Life Cycle Cost Optimization Research Articles

A Proof-of-Concept of a Reliability-Based Life-Cycle Cost Optimization Framework for Activated Sludge Processes

Wastewater treatment plants need their reliability to be properly assessed to preserve society’s health and availability of water resources. To date, no wastewater treatment plant framework comprehends the reliability of the system, considering the influence of uncertain parameters, and the total costs during the lifespan of the project. Here, an innovative framework combining a reliability analysis, a reliability-sensitivity analysis, and a life-cycle cost assessment is presented as a proof-of-concept tool for reliability-based life-cycle cost optimization of an activated sludge process due to its common application in sanitation worldwide. The results indicate (1) great variability of the reliability scenario due to the influent loads, (2) the sludge volumetric index exerts the most influence on the system’s reliability and risk expenditures, and (3) an optimum scenario associated with the lowest life-cycle cost and an annual failure rate of 19 day of failure year−1 can be obtained via an exhaustive simulation protocol. The framework demonstrates to be a promising tool for techno-economic analysis of activated sludge processes, as well as to optimize project expenditures based on its reliability to withstand different influent loads. This proof-of-concept optimization framework is expected to find multiple applications not only in sanitation and water treatment but also in other industries while supporting sustainable development goals.

Optimization and comparison of multiple solar energy systems for public sanitation service buildings in Tibet

Qinghai Tibet Plateau, known as ‘Roof of the World’, is the highest and largest plateau on Earth, with an average elevation of 4900 m and spanning nearly two-thirds the size of the European continent. The energy consumption characteristics of public sanitation service buildings in the Qinghai Tibet Plateau are significantly different from traditional public buildings. It has unique advantages that allow these facilities to use the local enriched solar energy resources to meet the energy demand. This study proposes eight potential solar energy system schemes to obtain a suitable solar energy supply system and design an optimization method for public sanitation service buildings. The optimization models aimed at the life cycle cost for each solar energy system are established, and the equipment capacity in the system is optimized and simulated. Firstly, the optimized life cycle cost and equipment capacity of different solar energy system are compared and analyzed. Then, the short-term dynamic operation performance and the system's energy conservation, economic and CO2 emission reduction performance are comprehensively analyzed. Finally, the sensitivities of economic parameters and equipment price to the system optimization results are analyzed. The results indicate that the life cycle cost of the integrated solar hot water and heat storage system is 43% lower than that of the standalone solar hot air heat supply system and the standalone photovoltaic system. An optimized integrated system consisting of photovoltaic, photothermal, thermal storage, and power storage has the best comprehensive performance. The annual energy saving ratio of the integrated system is ∼85%, and the life cycle cost saving rate is about 50%. In addition, the sensitivity analysis shows that the electricity price is the most significant factor for life cycle cost compared to the annual interest and inflation rates. The price of a solar collector and air source heat pump have the most significant impact on the life cycle cost optimization results of a photovoltaic-photothermal-thermal and power storage integrated system.

Evaluation of anticipated post-fire repair cost for resilient design of composite slab panels

The design limit states form the basis of current structural fire design approaches. These design practices overlook the post-fire resilience and repairability of the structure. Consequently, a minor fire might lead to an irreparable structure and a need of demolishing it. We propose a framework to evaluate during the design phase the anticipated repair cost for a structure in case of a fire event, in order to enable consideration of post-fire resilience in design decisions. We apply the framework to evaluate the repair cost for a composite slab panel comprising a concrete slab, two girder and two boundary beams at opposite edges, and two central beams at the center. Two fire designs for the composite slab panel satisfying the nominal fire design requirement are considered: a prescriptive design and a performance-based design which harnesses tensile membrane action and omits insulation on central beams. The repair costs are evaluated and compared for both designs for a range of natural fire exposures, demonstrating that the performance-based design achieves its target of stability during fire, but also results in higher anticipated post-fire damages. This concept of pre-evaluation of repair cost can further be implemented in life-cycle cost optimization procedures to allow an optimized structural design.

