Design–operation optimisation of run-of-river power plants

Author:

Bozorg Haddad Omid1,Moradi-Jalal Mahdi2,Mariño Miguel A.3

Affiliation:

1. Department of Irrigation & Reclamation Engineering, College of Agriculture & Natural Resources, University of Tehran, Karaj, Tehran

2. Department of Civil Engineering, University of Toronto, Toronto, ON, Canada

3. Hydrology Program, Department of Civil & Environmental Engineering and Department of Biological & Agricultural Engineering, University of California, Davis, CA, USA

Abstract

This paper addresses a strategy for the optimal design, control and operation of small hydropower (run-of-river (RoR) power) plants with the honey bee mating optimisation (HBMO) algorithm, while taking into account optimal design of the associated penstock as well as the turbines' number, type and their operation in the system. Civil engineering and electromechanical cost-effectiveness and constraints in an expected stream flow are also considered. The optimisation is driven by an objective function that includes the annual difference between generated energy, operating costs and depreciation costs for both initial investment and operation costs, considering various performance and hydraulic constraints. The HBMO algorithm specifies the annual benefit of generated energy and simultaneously determines the annualised operating cost. The solution includes selection of turbine types, number of turbines, penstock diameter, as well as scheduling the operation of an RoR power plant that results in maximum annualised benefit for a given set of river inflow histograms. The results of the proposed algorithm, which are compared with those of an analytical approach using Lagrange multipliers (LM), highlight the advantages in design, effective operation, ease of application and capability of the proposed HBMO algorithm for solving complex problems of this type.

Publisher

Thomas Telford Ltd.

Subject

Water Science and Technology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3