Total Installation Cost Research Articles

Optimising the thermal environment and the ampacity of underground power cables using the gravitational search algorithm

This study takes into consideration a problem that commonly occurs at the design stage of underground cable lines and that relates to the manner of determining the optimal values for dimensions of cable trench and bedding, interaxial spacings between power cables in flat formation and cable ampacities. The problem is formulated as a non-linear optimisation problem with constraints. The gravitational search algorithm, simulated annealing algorithm and generalised pattern search algorithm are used to solve the problem. The optimal solutions are obtained based on the following three optimisation criteria: (i) minimisation of the total installation costs, i.e. the total costs for producing the cable trench, laying the bedding material, laying the backfill material and installing the cables, (ii) maximisation of the cable ampacity and (iii) a simultaneous application of the minimisation of the total installation costs and the maximisation of the cable ampacity. The constraints on design and control variables are introduced through penalty factors by means of which the objective function is expanded. The procedure is conducted taking into account the effect of drying out of the soil surrounding the cables.

A “New-Deal” for the Development of Photovoltaic Investments in Greece? A Parametric Techno-Economic Assessment

The aim of this paper is to identify the financial impact imposed by cost containment measures and especially by the feed in tariff (FiT) reduction upon the profitability of different photovoltaic (PV) investments and the electricity charge faced by consumers. A fully parametric analysis is carried out by varying the following parameters: total installation costs based on their activation date, interest rate for a bank loan, use of a construction subsidy, tax imposition levels, the solidarity surcharge differentiated by the activation and the purchase agreement date and the issuance of credit invoice. During the simulations the simple payback period, the internal rate of return and the profitability index were calculated for the most common investment cases. These were identified through empirical observations on the deployment of PV stations. The profitability of PV stations connected to the medium voltage network were by far affected the most by the cutback while farmers’ PV stations and PV rooftop systems were comparatively less affected. Parameters such as the size of the station and the PV activation date were crucial for the assessment of the viability of PV stations. From a social perspective, the FiT cutback prevented an additional 40% increase in the electricity charge paid by electricity consumers.

A stochastic program approach for path reconstruction oriented sensor location model

Path flow identification is of particular interest for a number of traffic applications, such as OD demand estimation, link flow inference, and toll freeway revenue management. Optimal positioning of active sensors can help to identify path flows. Due to the stochastic nature of transportation systems, we propose a scenario based two stage stochastic programming framework which considers the uncertainty of the link-path matrix. The first stage model aims to minimize the total traffic sensor installation cost and the expected penalty for uncovered and undifferentiated paths. The second stage model attempts to minimize uncovered and undifferentiated paths for a given sensor location pattern and a specific scenario. In addition, a mean risk measure is also incorporated into the two stage stochastic programming framework, and consequently a mean risk two stage stochastic programming model is proposed. Both models have the same structure, where the first stage and second stage decision variables are binary. The second stage decision variable can be relaxed to a continuous variable without changing the nature of the model. To solve the two stochastic programming models, a branch and bound based integer L-shaped algorithm is presented. Finite steps convergence is guaranteed for the algorithm. To handle the problem with a large number of scenarios, a sampling technique is introduced, and the confidence bound is analyzed with respect to the scenario size. Extensive numerical experiments are conducted to verify the effectiveness of the proposed models and algorithm. The most important numerical results are as follows: (i) the stochastic programming framework is capable of capturing the reality more efficiently and accurately, (ii) the path differentiation factor is more critical than the path coverage factor in determining the sensor placement pattern, and (iii) in the partial parameter setting case, the mean risk based stochastic programming model results in a significantly different sensor placement pattern compared to the normal stochastic programming model. The study contributes to practical sensor placement design.

Mesh node placement in wireless mesh network based on multiobjective evolutionary metaheuristic

To achieve important properties of wireless mesh networks (WMNs) such as coverage and reliability, the placement of mesh nodes plays an important role. The impact of the mesh node placement on the performance of WMNs has been carried out in the past years. To improve such properties, we propose a novel scheme for mesh node placement in WMNs. We have developed a multi-objective optimisation model for node placement where the coverage, reliability and the total installation cost in terms of nodes to be deployed are the three objectives to optimise simultaneously. We first applied the two well-known evolutionary algorithms, namely the non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective genetic algorithm (MOGA) to generate the number and positions of the communication nodes. Subsequently, we developed algorithms that determine the cluster formation, gateway selection and relay nodes selection. The results showed satisfactory performance.