Life cycle optimisation of building retrofitting considering climate change effects

NoveltyClimate change has significant impacts on building energy performance. A novel life cycle optimisation strategy is developed for determining optimal retrofitting solutions for office buildings with climate change effects taken into consideration. The first innovation is that a hybrid genetic algorithm and artificial neural network model is developed to estimate future heating and electrical energy demands. The second innovation is that performance of integrated retrofitting measures under climate change conditions is evaluated. The third innovation is that life cycle cost optimisation is conducted using future weather profiles, while the energy usage and carbon footprint of the retrofitted building over its whole life span is evaluated. MethodologyThe proposed life cycle optimisation strategy is implemented on two campus buildings in Bristol, the United Kingdom. The historical weather profile and energy consumption data during the past two years is collected to develop and train the hybrid energy prediction model. The future weather profile, including air temperature, relative humidity, precipitation rate, solar radiation, wind speed and cloud percentage, is projected using the HadCM3 model. The collective performance of various passive, active and renewables retrofitting options is investigated. Major results and future applicationIt is found that there exists a distinct discrepancy between optimal retrofitting solutions determined using the current and future weather conditions. Moreover, there would be at most 4.7% over-estimation or 54.7% under-estimation of lifetime cost, energy and carbon if the selected optimal retrofitting solution from current weather conditions is adopted under climate change conditions. Therefore, the proposed framework can provide a meaningful guideline in determining appropriate retrofitting solutions and supporting energy efficiency policies to achieve net-zero by 2050.

Mass, Direct Cost and Energy Life-Cycle Cost Optimization of Steel-Concrete Composite Floor Structures

This paper presents a study showing the optimization of the mass, direct (self-manufacturing) costs, and energy life-cycle costs of composite floor structures composed of a reinforced concrete slab and steel I-beams. In a multi-parametric study, mixed-integer non-linear programming (MINLP) optimizations are carried out for different design parameters, such as different loads, spans, concrete and steel classes, welded, IPE and HEA steel profiles, and different energy consumption cases. Different objective functions of the composite structure are defined for optimization, such as mass, direct cost, and energy life-cycle cost objective functions. Moreover, three different energy consumption cases are proposed for the energy life-cycle cost objective: an energy efficient case (50 kWh/m2), an energy inefficient case (100 kWh/m2), and a high energy consumption case (200 kWh/m2). In each optimization, the objective function of the structure is subjected to the design, load, resistance, and deflection (in)equality constraints defined in accordance with Eurocode specifications. The optimal results calculated with different criteria are then compared to obtain competitive composite designs. Comparative diagrams have been developed to determine the competitive spans of composite floor structures with three different types of steel I beam: those made of welded sections and those made of IPE or HEA sections, respectively. The paper also answers the question of how different objective functions affect the amount of the calculated costs and masses of the structures. It has been established that the higher (more wasteful) the energy consumption case is, the lower the obtained masses of the composite floor structures are. In cases with higher energy consumption, the energy life-cycle costs are several times higher than the costs determined in direct cost optimization. At the end of the paper, a recommended optimal design for a composite floor system is presented that has been developed on the multi-parametric energy life-cycle cost optimization, where the energy efficient case is considered. An engineer or researcher can use the recommendations presented here to find a suitable optimal composite structure design for a desired span and uniformly imposed load.

Optimization of pipeline lifecycle cost using alternatives with different life spans

Abstract This paper suggests a pipeline project optimization approach that compares alternatives with different life spans. The average inflation rate is used to project the future maintenance, operation and replacement costs. The average interest rate is used to express all the costs in Equivalent Real Annual Cost (ERAC), which is the correct cost form to compare alternatives with different life spans. The pipe diameter, material, pressure rating, surge tank size, and inlet/outlet resistances are the decision variables. A software was compiled with a commercial pipeline software to generate all the possible design alternatives based on the decision variables. Pipe initial cost as well as operation and maintenance costs are computed for each design alternative. The alternative with the least ERAC value is the optimum one. It was found that the approach can lead to substantial savings in pipeline projects cost. For pipes 800 mm in diameter or larger, and when selecting the optimum diameter, savings are between 23 and 27% in the total project cost. When imposing certain pipe material savings in overall cost will be 8.5, 16.3 and 31.3% for ductile iron, GRP and mild steel pipe material, respectively.

