{"title":"Stochastic Economic Dispatch of a Power System With Solar Farm Considering Generation Flexibility and Reliability","authors":"Asghar Sabzevari, Majid Moazzami, Bahador Fani, Ghazanfar Shahgholian, Mahnaz Hashemi","doi":"10.1155/2024/5528243","DOIUrl":null,"url":null,"abstract":"<div>\n <p>In this paper, a novel approach is presented for optimizing economic dispatch (ED) in power systems featuring solar farms and flexible loads. The ED problem is formulated as a multiobjective optimization task with stochastic characteristics. To address this challenge, a hybrid multiobjective algorithm named hybrid differential evolution algorithm (hDE)-multiobjective flower pollination algorithm (MOFPA) is proposed, which integrates principles from the differential evolution algorithm and the MOFPA, yielding enhanced performance. Two weighted objective functions are introduced to represent operation cost and the power system generation flexibility index (GFI) based on carefully selected scenarios. The occurrence probability of each scenario influences the objective function’s final value. Monte Carlo simulation (MCS) is utilized for scenario selection, enabling a comprehensive assessment of system performance. We first evaluate the proposed algorithm by optimizing standard benchmark functions and comparing results against those of other state-of-the-art algorithms. The outcomes demonstrate the superior accuracy and efficiency of the hDE-MOFPA algorithm. In the subsequent simulation phase, we optimally solve the ED problem, considering uncertainties and the involvement of flexible loads. A sensitivity analysis is conducted to examine the impact of uncertainties and flexible loads on both cost and emissions. The results reveal that the combined uncertainty of load and photovoltaic (PV) significantly influences the system. By adopting this novel approach, our proposed method offers valuable insights into optimizing the ED problem in power systems with solar farms and flexible loads, considering uncertainties and various scenarios. The sensitivity analysis indicates that considering uncertainties leads to a 4.9% increase in operational expenditures and a 4.1% decrease in GFI. Also, uncertainties in load and irradiation range from 5% to 20%, GFI experiences a decline from 4.08% to 20.18%, while costs undergo an increase from 4.92% to 18.93%.</p>\n </div>","PeriodicalId":14051,"journal":{"name":"International Journal of Energy Research","volume":"2024 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/5528243","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Energy Research","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/5528243","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a novel approach is presented for optimizing economic dispatch (ED) in power systems featuring solar farms and flexible loads. The ED problem is formulated as a multiobjective optimization task with stochastic characteristics. To address this challenge, a hybrid multiobjective algorithm named hybrid differential evolution algorithm (hDE)-multiobjective flower pollination algorithm (MOFPA) is proposed, which integrates principles from the differential evolution algorithm and the MOFPA, yielding enhanced performance. Two weighted objective functions are introduced to represent operation cost and the power system generation flexibility index (GFI) based on carefully selected scenarios. The occurrence probability of each scenario influences the objective function’s final value. Monte Carlo simulation (MCS) is utilized for scenario selection, enabling a comprehensive assessment of system performance. We first evaluate the proposed algorithm by optimizing standard benchmark functions and comparing results against those of other state-of-the-art algorithms. The outcomes demonstrate the superior accuracy and efficiency of the hDE-MOFPA algorithm. In the subsequent simulation phase, we optimally solve the ED problem, considering uncertainties and the involvement of flexible loads. A sensitivity analysis is conducted to examine the impact of uncertainties and flexible loads on both cost and emissions. The results reveal that the combined uncertainty of load and photovoltaic (PV) significantly influences the system. By adopting this novel approach, our proposed method offers valuable insights into optimizing the ED problem in power systems with solar farms and flexible loads, considering uncertainties and various scenarios. The sensitivity analysis indicates that considering uncertainties leads to a 4.9% increase in operational expenditures and a 4.1% decrease in GFI. Also, uncertainties in load and irradiation range from 5% to 20%, GFI experiences a decline from 4.08% to 20.18%, while costs undergo an increase from 4.92% to 18.93%.
期刊介绍:
The International Journal of Energy Research (IJER) is dedicated to providing a multidisciplinary, unique platform for researchers, scientists, engineers, technology developers, planners, and policy makers to present their research results and findings in a compelling manner on novel energy systems and applications. IJER covers the entire spectrum of energy from production to conversion, conservation, management, systems, technologies, etc. We encourage papers submissions aiming at better efficiency, cost improvements, more effective resource use, improved design and analysis, reduced environmental impact, and hence leading to better sustainability.
IJER is concerned with the development and exploitation of both advanced traditional and new energy sources, systems, technologies and applications. Interdisciplinary subjects in the area of novel energy systems and applications are also encouraged. High-quality research papers are solicited in, but are not limited to, the following areas with innovative and novel contents:
-Biofuels and alternatives
-Carbon capturing and storage technologies
-Clean coal technologies
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-Energy systems
-Hybrid/combined/integrated energy systems for multi-generation
-Hydrogen energy and fuel cells
-Hydrogen production technologies
-Micro- and nano-energy systems and technologies
-Nuclear energy
-Renewable energies (e.g. geothermal, solar, wind, hydro, tidal, wave, biomass)
-Smart energy system