Description and Assessment of a Small Renewable Energy Community in the Island of Crete, Greece

A description and assessment of a small renewable energy community located in Crete, Greece is presented. The community included private residential and agricultural activities without any involvement of the public sector. Small-scale decentralized energy systems were used. Solar energy and solid biomass which are locally available covered most of the heat and electricity requirements in the community. Renewable energy technologies used include solar thermal energy, solar-PV and solid biomass burning utilizing olive tree wood and olive kernel wood. These technologies are mature, reliable, well proven in Crete and cost-effective. Existing energy systems were generating 857,877 kWh per year covering 94.46% of the current energy requirements in the community, significantly reducing its emissions at 278,494 kg CO2 per year. The addition of a new solar-PV system with nominal power of 33.6 kWp could cover all the remaining electricity needs in the community, transforming it to a zero-CO2 emission community due to energy use. The total installation cost of the existing renewable energy systems in the community was estimated at 0.16�per total kWh of thermal and electric energy generated annually and at 0.50�per ton of CO2 emissions saved annually. Results indicated that the creation of the above-mentioned small local energy community is economically viable, environmental friendly and socially accepted. Therefore it could be replicated in other territories with similar availability of renewable energies, increasing their energy autonomy and sustainability.

Electric Vehicle Charging Station Placement for Urban Public Bus Systems

Due to the low pollution and sustainable properties, using electric buses for public transportation systems has attracted considerable attention, whereas how to recharge the electric buses with long continuous service hours remains an open problem. In this paper, we consider the problem of placing electric vehicle (EV) charging stations at selected bus stops, to minimize the total installation cost of charging stations. Specifically, we study two EV charging station placement cases, with and without considering the limited battery size, which are called ECSP_LB and ECSP problems, respectively. The solution of the ECSP problem achieves the lower bound compared with the solution of the ECSP_LB problem, and the larger the battery size of the EV, the lower the overall cost of the charging station installation. For both cases, we prove that the placement problems under consideration are NP-hard and formulate them into integer linear programming. Specifically, for the ECSP problem we design a linear programming relaxation algorithm to get a suboptimal solution and derive an approximation ratio of the algorithm. Moreover, we derive the condition of the battery size when the ECSP problem can be applied. For the ECSP_LB problem, we show that, for a single bus route, the problem can be optimally solved with a backtracking algorithm, whereas for multiple bus routes we propose two heuristic algorithms, namely, multiple backtracking and greedy algorithms. Finally, simulation results show the effectiveness of the proposed schemes.

Theoretical Design for the Production of Quinoa (Chenopodium quinoa Willd.) in a Closed Plant Factory

Quinoa (Chenopodium quinoa Willd.) is a grain crop with high nutritional value. The leaves and sprouts of quinoa can also be consumed either raw or cooked, providing considerably nutritional value as well as high antioxidant and anticancer activities. This study was carried out to obtain basic data to assist in the practical design of a plant factory with artificial lighting for the cultivation of quinoa as a leafy vegetable. We estimated the energy content of the quinoa and the electrical energy required to produce this crop. The yield was 1,000 plants per day, with a planting density and light intensity of 0.015 m2 (15 × 10 Cm) and 200 μmol·m-2·s-1, respectively. The total number of plants, cultivation area, and electricity consumption were estimated to be 25,000, 375 m2, and 93,750 μmol·s-1, respectively. White fluorescent lamps were used at a power of 20.4 kW from 1,857 fluorescent lamps (FL, 55 W), and the cost for electricity was approximately 1,820 dollars (exchange rate of $1 = 1,200 won) per month. For a daily harvest of 1,000 plants per day in a closed plant factory, the estimated light installation cost, total installation cost, and total production cost would be 15,473, 46,421, and 55,704 dollars, respectively. The calculated production cost per plant, including labor costs, would be 27 cents for the 25-day cultivation period, with a marketable ratio of 80%. Considering the annual total expenses, income, and depreciation costs, the selling price per plant was estimated to be approximately 56 cents.

Minimizing transportation and installation costs for turbines in offshore wind farms

Building an offshore wind energy facility is an undertaking of large capital investment. The cost of such transportation and installation depends on the time to complete these processes. The cost can be minimized by an optimum selection of variables of transportation and installation operations such as onshore pre-assembly of turbines and their rated power outputs. Other factors such as learning rates for lifting and assembly operation, port-to-farm site distance, vessel deck area and lifting rate of the vessel crane have significant effects on the system cost. A model based on these costs is developed for wind turbine installation and transportation in an offshore wind farm, and the impact of decision variables on total cost of transportation and installation is investigated here. The effects of wind farm and vessel parameters on cost are studied such that an optimal set of system parameters is chosen to minimize the total cost of transportation and installation. A numerical analysis is performed to illustrate the model and to understand the general behavior of different system parameters. The results show that the total cost is significantly impacted by turbine size and pre-assembly method. Also, the scheduled maintenance help reduce the cost significantly that the unscheduled maintenance.

