Life Cycle Economic Costs Research Articles

Multi-objective particle swarm optimization algorithm based on multi-strategy improvement for hybrid energy storage optimization configuration

In order to fully leverage the advantages of hybrid energy storage systems in mitigating voltage fluctuations, reducing curtailment rates of wind and solar power, minimizing active power losses, and enhancing power quality within distributed generation systems, while effectively balancing the economic and security aspects of the system, this paper establishes a multi-objective hybrid energy storage optimization configuration model that comprehensively considers the lifecycle economic costs, node voltage deviations, and system active power losses. To address the limitations of single-objective solution algorithms and the lack of diversity and premature convergence in multi-objective optimization processes, a multi-objective particle swarm optimization by multi-strategy improvements (CMOPSO-MSI) is proposed to solve the model. By introducing adaptive grid crowding distance and roulette wheel selection strategies to dynamically update the Pareto solution set, population uniformity and diversity are ensured. An improved dynamic nonlinear weighting strategy is introduced to enhance the algorithm's global search capability and convergence performance. A Gaussian mutation strategy is incorporated into the iteration process to enhance the uniformity of non-dominated solutions and particle search capabilities The aim is to achieve an optimal balance between the configuration cost and stability of hybrid energy storage systems. A simulation analysis under multiple cases is performed, taking an IEEE 33-node power distribution system as an example, with introducing photovoltaic and wind energy sources. The results demonstrate that the proposed algorithm achieves better Pareto frontiers and convergence performance compared to conventional multi-objective particle swarm optimization algorithms MOPSO, and classical multi-objective optimization algorithm NSGA-II, validating the effectiveness and accuracy of the proposed model and algorithm strategies in solving the hybrid energy storage optimization configuration problems. The approach concurrently considers system economics and grid stability while improving power quality.

Assessing the prospect of bio-methanol fuel in China from a life cycle perspective

Along with rapid industrial development, China has become the world’s largest energy consumer and CO2 emitter. In recent years, bio-methanol has been used as one of the low-carbon alternative energy sources in the transportation sector. This study assessed the development prospects of bio-methanol fuel with corn straw as a common feedstock in China in terms of energy consumption, environmental emissions, and economic costs based on life cycle assessment. In this study, the life cycle of bio-methanol fuel was divided into three stages: biomass growth, biomass collection, and methanol production. The results showed that the energy consumption of methanol extracted from biomass was 51.02 × 104 MJ/ton, CO2 emission was 667.53 kg/ton, and the economic cost was $502.0/ton (UD$ in 2022). Compared with coal-to-methanol fuel, although the life cycle economic cost was increased by 24.46%, the CO2 emission was reduced by 59.39%. If the bio-methanol fuel is applied to the marine industry, which currently has high carbon emissions and operating costs, the carbon emissions could be reduced by 54.01% per km, and the economic cost could be saved by 14.81% per km compared to the conventional diesel fuel. Some policy recommendations for developing bio-methanol in China are provided in the end.

Resilience and sustainability-informed probabilistic multi-criteria decision-making framework for design solutions selection

In this paper, a novel probabilistic multi-criteria decision-making (MCDM) framework for sustainable and resilient building design solutions selection is developed to optimize alternatives or rehabilitation strategies in a life cycle context. The proposed framework holistically takes into account the buildings' resilience metrics, environmental sustainability, and energy consumption. The life cycle economic cost, global warming potential (GWP), primary energy use (PEU), and social impact are used to represent the buildings’ resilience and sustainability. The second-generation Performance-based Earthquake Engineering procedure and FEMA P-58 method for time-based seismic performance analyses are used to evaluate earthquake-induced impact. The whole-building energy modeling (BEM) is adopted to assess energy use during the operational phase. In addition, life cycle analysis (LCA) and life cycle cost analysis (LCCA) are carried out to assess the life cycle performance of different design alternatives regarding environmental impacts and cost, respectively. Aiming to consider the various uncertainties in the decision-making process, a novel MCS-MCDM method is developed by combining the Monte Carlo simulation (MCS) with the traditional MCDM method. The proposed framework is applied to analyze hypothetical cases considering different geographic locations, structural systems, and building envelope systems, and recommendations are given according to the analysis results. The case study demonstrates the advantages of the proposed framework over traditional frameworks and its guidance for architectural design decisions.

