High Construction Costs Research Articles

A Numerical Analysis of the Role of Pile Foundations in Shaft Sinking Using the Vertical Shaft Sinking Machine (VSM)

The use of the Vertical Shaft Sinking Machine (VSM) for shaft construction marks a significant advancement in modern technology and is recognized as one of the leading techniques in the field. However, much of the existing research focuses on mechanical and technical challenges, often overlooking the effects on surrounding soil and the structural integrity of shafts. This study demonstrates that increasing pile diameter by 20% improves load-bearing capacity by 15% and reduces soil settlement by 12%, though these improvements come with higher construction costs. Additionally, larger diameters improve lateral stability, but excessively long piles lead to diminishing returns. To address the limited research on reinforcement design in soft soils, a series of numerical models were employed to investigate the effects of pile spacing, length, and diameter on surrounding soil behavior. This in-depth analysis aims to provide a scientific foundation for optimizing VSM technology in caisson pile foundations, particularly in soft-soil conditions.

The design of a model predictive control strategy and performance analysis for pumped storage units and super capacitors in power systems

IntroductionSuper capacitors were regarded as one of the most effective frequency regulation technologies in power systems. The major issue of applying super capacitors for frequency regulation is the limited energy capacity and the high construction costs. The pumped storage units have been developed and applied in power systems for decades, whereas it was rarely operated to regulate the system frequency due to the operation limitations. The pumped storage units could be operated as a hydro generator under the generation mode and provide effective frequency regulation service with the conventional automatic generation control (AGC) system while its output power was constant under the pumping mode.MethodIn this paper, the pumped storage unit was controlled to participate in frequency regulation under the generation mode with super capacitors. Considering the AGC system could not consider the state of charging (SOC) of super capacitors for frequency regulation, an optimization model was proposed to determine the operation points for super capacitors and pumped storage units under a model predictive control (MPC) strategy to regulate the system frequency for power systems.Results and DiscussionBased on the various operation scenarios, the effectiveness and costs of pumped storage units and super capacitors to provide frequency regulation services were discussed. It was indicated that pumped storage units and super capacitors were effective technologies for power systems.

Predicting Subsurface Drainage Requirement for Different Soil Desalinization Goals in Coastal Reclamation Areas

ABSTRACTBuilding subsurface drainage systems for more efficient salt leaching with the natural rainfall or artificial irrigation is a widely accepted practice for saline soils reclamation, but the high initial cost of the system construction often limits its adoption, and the uncertainty in drainage intensity requirement to meet desired desalinization goals for field crop production challenges the system design. In this paper, we proposed a soil desalinization model based on the field hydrology model‐DRAINMOD, predicted number of years required to lower soil salinity to a threshold level under different subsurface drainage conditions, and estimated the net return from different subsurface drainage system layout based on a case study in a coastal reclamation area in eastern China. The results showed that, DRAINMOD accurately predicted water table fluctuations in artificially drained fields: the root mean square error to standard deviation ratio (RSR) was 0.4 and 0.54, and the Nash Sutcliffe efficiency (NSE) was 0.84 and 0.68, respectively, during the model calibration and validation periods. The DRAINMOD based soil desalinization model predicted a negative relationship between subsurface drainage intensity and the soil desalinization period, that is, improving drainage condition shortened the time requirement for soil desalinization. For the study area, the model's predictions showed that installing subsurface drainage at 20 m spacing and 1.2 m deep lowered soil salinity to the slightly saline level in less than 7 years under the rainfall leaching only, and such system layout produced the maximum economic return based on the local agricultural practice. The results indicate that, early investment in adequate subsurface drainage systems is beneficial for field crop production in the salt impacted farmland areas. Findings from this research may provide technical references for saline soil reclamation or land improvement in both rain fed and irrigated agricultural areas.