Thermo-economic analysis of four different types of ground heat exchangers in energy piles

In this paper, thermal efficiency of four different types of ground heat exchangers in energy piles is investigated (type: double-U, triple-U, double-W and spiral). Five thermal performance tests are conducted to analyze ground heat exchangers operation under an intermittent condition (7days on for cooling, 26days off, 7days on for heating).Results show that double-U type is with worst heating and cooling performance, accounting for 67–69% thermal efficiency than spiral and double-W types which are with similar thermal outputs. For technical problems, only heating performance of triple-U type is examined experimentally but the cooling performance is studied numerically. The findings show that tripe-U type performs highest thermal efficiency among all types. By examination of different pipe dimensions heat transfer rate of spiral type with 32mm diameter is increased by 32% than that of 25mm diameter.In addition, cost-benefits evaluation shows that triple-U shaped ground heat exchanger has highest economic performance, followed by double-U, spiral and double-W type. However, pipe material is only a small consists of the total installation costs. Hence, thermal efficiency is a more important factor to consider than pipe costs in practical application.

Heterogeneous sensor location model for path reconstruction

A new traffic sensor location problem is developed and solved by strategically placing both passive and active sensors in a transportation network for path reconstruction. Passive sensors simply count vehicles, while active sensors can recognize vehicle plates but are more expensive. We developed a two-stage heterogeneous sensor location model to determine the most cost-effective strategies for sensor deployment. The first stage of the model adopts the path reconstruction model defined by Castillo et al. (2008b) to determine the optimal locations of active sensors in the network. In the second stage, an algebraic framework is developed to strategically replace active sensors so that the total installation cost can be reduced while maintaining path flow observation quality. Within the algebraic framework, a scalar product operator is introduced to calculate path flows. An extension matrix is generated and used to determine if a replacement scheme is able to reconstruct all path flows. A graph model is then constructed to determine feasible replacement schemes. The problem of finding the optimal replacement scheme is addressed by utilizing the theory of maximum clique to obtain the upper bound of the number of replaced sensors and then revising this upper bound to generate the optimal replacement scheme. A polynomial-time algorithm is proposed to solve the maximum clique problem, and the optimal replacement scheme can be obtained accordingly. Three numerical experiments show that our proposed two-stage method can reduce the total costs of transportation surveillance systems without affecting the system monitor quality. The locations of the active sensors play a more critical role than the locations of the passive sensors in the number of reconstructed paths.

Laboratory test and FEM analysis on a developed continuous rail absorber (CRA)

Rail has a significant contribution in overall produced noise in railway freight tracks. Implementing rail noise absorbers is a promising way to increase the attenuation of the vibration. Designing of a rail noise absorber to work in critical frequencies in which the rail undergoes its maximum vibration is crucial. Moreover, total cost of installation, maintenance, repair, and operations as practical aspects of manufacturing have drew the attention of researchers. Regard to this point, the authors have developed a continuous rail noise absorber (CRA) which is composed of steel and elastomeric layers. The lateral and bottom surfaces of the rail is covered by the layers using specialized proprietary adhesive. The initial investigations and survey of the problem is reported in the authors’ previous paper which resulted in proposition of CRA. In this research CRA is produced and laboratory tests are carried out on a disjointed section of Tehran-Zanjan commercial rail track to determine the efficiency of the noise absorber system. It is revealed that the noise of rail availed of CRA is decreased about 9 dB in frequency range 500-2000 Hz. Owing to its noncomplex structure and lower cost of installation, CRA is a desirable noise absorber system for railway administrations. Furthermore, experimental values are compared with those ones obtained through a finite element model which are in a good agreement.

Optimal layout and deployment for RFID system using a novel hybrid artificial bee colony optimizer based on bee life-cycle model

Large-scale radio frequency identification (RFID) network planning (RNP) problem has been proven to be a NP-hard issue, which can be formulated as a high-dimensional nonlinear optimization problem with a mixture of discrete and continuous variables and uncertain parameters. First, a two-level optimization model for RFID network planning based on distributed decision making (DDM) is presented in this paper. In this model, the mixed discrete and continuous planning variables, namely the number, location, and radiate power of RFID readers are optimized. In each level of the optimization model, the different objectives to determine optimal values for these planning variables are as follows: (i) minimization of total installation cost of RFID network in the top-level; (ii) maximization of tag coverage and network reliability, and minimization of reader interference in the lower-level. In order to solve the proposed model effectively, this work proposes an efficient approach for RNP problem, namely the hybrid artificial bee colony optimizer (HABC), which employs the natural life-cycle mechanism to cast the original ABC framework to a cooperative and population varying fashion. In the proposed HABC, individuals can dynamically shift their survival states and population size varies dynamically according to the local fitness landscape during the executions of algorithm. These new characteristics of HABC help to avoid redundant search and maintain diversity of population in complex environments. Experiments are conducted on a set of CEC2005 and discrete benchmarks for evaluating the proposed algorithm. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.

