A chance-constrained programming-based optimization model for the dynamic economic emission dispatch problem (DEED), consisting of both thermal units and wind turbines, is developed. In the proposed model, the probability of scheduled wind power (WP) is included in the set of problem-decision variables and it is determined based on the system spinning reserve and the system load at each hour of the horizon time. This new strategy avoids, on the one hand, the risk of insufficient WP at high system load demand and low spinning reserve and, on the other hand, the failure of the opportunity to properly exploit the WP at low power demand and high spinning reserve. The objective functions of the problem, which are the total production cost and emissions, are minimized using a new hybrid chaotic maps-based artificial bee colony (HCABC) under several operational constraints, such as generation capacity, system loss, ramp rate limits, and spinning reserve constraints. The effectiveness and feas... [more]

Bag-of-Tasks (BoT) scheduling over cloud computing resources called Cloud Bag-of-Tasks Scheduling (CBS) problem, which is a well-known NP-hard optimization problem. Whale Optimization Algorithm (WOA) is an effective method for CBS problems, which still requires further improvement in exploration ability, solution diversity, convergence speed, and ensuring adequate exploration−exploitation tradeoff to produce superior scheduling solutions. In order to remove WOA limitations, a hybrid oppositional differential evolution-enabled WOA (called h-DEWOA) approach is introduced to tackle CBS problems to minimize workload makespan and energy consumption. The proposed h-DEWOA incorporates chaotic maps, opposition-based learning (OBL), differential evolution (DE), and a fitness-based balancing mechanism into the standard WOA method, resulting in enhanced exploration, faster convergence, and adequate exploration−exploitation tradeoff throughout the algorithm execution. Besides this, an efficient al... [more]

The need for a clean and affordable energy supply is a major challenge of the current century. The tough shift toward a sustainable energy mix becomes even more problematic when facing realities that lack infrastructures and financing, such as small islands. Energy modeling and planning is crucial at this early stage of the ecological transition. For this reason, this article aims to improve an established long-run energy model framework, known as “OSeMOSYS,” with an add-on tool able to estimate different types of Levelized Cost Of Electricity (LCOE): a real and theoretical LCOE of each technology and a real and theoretical system LCOE. This tool fills a gap in most modeling frameworks characterized by a lack of information when evaluating energy costs and aims at guiding policymakers to the most appropriate solution. The model is then used to predict future energy scenarios for the island of San Pietro, in Sardinia, which was chosen as a case study. Four energy scenarios with a time h... [more]

The penetration of renewable energy sources (RESs) in the electrical power system has increased significantly over the past years due to increasing global concern about climate change. However, integrating RESs into the power market is highly problematic. The output of RESs such as wind turbines (WTs) and photovoltaics (PVs) is highly uncertain. Their correlation with load demand is not always guaranteed, which compromises system reliability. Distributed energy resources (DERs), especially demand response (DR) programs and energy storage systems (ESSs), are possible options to overcome these operational challenges under the virtual power plant (VPP) setting. This study investigates the impact of using a DR program and battery energy storage system (BESS) on the VPP’s internal electricity market, and also cost-minimization analysis from a utility viewpoint. Three different constrained optimal power flow (OPF) problems are solved such as base case, DR case, and BESS case to determine tot... [more]

The evolution of changes in shopping in the modern society necessitates suppliers to seek new solutions consisting of increasing the efficiency of transport processes. When it comes to controlling the flow of goods in modern distribution networks, planning and timely deliveries are of particular importance. The first factor creating a competitive advantage involves the tendency to shorten order delivery times, especially for products with a short shelf life. Shorter delivery times, in turn, extend the period of effective residence of the product “available on the shelf”, increasing the likelihood of its sale. The second component in line with the Sustainable Development Strategy consists of aspects related to the protection of the natural environment, in particular those related to car transport. In this case, the fuel consumption and the level of emitted toxic substances (including carbon dioxide) are analyzed and assessed. Bearing in mind the above, this article presents the problem... [more]