Long-Term Comparative Life Cycle Assessment, Cost, and Comfort Analysis of Heavyweight vs. Lightweight Construction Systems in a Mediterranean Climate

Massive construction systems have always characterized traditional architecture and are currently the most prevalent, straightforward, and cost-effective in many Mediterranean countries. However, in recent years, the construction industry has gradually shifted towards using lightweight, dry construction techniques. This study aims to assess the effects on energy consumption, comfort levels, and environmental sustainability resulting from the adoption of five high-performance construction systems in a multi-family residential building: (i) reinforced concrete structure with low-transmittance thermal block infill; (ii) reinforced concrete structure with light-clay bricks and outer thermal insulation; (iii) steel frame; (iv) cross-laminated timber (CLT); (v) timber-steel hybrid structure. To achieve this goal, a multidisciplinary approach was employed, including the analysis of thermal parameters, the evaluation of indoor comfort through the adaptive model and Fanger’s PMV, and the quantification of environmental and economic impacts through life cycle assessment and life cycle cost applied in a long-term analysis (ranging from 30 to 100 years). The results highlight that heavyweight construction systems are the most effective in terms of comfort, cost, and long-term environmental impact (100 years), while lightweight construction systems generally have higher construction costs, provide lower short-term environmental impacts (30 years), and offer intermediate comfort depending on the thermal mass.

Evolution mechanism of deviated well fiber-optic strain induced by single-fracture propagation during fracturing in horizontal wells

Considering the high construction cost of horizontal adjacent well monitoring and the lack of vertical adjacent well fiber optic for obtaining fracturing information, this paper proposes the use of deviated wells with fiber optics for monitoring purposes. To demonstrate the advantages of deviated well fiber optics and the feasibility of their deployment, this paper constructs a forward model based on the finite element coupled with cohesive element approach to simulate the strain induced by the propagation of a single hydraulic fracture in horizontal wells on deviated well fiber optics, and conducts a numerical simulation analysis of the strain induced by the propagation of a single hydraulic fracture on deviated well fiber optics. The results show that the strain evolution induced by single-fracture propagation in deviated well fiber optics can be divided into four stages: strain-enhancing, strain-converging, tensile strain-expanding, and linear strain-converging. The strain evolution characteristics of deviated well fiber optics are manifested as follows: a “heart-shaped” tensile strain convergence zone with a certain deviation appears in the middle, which subsequently converges into a tensile strain convergence band, with compressive strain convergence zones on both sides, and an expanding tensile strain convergence zone on the outer side of the compressive strain convergence band. The analysis finds that when the well inclination angle is greater than 45°, the strain response characteristics of deviated well fiber optics are mainly governed by the width expansion of the fracture, and when less than 45°, they are mainly governed by the height expansion of the fracture. Changes in the azimuth angle can cause a deviation of the “heart-shaped” tensile strain area and the compressive strain convergence zone in the fiber-optic strain waterfall plot, with larger deviations corresponding to smaller azimuth angles. The depth at which the deviated well fiber optics are deployed, reaching the depth of the horizontal section of the horizontal well, can reflect the upward expansion of the fracture height. The results of the analysis illustrate the advantages of deviated well fiber optics in obtaining both fracture width and height expansion information simultaneously and propose a method for selecting suitable deviated well fiber-optic construction parameters based on fracturing monitoring needs. This research can reduce the construction cost of deploying fiber optics in adjacent wells and has significant implications for guiding the layout of adjacent well fiber optics.

Towards Hydraulic Design Optimization of Shaft Hydropower Plants: A 3D-CFD Application Based on Physical Models