Incorporating Flood Hazards into Pavement Sustainability Assessment

The functional and structural performance of pavement infrastructures are at risk from climate change impacts. However, past sustainability assessment studies do not consider how the performance of infrastructure will be affected by a changing climate. The goal of this research is to investigate the impacts of flooding in a unified assessment of the resilience and sustainability of pavement. A case study of concrete pavement was evaluated for scenarios with and without flooding. The AASHTOWare Pavement ME design program was used to simulate the structural performance of typical jointed plain concrete pavement (JPCP) designs for collector roads in Canada. Predicted performance was used in the resilience and sustainability assessment under scenarios with and without flooding. The damage ratio and cost of damage were assessed to quantify the resilience of concrete pavement to floods. Life cycle costs and environmental impacts were compared across a climate change scenario with consideration of maintenance and rehabilitation activities. Results reveal that a typical Ontario JPCP design with structural slab thickness < 200 mm is less resilient than the Manitoba design for collector roads, but the 25 mm slab thickness difference in Manitoba design can lead to 50% change in damage ratio and damage cost. When estimating the social cost associated with greenhouse gas and air pollutant emissions, the additional environmental impact resulting from flooding for the Ontario road is almost seven times that of the Manitoba road. However, the life cycle economic cost and environmental impact do not yield an overall benefit with increased slab thickness.

Unit-level cost-benefit analysis for coal power plants retrofitted with biomass co-firing at a national level by combined GIS and life cycle assessment

To avoid the irreversible impact of global climate change on human society, many countries have recently put forward ambitious goals to accelerate the low-carbon transition of energy systems. Among low-carbon measures, retrofitting existing coal power plants with biomass co-firing is regarded as a promising cost-efficient option to mitigate greenhouse gas and air pollutant emissions. However, the life-cycle economic cost or environmental benefit of this coal-to-biomass retrofit is not identical for various types of power plants in different regions. To facilitate a more efficient biomass utilization strategy in an energy system, it is necessary to carry out a large-scale and high-resolution cost-benefit assessment for the co-firing of biomass and coal in retrofitted plants. Taking China as an example, this study utilized a bottom-up approach and geographic information system, combined with the latest available datasets, to develop a unit-level cost-benefit analysis framework for the coal-to-biomass transition. The results indicate that the coal-to-biomass retrofit costs US$18.3–73.0 for each ton of carbon reduction, and US$21.6–806.5 for each kg of SO2 reduction, at a 25% blending ratio. Installed capacity, operating year, and transportation distance are important influencing factors of cost-benefit heterogeneity. The priority of power unit retrofitting in terms of carbon reductions mainly depends on the cost preference, while that for SO2 reduction is mainly determined by benefit preference. The analytical framework proposed in this study can be used in other countries to formulate an efficient biomass development strategy.

Green infrastructure life cycle assessment: A bio-infiltration case study

This paper presents life cycle assessment (LCA) as a methodology to evaluate environmental, economic, and social performance of green infrastructure stormwater control measures (SCMs). A case study examining a bio-infiltration rain garden at the Villanova University Campus is offered to demonstrate this methodology. The scope of this analysis is cradle to grave benefits and impacts of green infrastructure. Metrics used in this case study to evaluate benefits and impacts include carbon footprint (global warming potential), acidification potential, human health cancer impact, human health non-cancer impact, respiratory effects, eutrophication potential, ozone depletion potential, eco-toxicity, smog formation potential, labor impacts, and life cycle economic costs. Results of this bio-infiltration rain garden case study show that the construction phase is the main contributing life cycle phase for all adverse environmental impacts, as well as total life cycle cost and labor impacts. The majority of these construction phase environmental impacts are attributed to the use of silica sand as a soil amendment for the rain garden media and the use of bark mulch to provide ground cover, repress invasive vegetation, and establish target vegetation. The bio-infiltration rain garden operation phase was found to provide significant avoided environmental impacts relative to the construction phase impacts. These avoided impacts are attributed to urban forest benefits from rain garden vegetation, benefits due to stormwater runoff pollutant treatment by the practice, and benefits to combined sewer systems due to reduced stormwater volume through infiltration and evapo-transpiration. Consideration of multiple rain garden decommissioning phase scenarios makes a case to support the onsite reuse on rain garden media at the end of the practice life.