The reasonable and efficient use of the abundant biomass resources in rural areas has not been realized. Therefore, the concept of a combined cooling, heating, and power (CCHP) microgrid system, considering biomass pyrolysis and gasification, has been developed by researchers. A biomass gasification device can fully use biomass resources and can play a role in absorbing wind energy. Meanwhile, in order to minimize the operating cost of each micropower supply unit, as well as the environmental pollution costs, researchers have also established an optimal scheduling model for CCHP microgrids, which uses the sparrow search algorithm. In this paper, we have improved upon the traditional sparrow algorithm to solve the problems of its uneven population distribution, poor global search ability, and the risk of falling into local optima, through the development of the random walk sparrow search algorithm (RSSA). First, a sinusoidal chaotic map is used to generate the early-generation sparrow p... [more]

Current electric utilities must achieve reliability enhancement of considerable distribution feeders with an economical budget. Thus, optimal preventive maintenance planning is required to balance the benefits and costs of maintenance programs. In this research, the proposed method determines the time-varying failure rate of each feeder to evaluate the likelihood of future interruptions. Meanwhile, the consequences of feeder interruptions are estimated using interruption energy rates, customer-minutes of interruption, and total kVA of service areas. Then, the risk is assessed and later treated as an opportunity for mitigating the customer interruption costs by planned preventive maintenance tasks. Subsequently, cooperative game theory is exploited in the proposed method to locate a decent balance between the benefits of reliability enhancement and the costs required for preventive maintenance programs. The effectiveness of the proposed method is illustrated through case studies of larg... [more]

This paper deals with the optimal sizing of islanded microgrids (MGs), which use diesel generators to supply energy in off-grid areas. The MG under study integrates photovoltaic (PV) and diesel generation, a battery energy storage System (BESS), and an inverter for the connection between AC and DC voltage buses. Levelised cost of energy (LCOE) and annual system cost (ASC) are considered economic indicators, while the loss of power supply probability (LPSP) is used as a reliability indicator. Fiscal incentives such as the tax benefits and accelerated depreciation applied in Colombia are considered for the optimally sizing of each MG element. Solar measurements were taken at a weather station located in the main campus of Universidad de Antioquia in Medellin, Colombia at a latitude of 6.10 and longitude of −75.38. The objective function is the minimization of the total energy delivered from the power sources that successfully meets the load. The model was implemented in Python programmin... [more]

This work describes the development of a fast Model Predictive Control (MPC) algorithm for a Proton Exchange Membrane (PEM) fuel cell. The MPC cost-function used considers the sum of absolute values of predicted control errors (the L1 norm). Unlike previous approaches to nonlinear MPC-L1, in which quite complicated neural approximators have been used, two analytical approximators of the absolute value function are utilised. An advanced trajectory linearisation is performed on-line. As a result, an easy-to-solve quadratic optimisation task is derived. All implementation details of the discussed algorithm are detailed for two considered approximators. Furthermore, the algorithm is thoroughly compared with the classical MPC-L2 method in which the sum of squared predicted control errors is minimised. A multi-criteria control quality assessment is performed as the MPC-L1 and MPC-L2 algorithms are compared using four control quality indicators. It is shown that the presented MPC-L1 scheme gi... [more]

Higher alcohols can be included as a third component in biodiesel-diesel mixtures to improve fuel properties and reduce emissions. Determining the optimum concentrations of these fuels according to the purpose of engine use is important both environmentally and economically. In this study, eight different concentrations of diesel (D), waste oil derived biodiesel (WOB), and 1-pentanol (P) ternary mixtures were determined by the design of experimental method (DOE). In order to determine the engine performance and exhaust emission parameters of these fuels, they were tested on a diesel engine with a constant load of 6 kW and a constant engine speed of 1800 rpm. Using the test results obtained, a full quadratic mathematical model with a 95% confidence level was created using the Response Surface Method (RSM) to predict five different output parameters (BSFC, BTE, CO, HC, and NOx) according to the fuel mixture ratios. The R2 accuracy values of the outputs were found at the reliability level... [more]