Off-Grid Rural Electrification in India Using Renewable Energy Resources and Different Battery Technologies with a Dynamic Differential Annealed Optimization

Several families in India live in remote places with no access to grid-connected power supply due to their remoteness. The study area chosen from the Indian state of Odisha does not have an electrical power supply due to its distant location. As a result, this study analyzed the electrification process using Renewable Energy (RE) resources available in the locality. However, these RE resources are limited by their dependency on weather conditions and time. So, a robust battery storage system is needed for a continuous power supply. Hence, the Nickel Iron (Ni-Fe), Lithium-Ion (Li-Ion) and Lead Acid (LA) battery technologies have been analyzed to identify a battery technology that is both technologically and economically viable. Using the available RE resources in the study area, such as photovoltaic and biomass energy resources, as well as the various battery technologies, three configurations have been modelled, such as Photovoltaic Panels (PVP)/Biomass Generator(BIOMG)/BATTERY(Ni-Fe), PV/BIOMG/BATTERY(Li-Ion) and PVP/BMG/BATTERY(LA). These three configurations have been examined using nine prominent metaheuristic algorithms, in which the PVP/BIOMG/BATTERY(Ni-Fe) configuration provided the optimal Life Cycle Cost value of 367,586 USD. Among the all metaheuristic algorithms, the dynamic differential annealed optimization algorithm was given the best Life Cycle Cost values for all of the three configurations.

Estimation of the value of an inspection and maintenance program: A Bayesian gamma process model

This paper presents a model to quantify the economic value gained by implementation of an inspection and preventive maintenance program for managing an ageing component population. The proposed approach is a refinement of the Bayesian value of information analysis through the consideration of an intricate interaction between parameter and temporal uncertainties associated with the gamma process of degradation. This paper presents an analytical formulation and computational approach to solve this complex problem in a multivariate setting. The paper shows that the economic value is significantly sensitive to the prior information and relative costs of preventive and corrective maintenance. Since the value of inspection is dominated by a reduction in the parameter uncertainty of the gamma process model, lifecycle cost optimization which ignores this aspect would lead to a sub-optimal solution of the problem.

Mobile energy hub planning for complex urban networks: A robust optimization approach

The electricity grid with a high penetration of renewable energy can enable travelers to travel free of emissions using state-of-the-art electric vehicles (EVs). Extensive electric vehicle demands at the peak-times, and an increase in electricity consumption due to population growth, have led to higher utility infrastructure investments. Mobile energy hubs i.e. clustered EVs parked in a dedicated location, can be used as an innovative demand-side management solution to reduce long-term utility infrastructure investments. They can store and release electricity to the grid based on consumer demand. However, a scientific planning approach for grid integration has been overlooked. Accordingly, this study proposes a comprehensive framework required to plan and develop mobile energy hubs based on optimization of life cycle cost, access distance and parking duration considering the temporal variation of EV recharging demands. The results of the study show that the framework developed can minimize lifecycle costs, and improve infrastructure utilization by accounting for the interests of all stakeholders. The total cost with the proposed robust optimization model under uncertainties of 50% is lesser than the robust cost calculated from a scenario-based approach. Furthermore, the developed framework is useful for recharging infrastructure planners to devise the deployment schedules and attract investors based on the economic viability of the planned strategies.

Life-cycle cost optimization of a solar combisystem for residential buildings in Nepal

ABSTRACT Current solar thermal systems used in Nepal are mostly for domestic hot water heating. Meanwhile, there is a growing need for space heating. A solar heating system can be configured to provide heat for both space heating and domestic hot water, leading to a solar combisystem. Research on residential solar combisystems in the Nepalean context barely exists in literature. This paper intends to propose, model and optimize a solar combisystem for typical single-family houses in Nepal. The optimization problem is formulated to have life-cycle cost as the objective function and a total of 11 variables, which are related to the sizing of combisystem components and the insulation thickness of building envelope. The number of hours not satisfying the thermostat heating set point is treated as the constraint. TRNSYS is used for modeling the solar combisystem. Particle Swarm optimization and the Hooke-Jeeves algorithm implemented in GenOpt are sequentially applied to solve the optimization problem. The results show that the optimization is effective to reduce the life-cycle cost by 66% for the Terai region and 77% for the Hilli region. The findings have demonstrated the importance of building envelope insulation to spread the use of solar combisystems in Nepal.

