1007/s13198-023-01932-1

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