The shaft hydropower plant (SHPP) is a novel hydraulic concept for low-head hydropower sites with several environmental and operational advantages over conventional layouts. However, the first two projects implementing this concept have shown comparatively high construction costs and project risks. Therefore, further optimization is required to increase economic attractiveness and enable broader market adoption. Initial model tests recommend a square-shaped shaft inlet with a three-sided approach flow for low-loss and fish-friendly inflow conditions. Yet, this design requires significant space for structural implementation and may be unsuitable for use with multiple shafts or as an extension of non-powered dams and weirs. This research paper presents the application of a computational fluid dynamics simulation setup to evaluate the hydraulic performance of various design configurations, especially alternative design layouts with a one-sided approach flow without further physical model tests. The simulation setup is calibrated against observations including head loss and velocity measurements from the physical model tests, and its satisfactory performance enables the analysis of alternative design layouts. This study aims to derive the most significant design parameters for achieving the desired hydraulic conditions at the intake. Increasing the flow depth before the intake and enlarging the inlet area have the most significant impact, while increasing the overflow of the front gate has the least significant effect. The chosen CFD application is deemed suitable for hydraulic design optimization and provides guidance on the key parameters to focus on for tailored site-specific design development.

Full-scale field test of early-age behaviour of partially continuous reinforced concrete pavement

To address the damage characteristics and deficiencies of the existing continuously reinforced concrete pavement (CRCP), which are the high construction cost and irregular crack distribution patterns, a concrete pavement structure called partially continuous reinforced concrete pavement (PCRCP) is proposed. In this paper, the early-age (28 days, without traffic) behaviour of PCRCP subjected to environmental loading is investigated. To this end, full-scale field tests were carried out in Xiangjiagou Tunnel, Shanxi Province, China. Testing results showed that the PCRCP test section with the partial continuous reinforcement length of 100 cm and active crack spacing of 5 m can provide better early-age performance and lower initial construction cost in this study. The PCRCP test section with the active crack control method has a uniform crack distribution pattern with narrow width compared to the CRCP test section. The results of this study would provide data support and reference for the rational design of PCRCP.

Evolutionary Game Analysis of Collaborative Prefabricated Buildings Development Behavior in China under Carbon Emissions Trading Schemes

Prefabricated buildings (PBs) are considered a green way to reduce energy consumption and carbon emissions in the construction industry due to their environmental and social benefits. However, PBs have obstacles such as high construction costs, immature technology, and insufficient policy incentives, and developers’ willingness to develop them needs to be higher. Therefore, it is necessary to explore how to motivate more developers to develop PBs. In this paper, we first discuss the impact of the carbon emissions trading scheme (ETS) on the construction industry and then consider the heterogeneity of construction developers, introduce a collaborative mechanism to establish a three-party evolutionary game model between the government and the heterogeneous developers, and explore the evolution of the three-party dynamic strategies through numerical simulation. The results show that developers’ initial development probability affects the system’s evolutionary trend, and the developer who obtains more low-carbon benefits plays a dominant role. Further analyses show that critical factors such as market profitability, synergistic benefits, and carbon tax price positively influence the development of PBs, and the influence of synergistic cooperation mechanisms should be especially emphasized. This study provides practical insights into the sustainable development of the construction industry and the government’s development of a suitable carbon portfolio policy for it. Including the construction industry in the ETS is recommended when carbon prices reach 110 RMB/t. At this point, the government can remove the subsidy for PBs, but the behaviors of the developers who participate in the ETS still need to be supervised.

Flexural behavior and numerical simulation of reinforced concrete beams with a UHPC stay-in-place formwork

