Multi-objective-based economic and emission dispatch with integration of wind energy sources using different optimization algorithms

IF 2.6 4区 工程技术 Q3 ENERGY & FUELS
R. Lalhmachhuana, Subhasish Deb, Subir Datta, Ksh. Robert Singh, Umit Cali, Taha Selim Ustun
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Abstract

In this work, a study of economic and emission dispatch issues based on the multi-objective optimization is solved, and generation costs and emissions are reduced by utilizing multi-objective optimization techniques. This optimization is carried out in an IEEE-30 bus system, with and without the integration of wind energy sources, with equality and inequality constraints. The equality constraints are the power balance constraints, stipulating that to have an optimal solution, the generated power must be adequate to satisfy the load demand plus losses. The inequality constraints are a collection of limitations for active power generation, reactive power generation, generator bus voltage, and load bus voltage. To track the hourly load demand, a daily load profile is established using the IEEE-30 bus system. The generation costs and emissions in the system are optimized using multi-objective particle swarm optimization and multi-objective Ant–Lion Optimization approaches. In order to determine the goals’ minimum values, a fuzzy min–max technique is applied. The values that have been minimized are then compared to determine how well wind energy integration has reduced the generation costs and emissions. Two case studies are performed in this work. For Case 1, the total generation costs and emissions using MOPSO are less, with a difference of $42.763, while MOALO has lower emissions, with a difference of 157.337 tons. For Case 2, with the implementation of wind energy, MOPSO has lower total generation costs, with a difference of $51.678, and lower emissions, with a difference of 459.446 tons.
基于多目标的经济和排放调度,使用不同的优化算法整合风能资源
在这项工作中,基于多目标优化对经济和排放调度问题进行了研究,并利用多目标优化技术降低了发电成本和排放。该优化是在一个 IEEE-30 总线系统中进行的,该系统有风能集成和无风能集成,有平等和不平等约束。相等约束条件是电力平衡约束条件,规定要获得最佳解决方案,发电量必须足以满足负载需求加上损耗。不等式约束是对有功发电、无功发电、发电机母线电压和负载母线电压的一系列限制。为了跟踪每小时的负荷需求,使用 IEEE-30 总线系统建立了日负荷曲线。使用多目标粒子群优化和多目标蚁狮优化方法对系统中的发电成本和排放进行优化。为了确定目标的最小值,采用了模糊最小最大技术。然后对最小值进行比较,以确定风能集成在降低发电成本和排放方面的效果。这项工作进行了两个案例研究。对于案例 1,使用 MOPSO 的总发电成本和排放量较低,两者相差 42.763 美元,而 MOALO 的排放量较低,两者相差 157.337 吨。对于情况 2,在使用风能的情况下,MOPSO 的总发电成本更低,差额为 51.678 美元,排放量更低,差额为 459.446 吨。
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来源期刊
Frontiers in Energy Research
Frontiers in Energy Research Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
3.90
自引率
11.80%
发文量
1727
审稿时长
12 weeks
期刊介绍: Frontiers in Energy Research makes use of the unique Frontiers platform for open-access publishing and research networking for scientists, which provides an equal opportunity to seek, share and create knowledge. The mission of Frontiers is to place publishing back in the hands of working scientists and to promote an interactive, fair, and efficient review process. Articles are peer-reviewed according to the Frontiers review guidelines, which evaluate manuscripts on objective editorial criteria
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