Design and cost-benefit analysis of a novel anaerobic industrial bioenergy plant in Pakistan

The design and Cost-benefit analysis (CBA) of a novel anaerobic bioenergy plant is presented. This plant can digest various feed sources including animal-manure, vegetable-fruit wastes, poultry wastes, sugar molasses etc. The fixed dome multi-digestor system enables a continuous feed and flow mechanism. It is also equipped with a biogas purification, compression and storage system. This medium scale bioenergy plant is the first of its kind in Pakistan. It has a total installation cost of US$105,000 and annual operation and maintenance cost of US$23,400. The average energy production is 142,380 kWh per annum. With a current average energy cost of US$0.315 per kWh from all sources in Pakistan, the cost-benefit ratio is 1.2 at an internal rate of return (IRR) of 19.76%, and short payback period.

Transfer of Model of Innovative Smart Factory to Croatian Economy Using Lean Learning Factory

Croatia's manufacturing industry faces many problems and obstacles that have a large impact on its competitiveness. Insufficiently educated and unskilled personnel, particularly in the production and management fields, are decreasing competitiveness that is necessary for survival in the global market. Objective of project Innovative Smart Enterprise is to establish a special learning environment in one Laboratory asLean Learning Factory, i.e. simulation of a real factory through specialized equipment. The Lean Learning Factory's mission is to integrate needed knowledge into the engineering curriculum. Therefore, Lean Learning Factory at University of Split is in continuous developing process to support practice-based engineering curriculum with possibility of learning necessary tools and methods, using didactic games or real life products and equipment. Solution proposal for best balance between toys and real products consider design and production line development for product Karet. It is a traditional and original product from Croatia, so it will raise enthusiasmin learning process in both students and industry employees. Two assembly lines will be developed, one traditionally equipped and one intelligent, networked, flexible, and fully improved by Lean tools. By deeper analysis of both assembly lines, hybrid assembly lines could be designed, to balance on one side assembly tact time according to customer demand and total cost of installation and running on the other side. Methods and tools adapted and implemented, in both design and analysis process for optimization of this hybrid assembly line would be scaled and adjusted for industry use as part as knowledge transfer from university to enterprises.

Optimized Reinforcement Detailing Design for Sustainable Construction: Slab Case Study

Reinforced steel rebar is commonly supplied in one-dimensional stocks and typically designed for and installed in various structural components in civil and industrial construction. Surplus reinforcement constitutes a major fraction of construction generated waste. Cutting one-dimensional stocks to suit construction project requirements results in cutting losses. Therefore, reducing steel waste (or minimizing cutting losses) has long been the focus of academic research in one-dimensional stock design and cutting problems. Previous research developed mathematical models in an attempt to analytically minimize cutting losses based on preliminary engineering designs, but little insight has been provided on how to integrate minimization of cutting losses and engineering design into an integrated optimization problem, let alone considering minimizing total steel rebar installation cost as a parallel objective. The sustainability issue in regard to balancing reinforcement waste and crew installation costs on the basis of optimized engineering design has yet to be addressed. This study introduces a Mixed Integer Programming (MIP) approach to generate optimal cutting patterns, minimum cutting losses and associated total installation cost. A reinforced concrete slab case is adopted as a test to show that the proposed methodology is capable of producing optimal tradeoff solutions in slab reinforcement detailing design, resulting in less wastage and lower crew installation cost.

Analysis of exergy and total life cycle cost for segmental and helical baffles in a shell-and-tube heat exchanger

In this study, cost functions were analysed based on exergy rate and total life cycle for a shell and tube heat exchanger as a stand-alone unit with segmental baffles and helical baffles with helix angles from 5° to 45° in a retrofit project. Initially, the changes of shell-side exergy destruction rate were studied. After that the total life cycle costs, including capital, installation, operating and maintenance costs, were separately calculated for all cases. So as to determine the effect of baffle types, the net exergy saving cost function was considered based on the difference between the exergy profit cost and the net capital cost of the baffles' change. The results of exergy analysis showed that the shell-side exergy destruction rate decreased with the increase in helix angle. Moreover, the net exergy saving cost function analysis demonstrated that helical baffles from 25° to 45° improved thermodynamic performance in a cost-effective way in revamps and upgrades.