Both the unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) are attracting growing attention as enabling technologies for future wireless networks. In particular, IRS-assisted UAV communication, which incorporates IRSs into UAV communications, is emerging to overcome the limitations and problems of UAV communications and improve the system performance. This article aims to provide a comprehensive survey on IRS-assisted UAV communications. We first present six representative scenarios that integrate IRSs and UAVs according to the installation point of IRSs and the role of UAVs. Then, we introduce and discuss the technical features of the state-of-the-art relevant works on IRS-assisted UAV communications systems from the perspective of the main performance criteria, i.e., spectral efficiency, energy efficiency, security, etc. We also introduce machine learning algorithms adopted in the previous works. Finally, we highlight technical issues and research challenges that... [more]

What benefits, from the point of view of the energy and ecological performance of a multisource drive system, can be gained for a particular control criterion through the use of appropriate secondary energy source parameters (accumulator volume Vg and initial gas pressure pg) for a given work cycle of a machine working in closed spaces? This paper describes a method of determining energy and ecological efficiency for a selected multisource drive system control criterion and presents potential benefits resulting from a proper choice of secondary energy source parameters for a selected control criterion. Using, as an example, a multisource hydrostatic drive system with a combustion engine as the primary energy source, the energy consumption and the ecological parameters (nitrogen oxides NOx emissions, carbon monoxide CO emissions and opacity DYM) were analysed for selected work cycles and different hydraulic accumulator parameters, i.e., initial gas pressure (pg) and accumulator volume (... [more]

Heat transfer is one of the most fundamental engineering subjects and is found in every moment of life. Heat transfer problems, such as heating and cooling, where the transfer of heat between regions is calculated, are problems that can give exact solutions with parametric equations, many of which were obtained by solving differential equations in the past. Today, the fact that heat transfer problems have a more complex structure has led to the emergence of multivariate models, and problems that are very difficult to solve with differential equations have emerged. Optimization techniques, which are also the subject of computer science, are frequently used to solve complex problems. In this study, laminar thermal boundary layers in flow over a flat plate, a sub-problem of heat transfer, is solved with recent metaheuristic algorithms. Teaching learning-based optimization (TLBO), sine cosine optimization (SCO), gray wolf optimization (GWO), whale optimization (WO), salp swarm optimization... [more]

To solve the problem of layout design of charging stations in the early stage of the electric vehicle industry, the user’s satisfaction and the charging convenience are considered. An electric vehicle charging station site-selection model is established based on the kernel density analysis of the urban population. The goal of this model is maximum electric vehicle user satisfaction and the highest charging convenience. Then, according to model characteristics, the immune algorithm is designed and optimized to solve the model. The optimization of the immune algorithm includes two aspects. On the one aspect, judging that the stop condition is added in the mutation link. On the other aspect, two mutation operators are designed in the optimized immune algorithm. Finally, the simulation example is determined by a three-step method in Jinan City. The results show that the electric vehicle charging station site-selection model in this paper can better meet user needs compared with traditional... [more]

The low voltage (LV) distribution systems are extended year by year due to the increase in energy demand. To overcome this issue, distribution system utilities have been focusing on designing and operating an appropriate distribution system with minimum capital and operational expenditure for supplying electricity to users. This article compares different algorithms to design an LVAC distribution system in a rural area, which focuses on minimizing the total length of lines and the power losses and balancing the loads among the three phases including the economic evaluation of the grid-connected PV system. Firstly, the shortest path (SP) algorithm is established to search for the minimization of the conductor used. Secondly, three different algorithms which are repeated phase sequence (RPABC), first fit bin packing (FFBP), and mixed-integer quadratic programming (MIQP) algorithms are developed to balance the load and minimize power losses. Next, a comparative result of three different a... [more]