Life Cycle Cost Optimization of Residential Buildings in Bulgaria: a Case Study of the Building Envelope

Abstract Around 60 % of residential buildings in Bulgaria are constructed before the Nineties of the last century, i.e. they have been in use for more than 30 years. Furthermore, the final energy consumption of Bulgarian residential buildings is the highest in Europe. This raises the question of the improvement of the energy performance of existing residential buildings. The current study is intended to assess the influence of the heat transmittance coefficient of the external building envelop elements on the annual energy consumption for heating and cooling and finding its optimal value. Life-cycle cost (LCC) as the optimization criterion is using. The optimization procedure is conducted for the climatic and economic conditions in Bulgaria and taking into account the existing legal framework. The minimum of the building life cycle costs is determined by using a genetic algorithm.

Life cycle cost optimization analysis of battery storage system for residential photovoltaic panels

The current climate and energy policies of the European Union aim at achieving carbon dioxide emissions reduction and the promotion of clean energy. The priorities set concentrate on decarbonizing the energy sector, mainly by promoting renewables. At the same time, it is of great importance to effectively manage the energy generated in-situ within a community. That community can be approached as a micro-grid able either to be connected to the main grid or to be independent. In addition to this, storage of electricity seems the unavoidable solution for the effective energy management with the micro-grid. Due to the technological developments and the reduction in production costs that are expected to decrease even further in the coming years (50% reduction), batteries are a crucial factor for the effective integration of renewables on a residential scale. Thereafter, the proper size of a battery system plays an important role for the total minimization of system's cost during its lifetime. The purpose of the paper is to present a mathematical tool, able to manage the energy produced by residential photovoltaic panels, the energy stored in the batteries and the energy purchased from the main grid. Continuing with the energy management, the framework should come up with an optimized life cycle cost solution, regarding both the energy management within the grid and the optimum size of energy battery system. Main findings of the paper indicate that storage is a feasible option, whenever selling electricity to the main grid is not applicable, as for that case the battery capital cost should decrease to 400 (€/kWh); this is a 20% cost reduction compared to current prices and 30 (€/kWh).

Multi-objective capacity optimization of a hybrid energy system in two-stage stochastic programming framework

Hybrid energy system is one main mean to deal with the energy crisis and its capacity optimization is a key to obtain an economical and reliable supply of energy. In this paper, the capacity optimization of a novel hybrid system composed of wind turbine, concentrated solar plant and electric heater is modeled as a multi-objective two-stage stochastic problem, where capacity optimization minimizing the life cycle cost (LCC) and energy management strategy optimization minimizing the loss of power supply probability (LPSP) are integrated. The scenario-based approach is applied to reflect the random characteristics of wind and solar resources. The Pareto set of the problem is obtained by non-dominated sorting genetic algorithm (NSGA-II), whose effectiveness is validated by algorithm comparisons with multi-objective particle swarm optimization (MOPSO) and multi-objective evolutionary algorithm based on decomposition (MOEA/D). Furthermore, techno-economic comparisons with a reference hybrid energy system without electric heater are performed to investigate economic benefits of the electric heater. The comparison results show that the electric heater is beneficial for a lower LCC which is reduced by 1.21%, 1.34%, 1.68%, 3.14%, 4.94% and 4.55% respectively when the LPSP is 0%, 1%, 2%, 3%, 4% and 5%.

Water Pipe Replacement Scheduling Based on Life Cycle Cost Assessment and Optimization Algorithm

Water distribution networks (WDNs) comprise a complex network of pipes and are crucial for providing potable water to urban communities. Therefore, WDNs must be carefully managed to avoid problems such as water contamination and service failures; however, this requires a large budget. Because WDN components have different statuses depending on their installation year, location, transmission pressure, and flow rate, it is difficult to plan the rehabilitation schedule within budgetary constraints. This study, therefore, proposes a new pipe replacement scheduling approach to smooth the investment time series based on a life cycle cost (LCC) assessment for a large-scale WDN. The proposed scheduling plan simultaneously considers both the annual budget limitation and the optimum expenditure on the useful life of pipes. A multi-objective optimization problem consisting of three decision-making objectives—minimum imposed LCC on the network, minimum standard deviation of annual investment, and minimum average age of the network—is thus solved using a nondominated sorting genetic algorithm to obtain an optimal plan. Three scenarios with different pipe replacement time spans and different annual budget constraints are considered accordingly. The results indicate that the proposed scheduling framework provides an efficient water pipe replacement scheduling plan with a smooth management budget.