To overcome the shortcomings of traditional concrete structures such as long construction cycle, high construction cost and poor durability, seven composite beams with a UHPC stay-in-place formwork (UCB) and one reinforced concrete (RC) beam were designed. An experimental study was conducted to investigate the flexural behavior of composite beams under the static load. The research parameters include formwork thickness, reinforcement rate, and formwork surface treatment. The results revealed that roughening the surface of UHPC formwork has a positive impact on enhancing the integrity of composite beams. The utilization of UHPC stay-in-place formwork can effectively improve the stiffness, cracking load, and peak load of members. Compared with that of the RC beam, the cracking load and peak load of composite beams increased by 63% ~ 103% and 6% ~ 15%, respectively, and the yielding stiffness increased by 23% ~ 41%. Different from the RC beam, new cracks occurred on one side of the initial crack's end and continued to extend upwards rather than along the original crack. The existence of a significant quantity of tiny cracks in composite beams effectively slowed down the increase in the width of pre-existing cracks in the early stage of loading. Due to the multi-crack pattern exhibited by the UHPC formwork, the strain concentration of the steel bars was effectively mitigated. When subjected to the same load level, the strain of the longitudinal steel bars in composite beams was smaller than that of the RC beam. The formula for calculating the flexural bearing capacity of composite beams is established through theoretical analysis. In addition, the numerical model of the composite beam is established by the finite element method (FEM). The influence of the contact method of the UHPC-NC interface on the flexural performance of the composite beam is explored. The supplementary analysis of the parametric study of the reinforcement rate and the UHPC formwork thickness is carried out. When using ABAQUS for the numerical analysis of the composite beam, it is appropriate to adopt the cohesion model or the Tie model for the UHPC-NC interface, and it is not appropriate to use the Coulomb friction model.

CHARACTERISTICS OF YALIMO PAPUA KINANG JINGKION POWDER AS FILLER IN HRS-WC MIXTURE

<span lang="EN-US">Kinang Jingkion is the name of a region in Yalimo Regency, Papua, which has unique material deposits with specifications that make it suitable for use as aggregate in road pavement, including as filler in powder form. Jan Ukago, one of the first researchers on this aggregate, named the material after the region or location, so the material from the Kinang Jingkion region is now called Kinang Jingkion material. The high construction costs in the Yalimo region and generally in the Papua Mountains are caused by logistics, where materials such as cement and asphalt are mobilized using airplanes. With the alternative of using local filler material, it will eliminate long and expensive mobilization. The testing method was carried out according to the 2018 General Specifications Revision 2, Directorate General of Highways and Indonesian National Standard (SNI) for each test, including asphalt, coarse and fine aggregates, and Kinang Jingkion material. The Optimum Asphalt Content (OAC) obtained from Kinang Jingkion Filler was 6.85%. The Marshall characteristic test results for Kinang Jingkion Filler at OAC of 6.85% showed a stability value of 1194.40 Kg, MQ of 460.2 Kg/mm, VIM of 2.68%, and VFB of 80.16</span>

Modelling the predictive analysis of turbidity removal efficiency in the in-line coagulation and flocculation process

Coagulation and flocculation processes are commonly used in conventional water treatment plants to remove suspended solids from water. However, these methods often suffer from drawbacks such as high chemical consumption, sludge generation, and the need for huge areas, leading to high construction costs. To address these limitations, this study investigated the performance of in-line coagulation and flocculation processes as an alternative to conventional methods. The objectives were to determine the efficiency of in-line coagulation and flocculation, understand the underlying mechanisms, establish optimal operating conditions and design criteria, and to develop theoretical models for predicting turbidity removal efficiency in the in-line coagulation-flocculation process. Experiments were conducted using a continuous setup consisting of a static mixer and a 35-m helically coiled hydraulic tube flocculator.Various operating parameters, including water flow rate (100 – 800 L/hr), initial turbidity (20 – 200 NTU), and coagulant types (aluminum sulfate, poly aluminum chloride, aluminum chlorohydrate, and ferric chloride), were examined. The results demonstrated that aluminum sulfate was the appropriate coagulant for the water characteristics studied, and the in-line coagulation and flocculation processes achieved turbidity removal efficiencies of approximately 91 % under all operating conditions, with a notable 97 % removal efficiency achieved at a liquid flow rate of 600 L/hr, with a Gt value of 21,715 and an overflow rate of 2 m/hr. A prediction model of turbidity removal efficiency was developed, showing good agreement between experimental and predicted removal efficiency model, with an average deviation of about 20 %. This model can aid in determining optimal operating conditions and serve as a hybrid process in future water treatment systems, potentially applicable to other separation processes as well.