When designing biomass-to-biofuel supply chains, the biomass uncertainty, seasonality and geographical dispersion that affect economic viability need to be considered. This work presents a novel methodology that can optimize the design of biofuel supply chains by adopting a decentralized network structure consisting of a mix of fixed and mobile processing facilities. The model considers a variable biomass yield profile and the mobile fast pyrolysis technology. The mixed-integer linear programming model developed identifies the optimal biofuel production and biomass harvesting schedule schemes under the objective of profit maximization. It was applied in the case study of marginal lands in Scotland, which are assumed to be planted with Miscanthus. The trade-offs observed between economies of scale against the transportation costs, the effect of the relocation costs and the contribution of storage capacity were investigated. The results showed that, in most cases, harvesting is most conc... [more]

This paper provides insight into the optimal configuration scheme of the grid-connected inverters based on harmonic amplification suppression. The connection of the inverters changes the natural resonance frequencies of the grid. Hence, a reasonable configuration of grid-connected inverters can optimize the impedance distribution and shift the natural resonance frequencies to frequency bands farther away from the harmonic sources. We proposed a scheme of site selection and determination of the number of inverters to suppress harmonic amplification. The resonance frequencies and modal frequency sensitivities (MFSs) were obtained by the resonance modal analysis (RMA). Moreover, the concepts of security region and insecurity region of resonance frequency were illustrated. The grid-connected sites can be obtained by calculating the participation factors (PFs) of the resonance frequencies in the insecurity region. Furthermore, the optimal number was determined by building the Norton equival... [more]

In this paper, a series of equilibrium and kinetic experiments of Hg(II) removal in a single-stage batch reactor on natural (NZ) and sulfur-impregnated zeolite (SZ) were performed. Batch sorption of Hg(II) on zeolites was studied using different isothermal and kinetic models. It was found to be best described by the Brouers-Sotolongo isotherm and the Vermeulen’s approximation, which were applied in optimizing the mass and contact time in two-stage cross-current and counter-current flow batch reactors based on the desired criterion of 99.9% removal efficiency. Mathematical models for minimizing zeolite mass and contact time were developed and experimentally verified. The optimum minimum masses of NZ and SZ were calculated for all systems, and a significant saving in SZ consumption was found when the counter-current design was applied. The toxicity characteristic leaching procedure (TCLP) was applied to mercury contaminated soil from the Idrija mine region in Slovenia to evaluate potenti... [more]

Multi-attribute decision-making (MADM) refers to making preference decisions via assessing a finite number of pre-specified alternatives under multiple and usually conflicting attributes. Many problems in the field of additive manufacturing (AM) are essentially MADM problems or can be converted into MADM problems. Recently, a variety of MADM methods have been applied to solve MADM problems in AM. This generates a series of interesting questions: What is the general trend of this research topic from the perspective of published articles every year? Which journals published the most articles on the research topic? Which articles on the research topic are the most cited? What MADM methods have been applied to the field of AM? What are the main strengths and weaknesses of each MADM method used? Which MADM method is the most used one in this field? What specific problems in AM have been tackled via using MADM methods? What are the main issues in existing MADM methods for AM that need to be... [more]

The extraction of xylanase was performed using an aqueous two-phase system (ATPS) based on polyethylene glycol (PEG1540) and various salts. Preliminary studies in a batch extractor showed that the highest extraction efficiency, E = 79.63 ± 5.21%, and purification factor, PF = 1.26 ± 0.25, were obtained with sodium citrate dihydrate-H2O-PEG1540-based ATPS for an extraction time of 10 min. The process was optimized using the experimental Box-Behnken design at three levels with three factors: extraction time (t), xylanase concentration (γ), and mass fraction of PEG in the ATPS (wPEG). Under optimal process conditions (γ = 0.3 mg/mL, wPEG = 0.21 w/w, and t = 15 min), E = 99.13 ± 1.20% and PF = 6.49 ± 0.05 were achieved. In order to intensify the process, the extraction was performed continuously in microextractors at optimal process conditions. The influence of residence time, different feeding strategies, and channel diameter on extraction efficiency and purification factor was further ex... [more]

