{
    "abstract": "The Environmental Economic Power Dispatch (EEPD) problem, a widely studied bi-objective nonlinear optimization challenge in power systems, traditionally focuses on the economic dispatch of thermal generators without considering network security constraints. However, environmental sustainability necessitates reducing emissions and increasing the penetration of renewable energy sources (RES) into the electrical grid. The integration of high levels of RES, such as wind and solar PV, introduces stability issues due to their uncertain and intermittent nature. This paper addresses these concerns by formulating and solving the Stable Environmental Economic Power Dispatch (SEEPD) problem, which includes fixed zonal reserve capacity from conventional thermal generators and uncertain reserves from RES. Uncertainties in RES and load demand are modeled using random variable generation techniques, applying Gaussian, Weibull, and log-normal probability density functions (PDFs) for load demand, wind velocity, and solar irradiance, respectively. The stochastic SEEPD problem extends to multiple periods by replicating the single-period problem for each interval in the planning horizon, linking periods through intertemporal ramping costs, physical ramp rate, and fixed zonal reserve constraints on dispatch variables. Multi-Objective Evolutionary Algorithms (MOEAs) have gained importance for solving complex nonlinear problems involving multi-objective functions. This paper applies the latest MOEAs to tackle the proposed SEEPD problem, incorporating stochastic wind and solar PV power sources. Network security constraints, such as transmission line capacities and bus voltage limits, are considered along with constraints on generator capabilities and intertemporal spinning reserves, ramp-up and ramp-down constraints for thermal generators. A bidirectional coevolutionary-based multi-objective evolutionary algorithm is employed, integrating an advanced constraint-handling technique to ensure compliance with system constraints. The simulation results show that the proposed formulation achieves a better trade-off between various conflicting objective functions compared to other state-of-the-art MOEAs.",
    "authors": [
        {
            "affiliation": "Department of Electrical Engineering, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Sindh, 67450, Pakistan.",
            "firstname": "Aamir",
            "initials": "A",
            "lastname": "Ali"
        },
        {
            "affiliation": "Department of Electrical Engineering, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Sindh, 67450, Pakistan.",
            "firstname": "Sumbal",
            "initials": "S",
            "lastname": "Aslam"
        },
        {
            "affiliation": "Department of Electrical Engineering, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Sindh, 67450, Pakistan.",
            "firstname": "M U",
            "initials": "MU",
            "lastname": "Keerio"
        },
        {
            "affiliation": "School of Electrical Engineering, Beijing Jiaotong University, Beijing, 100044, China.",
            "firstname": "Sohrab",
            "initials": "S",
            "lastname": "Mirsaeidi"
        },
        {
            "affiliation": "Department of Electrical Engineering, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Sindh, 67450, Pakistan.",
            "firstname": "Noor Hussain",
            "initials": "NH",
            "lastname": "Mugheri"
        },
        {
            "affiliation": "Department of Electrical Engineering, Quaid-e-Awam University of Engineering Science and Technology, Nawabshah, Sindh, 67450, Pakistan.",
            "firstname": "Muhammad",
            "initials": "M",
            "lastname": "Ismail"
        },
        {
            "affiliation": "School of Electrical Engineering, Southeast University, Nanjing, 210096, China.",
            "firstname": "Ghulam",
            "initials": "G",
            "lastname": "Abbas"
        },
        {
            "affiliation": "Department of Computers and Information Technologies, College of Sciences and Arts Turaif, Northern Border University, Arar 91431, Saudi Arabia.",
            "firstname": "Salwa",
            "initials": "S",
            "lastname": "Othmen"
        }
    ],
    "conclusions": null,
    "copyrights": "\u00a9 2024 Published by Elsevier Ltd.",
    "doi": "10.1016/j.heliyon.2024.e39041\n10.1016/j.apenergy.2024.123522\n10.1016/j.apenergy.2023.121856\n10.3389/fenrg.2023.1293870\n10.1049/gtd2.12664\n10.1109/TPWRS.2022.3220283\n10.1109/TSTE.2021.3112983\n10.1109/TCNS.2017.2722818\n10.1016/j.energy.2015.12.096\n10.1016/j.energy.2016.09.140\n10.1016/j.enconman.2014.09.034\n10.1109/TPWRS.2019.2942964\n10.1109/TSG.2018.2866068\n10.1109/TII.2012.2210431\n10.1016/j.epsr.2013.07.006\n10.1016/j.asoc.2016.02.046\n10.1016/j.ins.2016.01.081\n10.1016/j.enconman.2014.12.029\n10.1109/TPWRS.2016.2533540\n10.1016/j.ijepes.2022.107992\n10.35833/MPCE.2021.000220\n10.1016/j.apenergy.2021.117524\n10.1016/j.eswa.2024.123729\n10.1186/s41601-023-00279-w\n10.1016/j.apenergy.2023.122121\n10.1016/j.ijepes.2022.108653\n10.1109/TPWRS.2022.3210106\n10.1049/rpg2.12949\n10.1049/gtd2.13221\n10.1016/j.energy.2024.131510\n10.1109/TPWRS.2023.3349237\n10.1109/JSYST.2014.2325967\n10.1016/j.renene.2016.10.022\n10.1109/TPAS.1974.293972\n10.1007/s00521-020-05453-x\n10.1016/j.enconman.2017.06.071\n10.1016/j.epsr.2013.07.006\n10.1109/TSTE.2010.2044817\n10.1016/j.energy.2018.03.002\n10.1109/tpwrd.1986.4308013\n10.1016/j.swevo.2024.101504\n10.1016/j.swevo.2024.101488\n10.1109/TCYB.2021.3056176\n10.1109/SPIES48661.2020.9243016\n10.1109/TEVC.2014.2308305\n10.1109/TEVC.2005.851275\n10.1016/j.artint.2012.09.005\n10.1109/tevc.2013.2281534\n10.1109/TCYB.2020.3031642\n10.1109/TEVC.2021.3066301\n10.1109/TEVC.2022.3145582\n10.1109/TEVC.2023.3281666\n10.1016/j.eswa.2022.116499",
    "journal": "Heliyon",
    "keywords": [
        "Economic dispatch",
        "Fixed reserve",
        "Multi-objective evolutionary algorithms",
        "Renewable energy resources",
        "Voltage stability index"
    ],
    "methods": null,
    "publication_date": "2024-12-06",
    "pubmed_id": "39640744\n33822731\n33206620",
    "results": null,
    "title": "Optimal solution of multiobjective stable environmental economic power dispatch problem considering probabilistic wind and solar PV generation.",
    "xml": "<Element 'PubmedArticle' at 0x78850506d5d0>"
}