Life cycle cost optimization of earthquake-resistant steel framed tube tall buildings

Past earthquakes revealed that while fulfilling the requirements of the conventional design codes guarantees the life safety of the occupants, considerable economic losses may still be incurred. This highlights the importance of considering life cycle losses in the design procedure of structures. In this research, the significance of the life cycle seismic risk costs in the optimal design of steel framed tube tall buildings is investigated. Typical 20- and 40-story buildings are optimally designed based on three approaches: the code-based, the cost-based, and the fixed weight approach. The first approach only minimizes the initial cost of the building while in the second and third approaches the total cost of the building in its lifetime is considered. Endurance Time (ET) method is used as the tool for seismic life cycle cost analysis. The requirements of the building codes are treated as the optimization constraints and the resulting problem is solved using the gradient-based algorithms. The results indicate that the cost-based approach results in the best practical design with the minimum total cost in the lifetime. The design based on the fixed weight approach reveals that the code-based design of tall buildings will not necessarily lead to the most economical use of material. Using ET method as the analysis tool along with the gradient-based algorithms as the optimization tool provides an efficient framework for the optimal seismic design of high-rise buildings based on life cycle costs.

Techno-economic investigation of the potential for energy efficiency measures of multi-story apartment buildings at cluster level using different district heating tariffs

The paper presents a systematic approach to study energy renovation of a larger building stock at cluster level using categorization, classification into modules, life cycle cost (LCC) optimization, and bottom-up modeling. Seven-story clusters of slab and tower blocks were analyzed to investigate the techno-economic potential for energy efficiency measures (EEMs) of 401 multi-story apartment buildings constructed during the 1960s and ’70s located in two Swedish municipalities. Energy renovation with intention of lowest LCC and projected energy savings concerned the purchased energy for space heating and domestic hot water use allocated by different district heating (DH) tariffs. Different conditions for DH and performance indicators demonstrated code compliance. The LCC analysis revealed a rather small potential for cost-optimal EEMs on building envelopes. Incentives to gain LCC savings during energy renovation increased with a DH tariff with constant price rate throughout the year. A starting point for cost-effective energy renovations arguably would be clusters with 94 two-story and 160 three-story slab blocks, also requiring fewer EEMs to achieve thermal performance requirements. DH systems using industrial excess heat can improve buildings’ energy performance and reduce required EEM investment costs. The DH price level is shown to be a vital issue for cost-effective energy renovations.

Life-Cycle Maintenance Management Strategies for Bridges in Kuwait

To meet the requirements of 21st century, Kuwait ministry of public works have realized that they should use modern technologies and management system to face challenges of modern world. So, they maintenance Administration has launched a massive program which helps to meet development needs and helps to maintain the infrastructure’s sustainable growth. Thus, it is very necessary to develop appropriate bridge maintenance strategies to meet serviceability criteria and life cycle cost optimization of new bridges. And main purpose was to meet the requirements of development needs. Bridge management system (BMS) is a software or we can say a management tool which helps us to maintain or manage the bridges. These are the following main points which helps decision makers to make a best decision. Defines bridge condition, identifies bridge needs for like if we need replacement of any material or renovation can be identified by BMS, cost of bridge during maintenance and management of the bridge, identifies bridges for Replacement and rehabilitation programs (MR & R) and also identifies for the assessment of bridges. According to replacement and rehabilitation programs minor changes or maintenance of the bridges is done by Work management system (WBS). This paper proposes a framework that can enhance the effectiveness of Kuwait’s Integrated Maintenance Management System (KIMMS). A survey for bridge contractors around the world was used as the research method for this study. This contains questions regarding their current bridge management system (BMS) and what are the input and output parameters it considers in the process. BIM (Bridge information modeling) technology is used to reduce the errors in designing and construction of the bridges by using BMS, BRIDGE OWNER may have a sustainability in the maintenance and enhancement of its bridge. We can determine the cash flow to be used in future for the replacement and repairment of bridge. It helps to adopt maintenance program to maintain life-cycle costs for the community. Helps to review the replacement and rehabilitation strategies. Helps to improve the economic life of infrastructure assets. After evaluating the BMSs used by the respondents, it turned out that the most effective procedure should have three main processes to be followed; maintenance planning, maintenance optimization, and maintenance decision support. Overall, the conceptualized framework considers an optimized procedure for maintenance management considering the balance in cost and quality of the process.