A novel and cost-effective model for cloud energy storage based on a dual storage setup in active distribution grid with resilience consideration

The rising occurrences of natural disasters, terrorist actions, and cyber-attacks that result in extensive, long-lasting, and expensive disruptions have necessitated a shift in focus towards the resilience of electrical grids for network operators. However, the task of designing a resilient network remains complex and costly. One potential solution to bolster resilience is the deployment of battery energy storage devices on the consumer side, known as distributed energy systems (DES). Despite its effectiveness, the high construction costs and lengthy payback period associated with investing in energy storage devices have led consumers to exhibit reluctance in adopting them. Cloud energy storage (CES) is an innovative and cost-effective solution to address those challenges. In the CES platform, investors install storage facilities in the network which can be rented by consumers to fulfill their needs and they become holders of the virtual batteries. By adopting this approach, consumers are relieved from the burden of maintenance, repair, and installation. While a single CES facility offers reduced costs and increased comfort for consumers, it compromises the resilience of the grid when compared to the Distributed Energy Storage (DES) mechanism. In order to bridge this gap, this paper proposes a dual CES model which serves as an intermediate solution between DES and single CES. The dual CES model strikes a balance between the resilience of the grid and cost-effectiveness. It provides a higher level of resilience compared to a single CES and a lower level compared to DES. Additionally, the costs associated with the dual CES model fall between that of a single CES and DES. This model not only increases the profit margin for investors but also enhances the overall comfort and well-being of consumers compared to the single CES. To validate the proposed model, a Mixed Integer Linear Programming (MILP) problem is formulated and simulated on the IEEE 33 bus network. Three cases are considered: DES, single CES, and dual CES. The results indicate that the dual CES reduces consumers' costs by 28 %, losses by 27 %, unsupplied load costs by 45 %, and return on investment by 33 %. Moreover, it increases the stability margin time by 2 intervals and improves robustness by 47 %.

Achieving Housing Affordability in the U.S. through Sustained Use of AI and Robotic Process Automation for Prefabricated Modular Construction

The rising housing issues occasioned by high costs in the United States (US) are traceable to the high costs of building materials and construction. This study proposes the combined leveraging of AI and Robotic Process Automation (RPA) for prefabricated modular construction as a strategic means of reducing high costs of housing and increasing efficiency in construction. It argues that doing so would pave way for housing affordability in the US. Deploying descriptive survey and qualitative method alongside the applicable interpretive and descriptive techniques, the study demonstrates in the course of its analysis that AI and RPA are viable means of reducing costs of construction and housing, and increasing efficiency. It submits that amidst the established constraints to the ideal extent of leveraging AI for construction activities, the leveraging of AI and RPA for prefabricated modular construction yields huge positive results among which are reduced costs of construction and housing and increased efficiency in construction. Government and construction organizations are charged to play enabling roles in the adoption and sustainability of AI and RPA in construction activities, including prefabricated modular construction, so as to achieve reduced costs of housing and increase efficiency in construction.

Optimization strategies for carbon neutrality in a maize-soybean rotation production system from farm to gate

Agricultural food production stands as a primary source of global greenhouse gas emissions, with residue management widely acknowledged as an effective avenue to achieve carbon neutrality. However, there is a lack of comprehensive assessment of the carbon footprint of agricultural residue production, processing, and recycling from farm to gate. Here we conducted a hybrid approach that integrated the DeNitrification-DeComposition (DNDC) model and life cycle carbon footprint to co-optimize water and residue management, targeting carbon neutrality and yield increase. The results revealed that controlled drainage with sub-irrigation (CDSI) served as a potent water management strategy to mitigate greenhouse gas emissions (15.65 %) while increasing yield (24.34 %) compared to free drainage. Regardless of the type of bioproduct, incorporating CDSI with downstream residue utilization exhibited substantial potential for carbon-negative emissions, reducing the average farm carbon footprint to −1538.15 kg CO2 eq yr−1. Among those scenarios, the CDSI with bioethanol scenario particularly stands out with its robust carbon mitigation capability (−1994.94 kg CO2 eq yr−1), driven by the enormous energy demand throughout the agricultural production process and the environmental friendliness of bioethanol, which substantially exceeds that of gasoline. However, challenges such as high plant construction costs and extended investment payback periods associated with residue conversion underscore the need for the urgent establishment of national subsidies and market mechanisms to foster carbon neutrality in agricultural production.