Techno-economic analysis of sustainable water management techniques - a case study of residential township in India

Technically efficient and economically viable methods of rooftop rainwater harvesting, greywater recycling and use of low flow devices for integrating in residential townships are identified. An integrated tool is developed for generating designs of identified techniques along with the estimates of capital costs required for installation and the total net present cost. It also calculates potential of water saving. A case study of a residential township in Nagpur, India has been presented. Unit cost and current net value of water using these techniques are calculated. Unit costs of water per cubic meter using rainwater harvesting, low flow devices and greywater recycling are found to be INR 230 (1USD = INR 55), INR 38 and INR 124 respectively. The current net value of water saved using rainwater harvesting; low flow devices and greywater recycling are INR 388,080 INR 162,437 and INR 70,560. Total cost of installation of these three techniques for the case study of residential township is INR 19,813,866, i.e., only 1.14% of the total cost of the project. This study enables prioritisation of practicing rainwater harvesting, use of low flow devices and greywater recycling for conservation of water as well as evaluation and allocation of the percentage of land area required for these techniques.

Optimizing of the cable bedding and the ampacity of underground power cables in trefoil formation by using the gravitational search algorithm

This paper considers the problem of the determination of the optimum values for dimensions of cable trench and cable bedding, interaxial spacings between power cables in trefoil formation and cable ampacities. This non-linear multi-objective optimization problem with constraints is solved by using the gravitational search algorithm (GSA). The procedure used in this paper has allowed the simultaneous inclusion of all control variables into the optimization process and the determination of an optimal solution in accordance with specified optimization criteria. in the present case, the optimal solution is obtained based on the following optimization criteria: (i) minimization of the total installation cost for cable line, (ii) maximization of the cable ampacity and (iii) a simultaneous application of the minimization of the total installation cost for cable line and the maximization of the cable ampacity. The constraints on control variables are introduced through penalty factors which expand the objective function, it is also assumed that the cable ampacity corresponds to a load factor of 0.8. The procedure is carried out with respect to the drying out effect in the soil surrounding the cables.

Robust and fuzzy goal programming optimization approaches for a novel multi-objective hub location-allocation problem: A supply chain overview

In this paper, a novel multi-objective mathematical model is developed to solve a capacitated single-allocation hub location problem with a supply chain overview. Three mathematical models with various objective functions are developed. The objective functions are to minimize: (a) total transportation and installation costs, (b) weighted sum of service times in the hubs to produce and transfer commodities and the tardiness and earliness times of the flows including raw materials and finished goods, and (c) total greenhouse gas emitted by transportation modes and plants located in the hubs. To come closer to reality, some of the parameters of the proposed mathematical model are regarded as uncertain parameters, and a robust approach is used to solve the given problem. Furthermore, two methods, namely fuzzy multi-objective goal programming (FMOGP) and the Torabi and Hassini's (TH) method are used to solve the multi-objective mathematical model. Finally, the concluding part presents the comparison of the obtained results.

Kajian Ekonomis Pembangkit Hybrid Renewable Energi Menuju Desa Mandiri Energi di Kabupaten Bone-Bolango

Energy crisis due to extensive uses of fossil fuel and environmental issues caused by unsustainable uses of energy driving the world and Indonesian government to accelerate the usage of renewable energy such as hydro, wind and solar. One of the government approaches is to implement a program called Independent Energy Village (IEV). Hybrid Optimization Model for Electric Renewables (HOMER) serves to design a micropower systems and to facilitate the comparison between some of power generation technologies. Researcher models the power system based on the physical behavior and overall cost, which are the total cost of installation and operation of the system during operation of the system. HOMER allows researcher to compare various forms of system designs technically and economically. This research was conducted in the village of Lombongo, District Suwawa, in Bone-Bolango Gorontalo. Some of the modeling results showed that the combination of micro-hydro and solar power have the most favorable economic value if operated over 25 years with a Net Present Cost (NPC) is US$ -369,087.00 and a Level Cost of Energy (LCOE) of -0.106 US$/kWh below the level energy costs of PLN at 0.116 US$/kWh in whch made this hybrid plant is very competitive. The hybrid plant has micro-hydro generating capacity of 58,9 kW with annual production of 657,384 kW, while solar power plant with a production capacity of 15,7 kW per year 20.091 kW.