Lifecycle cost optimization of pipeline projects

Abstract Lifecycle cost optimization for a pipeline network with medium-sized pipes is performed considering steady and unsteady flow conditions. Genetic algorithms are used to generate a wide range of hydraulically acceptable solutions and search for the most economical solutions. The impact of each cost component on the total cost is determined in this study. The decision variables include the pipe diameter, pipe material, pipe pressure rating, surge tank size and operational and maintenance costs over the project service life. A real-case project is presented to crosscheck the suggested procedure. Significant cost variations are observed, even between equally acceptable designs. Furthermore, the operational cost has a deterministic effect on the parameters of the optimum solution. Compared to conventional design wisdom that focuses on reducing the pipe diameter as much as possible to reduce the project cost, this approach demonstrates that significant savings in pipeline project costs can be achieved by carefully investigating all possible design alternatives under steady and unsteady flow conditions.

Life cycle cost optimisation model for design and reinforcement of dams based in fuzzy clustering and a backtracking search algorithm

As an important long-term task in the field of dam engineering, the maintenance and reinforcement (MAR) are of great significance for ensuring the safety of the project and prolonging the service period of the project. The MAR of large-scale and long-term projects also requires high costs. In order to reduce the consumption of funds and improve the utilisation of resources, the whole life cycle cost (LCC) method is introduced. Aiming at the lowest total cost in the whole life cycle, the optimisation of dam engineering planning, design and MAR is carried out. Taking gravity dam as an example, this article establishes a time-varying model of structural resistance and load effect, and the deterioration process of the gravity dam has been analysed and predicted. A decision model for design and reinforcement of gravity dams considering operational risk and LCC is established. Through the optimisation algorithm, the optimal initial design of the gravity dam and its optimal MAR plan is obtained.

Optimal design of redundant structural systems: fundamentals

In spite of extended recent interest in System Reliability-Based Design Optimization (System RBDO) and life-cycle cost or Risk Optimization (RO), there is a lack of published studies on optimal design of redundant hyperstatic systems with objective consideration of (a) progressive collapse and (b) the impact of epistemic uncertainties. This paper investigates the fundamental aspects of the problem, by addressing the optimal design of simple two-bar active and passive redundant systems. Progressive collapse is objectively addressed, differentiating consequences of direct collapse of statically determinate structures, and progressive collapse of redundant, statically indeterminate structures. A comprehensive study is performed, considering material post-failure behavior (fragile-ductile), strength correlation, dynamic amplification factors in load re-distribution, and material strength ratios. Physical uncertainty in material strengths and loads is considered. However, it is well known that reliability of a structural system also depends on nonstructural factors, or factors beyond structural design, such as unanticipated loading, manufacturing quality, quality of workmanship and human errors. These factors can be taken into account in an encompassing risk analysis, which accounts for physical and epistemic uncertainties, and which contributes a fixed latent failure probability to the structural optimization problem. Results presented herein show that the latent failure probability is the single most important parameter in determining optimal solutions, in System RBDO and in RO solutions. When the latent failure probability is smaller than target (System RBDO) or optimal (RO) failure probabilities, there is an equivalence between redundant and non-redundant (hyperstatic and isostatic) designs. However, when the latent reliability is smaller than target or optimal reliabilities, optimal designs become necessarily redundant (hyperstatic); as the only way to make system reliability larger than the latent reliability is by making structural systems redundant. This result is widely known in context of system reliability, but has been overlooked in past studies involving structural System RBDO and Risk Optimization.