Seasonal large-scale thermal energy storage in an evolving district heating system – Long-term modeling of interconnected supply and demand

Given the strong seasonal nature of heating demands, peak heat is important during colder seasons. Instead of peak heat plants, seasonal large-scale thermal energy storage (TES) could be utilized. These can be charged during warmer seasons and discharged when required, decreasing the need for peak heat plants. Systems modelling studies on seasonal TES are lacking. Thus, a long-term local energy system model is applied under different scenarios to investigate the potential roles of seasonal TES in an evolving heating system. The results show that seasonal TES is economically viable for: all future electricity price cases for low TES construction costs, corresponding to repurposing of underground oil storages, and for most electricity price cases for mid- and high construction costs, corresponding to new underground excavations. Seasonal TES mainly decrease the investments in and usage of electric boilers or biogas boilers, while increase the utilization of heat pumps. Other technologies may be affected depending on the future trajectory of electricity price developments. The size of the TES is between 3 and 7% of the annual district heating heat demand, depending on construction cost and electricity price development. The expansion of district heating into new housing is mostly unaffected by the availability of TES.

Cost-Related Drivers and Barriers of Passivhaus: A Systematic Literature Review

Passivhaus (PH) has gained global recognition for its energy-efficient features despite a 5% to 10% higher construction cost than traditional houses, especially within European countries. However, its adoption and popularity have not met the same fate in other countries like New Zealand. The higher upfront cost has been critical to the slow adoption of the PH movement in New Zealand. This study aimed to demystify the mist around the cost of PHs with a focus on the effects of drivers and barriers on their life cycle costs (LCCs). As such, a systematic literature review was conducted to provide a comprehensive understanding of the cost implications associated with PH. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) review method, we examined 71 past studies on PHs from 2005 to 2023. We found that the drivers of PHs include reduced heating demand, increased thermal comfort, and indoor air quality (IAQ). Research showed that the rising market for PHs is fueled by climate change, environmental awareness, innovative materials and technologies, individual commitment, improved regulations, pilot studies, research efforts, and governmental funding and initiatives. However, PHs face significant challenges such as increased complexity, advanced technology, higher initial investments compared to conventional and low-energy houses, national requirements, overheating, difficulties in affording the technologies, and a lack of options in the market. Despite the wealth of research on the economic aspects of PH, there is a lack of in-depth studies exploring the LCC of PHs focusing on cost commitments and benefits. Such studies are essential for assessing and optimising the cost-effectiveness of PH, considering different climates and regions, and comparing them with other low energy standards. The findings of our review provide a crucial focus for PH stakeholders in assessing the long-term financial viability of PH projects, thereby improving decision-making and facilitating effective planning for sustainable and cost-effective housing.

Effect of Supporting Carbon Fiber Anode by Activated Coconut Carbon in the Microbial Fuel Cell Fed by Molasses Decoction from Yeast Production

A microbial fuel cell (MFC) is a bioelectrochemical system that generates electrical energy using electroactive micro-organisms. These micro-organisms convert chemical energy found in substances like wastewater into electrical energy while simultaneously treating the wastewater. Thus, MFCs serve a dual purpose, generating energy and enhancing wastewater treatment processes. Due to the high construction costs of MFCs, there is an ongoing search for alternative solutions to improve their efficiency and reduce production costs. This study aimed to improvement of MFC operation and minimize MFC costs by using anode material derived from by-products. Therefore, the proton exchange membrane (PEM) was abandoned, and a stainless steel cathode and a carbon anode were used. To improve the cell’s efficiency, a carbon fiber anode supplemented with activated coconut carbon (ACCcfA) was utilized. Micro-organisms were provided with molasses decoction (a by-product of yeast production) to supply the necessary nutrients for optimal functioning. For comparison, an anode made solely of carbon fibers (CFA) and an anode composed of activated carbon grains without carbon fibers (ACCgA) were also tested. The results indicated that the ACCcfA system achieved the highest cell voltage, power density, and COD reduction efficiency (compared to the CFA and ACCgA electrodes). Additionally, the study demonstrated that incorporating activated coconut carbon significantly enhances the performance of the MFC when powered by a by-product of yeast production.