Stand-alone DC microgrids have multiple distributed generation (DG) sources that meet the required demand (load) by using droop control to achieve load (current) sharing between the DGs. The use of droop control leads to a voltage drop at the DC bus. This paper presents a distributed secondary control scheme to simultaneously ensure current sharing between the DGs and regulate the DC bus voltage. The proposed control scheme eliminates the voltage deviation and ensures balanced current sharing by combining the voltage and current errors in the designed secondary control loop. A new flight-based artificial bee colony optimization algorithm is proposed. This selects the parameters of the distributed secondary control scheme to achieve the objectives of the proposed controller. A state−space model of the DC microgrid is developed by using eigenvalue observation to test the impacts of the proposed optimized distributed secondary controller on the stability of the DC microgrid system. A real... [more]

The biofuel management of a biofuel-penetrated district heating system is complicated due to its association with multiple and polymorphic uncertainties. To handle uncertainties and system dynamic complexities, an inexact two-stage compound-stochastic mixed-integer programming technique is proposed, innovatively based on the integration of different uncertain optimization approaches. The proposed technique can not only address the inexact recourse problems sourced from multiple and compound uncertainties existing in the pre-regulated biofuel supply−demand match mode, but can also quantitatively analyze the conflicts between the economic target that minimizes the system cost and the risk preference that maximizes the heating service satisfaction. The developed model is applied to a real-world biofuel management case study of a district heating system to obtain the optimal biofuel management schemes subject to supply−demand, policy requirement constraints, and the financial minimization... [more]

In the present study, energy and exergy analyses of a simple supercritical, a split supercritical and a cascade supercritical CO2 cycle are conducted. The bottoming cycles are coupled with the main two-stroke diesel engine of a 6800 TEU container ship. An economic analysis is carried out to calculate the total capital cost of these installations. The functional parameters of these cycles are optimized to minimize the electricity production cost (EPC) using a genetic algorithm. Exergo-economic and exergo-environmental analyses are conducted to calculate the cost of the exergetic streams and various exergo-environmental parameters. A parametric analysis is performed for the optimum bottoming cycle to investigate the impact of ambient conditions on the energetic, exergetic, exergo-economic and exergo-environmental key performance indicators. The theoretical results of the integrated analysis showed that the installation and operation of a waste heat recovery optimized split supercritical... [more]

To maximize food waste utilization, it is necessary to understand the effect of process variables on product distribution. To this day, there is a lack of studies evaluating the effects of the multiple variables of HTC on food waste. A Design of Experiment (DoE) approach has been used to investigate the influence of three process variables on the product distribution and composition of process streams from the HTC of food waste. This work evaluates the effect of hydrothermal carbonization process conditions on the composition and utilization capabilities of hydrochar from food waste. Parametric analysis was carried out with a design of experiments of central composite rotatable design (CCRD) and response surface methodology (RSM). Derringer’s desirability function was employed to perform a multi-response evaluation. The optimized process conditions were 260.4 °C, 29.5 min reaction time, and 19.6% solid load. The predicted optimized responses were EMC = 2.7%, SY = 57.1%, EY = 84.7%, ED... [more]

The design of moisture-durable building enclosures is complicated by the number of materials, exposure conditions, and performance requirements. Hygrothermal simulations are used to assess moisture durability, but these require in-depth knowledge to be properly implemented. Machine learning (ML) offers the opportunity to simplify the design process by eliminating the need to carry out hygrothermal simulations. ML was used to assess the moisture durability of a building enclosure design and simplify the design process. This work used ML to predict the mold index and maximum moisture content of layers in typical residential wall constructions. Results show that ML, within the constraints of the construction, including exposure conditions, does an excellent job in predicting performance compared to hygrothermal simulations with a coefficient of determination, R2, over 0.90. Furthermore, the results indicate that the material properties of the vapor barrier and continuous insulation layer... [more]