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Article
Publication date: 15 May 2024

Bashar Shboul, Mohamed E. Zayed, Hadi F. Marashdeh, Sondos N. Al-Smad, Ahmad A. Al-Bourini, Bessan J. Amer, Zainab W. Qtashat and Alanoud M. Alhourani

This paper aims to assess the economic, environmental, policy-related and social implications of establishing green hydrogen production in Jordan.

Abstract

Purpose

This paper aims to assess the economic, environmental, policy-related and social implications of establishing green hydrogen production in Jordan.

Design/methodology/approach

The comprehensive analysis has been investigated, including economic assessments, environmental impact evaluations, policy examinations and social considerations. Furthermore, the research methodology encompasses energy demand, sector, security and supply analysis, as well as an assessment of the availability of renewable energy resources.

Findings

The results indicate substantial economic benefits associated with green hydrogen production, including job creation, increased tax revenue and a reduction in energy imports. Additionally, the study identifies positive environmental impacts, such as decreased greenhouse gas emissions and air pollution. Noteworthy, two methods could be used to produce hydrogen, namely: electrolysis and thermochemical water splitting. As a recommendation, the study proposes that Jordan, particularly Aqaba, take proactive measures to foster the development of a green hydrogen industry and collaborate with international partners to exchange best practices and establish the necessary infrastructure.

Originality/value

To the best of the authors’ knowledge, this paper is among the first to provide a comprehensive perspective on the potential of green hydrogen production as a driving force for Jordan’s economy, while also benefiting the environment and society. However, the research recognizes several challenges that must be addressed to materialize green hydrogen production in Jordan, encompassing high renewable energy costs, infrastructure development requirements and community concerns. Despite these obstacles, the study asserts that the potential advantages of green hydrogen production outweigh the associated risks.

Details

International Journal of Energy Sector Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-6220

Keywords

Article
Publication date: 13 May 2024

Vu Hong Son Pham, Nghiep Trinh Nguyen Dang and Nguyen Van Nam

For successful management of construction projects, a precise analysis of the balance between time and cost is imperative to attain the most effective results. The aim of this…

Abstract

Purpose

For successful management of construction projects, a precise analysis of the balance between time and cost is imperative to attain the most effective results. The aim of this study is to present an innovative approach tailored to tackle the challenges posed by time-cost trade-off (TCTO) problems. This objective is achieved through the integration of the multi-verse optimizer (MVO) with opposition-based learning (OBL), thereby introducing a groundbreaking methodology in the field.

Design/methodology/approach

The paper aims to develop a new hybrid meta-heuristic algorithm. This is achieved by integrating the MVO with OBL, thereby forming the iMVO algorithm. The integration enhances the optimization capabilities of the algorithm, notably in terms of exploration and exploitation. Consequently, this results in expedited convergence and yields more accurate solutions. The efficacy of the iMVO algorithm will be evaluated through its application to four different TCTO problems. These problems vary in scale – small, medium and large – and include real-life case studies that possess complex relationships.

Findings

The efficacy of the proposed methodology is evaluated by examining TCTO problems, encompassing 18, 29, 69 and 290 activities, respectively. Results indicate that the iMVO provides competitive solutions for TCTO problems in construction projects. It is observed that the algorithm surpasses previous algorithms in terms of both mean deviation percentage (MD) and average running time (ART).

Originality/value

This research represents a significant advancement in the field of meta-heuristic algorithms, particularly in their application to managing TCTO in construction projects. It is noteworthy for being among the few studies that integrate the MVO with OBL for the management of TCTO in construction projects characterized by complex relationships.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 21 February 2024

Mohammad Esmaeil Nazari and Zahra Assari

This study aims to solve optimal pricing and power bidding strategy problem for integrated combined heat and power (CHP) system by using a modified heuristic optimization…

Abstract

Purpose

This study aims to solve optimal pricing and power bidding strategy problem for integrated combined heat and power (CHP) system by using a modified heuristic optimization algorithm.

Design/methodology/approach

In electricity markets, generation companies compete according to their bidding parameters; therefore, optimal pricing and bidding strategy are solved. Recently, CHP units are significantly operated by generation companies to meet power and heat, simultaneously.

Findings

For validation, it is shown that profit is improved by 0.04%–48.02% for single and 0.02%–31.30% for double-sided auctions. As heat price curve is extracted, the simulation results show that when CHP system is integrated with other units results in profit increase and emission decrease by 3.04%–3.18% and 2.23%–4.13%, respectively. Also, CHP units significantly affect bidding parameters.

Originality/value

The novelties are pricing and bidding strategy of integrated CHP system is solved; local heat selling is considered in pricing and bidding strategy problem and heat price curve is extracted; the effects of CHP utilization on bidding parameters are investigated; a modified heuristic and deterministic optimization algorithm is presented.

Details

International Journal of Energy Sector Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-6220

Keywords

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