Machine Learning-Powered Earthquake Early Warning System

The most devastating natural disasters on earth are earthquakes that causes long-term effects on geography, civilization, and human life. These unpredictable events pose a serious threat to infrastructure. Furthermore, the current Earthquake Early Warning (EEW) systems are facing issues such as limited warning times, false alarms, maintenance costs, high construction costs, and data interpretation. Highlighting these as an urgent need for mitigation measures, there is a need to improve the effectiveness of electronic alerts and public safety measures. For this transformative machine learning techniques and the integration of disparate data, can embark on creating social security and lives protecting from major environmental disasters like earthquakes. This paper has compared various Machine Learning (ML) techniques by training them by using two datasets: one from India and another from India United States Geological from Research World Database to improve the robustness and generality of the earthquake prediction model in the Earthquake Early Warning (EEW) framework. This represents a major advance for earthquake detection and promises to reduce response time. Among various ML Techniques, Random Forest has performed well in earthquake warning with 96.06% accuracy and 98.6% precision.

Assessment of low-cost housing provision as government social responsibility towards achievement of sustainable development goal 11: stakeholders’ perspective

Studies show that the government’s role can improve low-cost housing (LCH) to achieve SDGs linked with housing. LCH provision as a government social responsibility to achieving Goal 11 may raise critical issues in Malaysia. Therefore, this study investigated the factors hindering Malaysia’s Government from providing LCH as a social responsibility to achieving Goal 11. The research adopted a qualitative approach via phenomenology. It covered four major cities in Malaysia and achieved saturation at the 35th selected participant. Findings reveal that housing provision for all Malaysia’s low-income earners (LIEs) is an issue. The complexity of the problems, such as government inadequate funding, housing market financialisation, faulty LCH registration system, LCH high development and construction cost, under-declaration of household income by an unqualified person, LIEs collateral lacking, inability to provide 10% down payment, reluctance by mortgage institutions to lend loans to LIEs, entitlement syndrome, and inadequate LCH data sharing between federal and states governments may hinder Malaysia’s Government alone from LCH provision as a social responsibility to the low-income groups. Findings show that achieving Goal 11 may be threatened if these issues are not addressed and suggest measures to improve LCH to achieve Goal 11 via all-inclusive mechanisms.

Distributed Energy Dispatch for Geo-Data Centers Port Microgrid

With the development of port automation and artificial intelligence, coordination with multi-geographic data centers (Geo-DCs) has become a viable solution to address the issue of limited port computing resources. This study proposes a distributed energy dispatch method for the port microgrid coordinated with Geo-DCs (Geo-DCPM), aimed at reducing port carbon emissions and operational costs. Consider the single point of failure problem and high construction costs of centralized data centers. Geo-DCs are first introduced to solve the problem of insufficient computing resources in ports. An energy consumption calculation model for Geo-DCs is established, considering the data load delay constraint and the data space transfer constraint caused by specific delay-sensitive loads in the port microgrid. Then, an energy dispatch model (EDM) is constructed for the Geo-DCPM, taking into account carbon capture costs. Moreover, based on mixed-integer linear programming, a distributed algorithm is proposed to solve the EDM problem. Finally, the simulation results verify the effectiveness of the proposed method. Compared with the centralized algorithm, the packet loss rate of the distributed algorithm combined with Geo-DCs is significantly lower, reduced by about 70%.