Growing ecological standards force the implementation of solutions that will contribute to reducing greenhouse gas (GHG) emissions to the atmosphere. This is particularly important in Poland, whose energy system is almost 80% based on coal. In the interest of low carbon development it is worth considering the optimization of existing old coal-based power plants. The main goal of the research was to present the benefits of modernization of existing boiler equipment and to analyze the combustion process of various types of coal sorts that have a significant impact on the optimization of the production processes of energy media. An analysis of the processes occurring in boiler devices during the combustion of fuel was carried out, which had a significant impact on the quality of generated heat and electricity. The conducted research defined technological solutions for boiler structures that have a significant impact on improving the efficiency of the technological process in heating plant... [more]

Fired bricks represent one of the most popular building materials, of which production is still growing. Since the functional properties of bricks have reached their physical limits, the current development aims at an optimization of production procedures as it goes along with heavy environmental loads. This paper is focused on tailoring the firing procedure to optimize the energy demands. Dealing with five different clays, their heat storage properties are determined using inverse analysis of calorimetric data so that the measurement errors are reduced. Moreover, effective values incorporate the thermal processes that occur during firing. A simplified model of clay samples is then used to calculate the energy demands for reaching an optimal firing scheme. The results show that specific treatment is necessary for particular clays as the energy demands may range between 89 and 173 MJ·m−2, depending on a clay composition. The highest demands were found in the case of clays containing the... [more]

Optimal performance parameters must be found in order to organize efficient heat and mass transfer and effective flue gas cooling using a wet scrubber. Mathematical models are widely used for system optimization. However, a significant number of the available models have application limitations. This study presents a universal model for heat and mass transfer simulation in a scrubber called a fog unit, which has been developed and validated. Validation was performed by comparing the experimental and calculated results. Good agreement was achieved among the data, with differences between results not exceeding 10%. The model facilitates an investigation of the effects of gas flow, droplet size, and sprayed water on heat recovery from flue gas. An experimental matrix for fog unit capacity which included five main variables was designed and analyzed. The boundaries of the parameters are set considering the results of the experiments. The optimization method used is the path of the steepest... [more]

This study investigates the potential of improving the energy efficiency and reducing the lifecycle costs of electric city buses with multispeed gearboxes. A two-speed dual clutch gearbox and a continuously variable transmission were studied and compared to a reference fixed gear ratio powertrain. A novel two-level optimization model was introduced. The top level involves an exhaustive search algorithm and quasi-static vehicle dynamic model for optimizing the two-speed gearbox gear ratios, utilizing efficiency maps for the electric motor and the inverter. The second level is an integer programming model, which finds an optimal gear shifting policy subject to constraints on hysteresis and gear shifting induced losses. The model was applied with a standard driving cycle and additionally with three measured cycles acquired from a prototype battery electric city bus operating on a daily schedule on a suburban route in Espoo, Finland. The results showed that a two-speed gearbox reduced ener... [more]

The optimization issues connected to a landing task of an unmanned aerial vehicle are discussed in the paper, based on a model of a mini-class drone. Three landing scenarios are considered, including minimum-time landing, landing with minimum energy consumption, and planned landing. With the use of classical dynamic programming techniques, including the minimum principle of Pontryagin, as well as the calculus of variations, the optimal altitude reference trajectories are found, to form the altitude control system in such a way as to mimic the profile of the reference trajectory by the actual altitude of the UAV. The simulation results conducted with the use of the Simulink Support Package for Parrot Minidrones verify the correctness and effectiveness of the method, and open the research directions for further analysis, especially to tune altitude controller in a way, as to track the reference profile. Up to this point, optimization tasks considered in the literature, with respect to th... [more]

Electric vehicles (EVs), which have become a fundamental part of the automotive industry, were developed as part of concerted worldwide efforts to reduce dependency on fossil fuels due to their devastating effects on the environment. The aim of this study was to analyse a complete trip using an EV from Toronto to Ottawa (Canada) along Ontario’s Highway 401, considering that use of conventional vehicles powered by petrol or diesel allow one to make this trip without stops; using EVs, it is necessary to recharge the vehicle. For this purpose, an algorithm was developed for optimizing recharging stops during a complete trip. In particular, the simulations analysed the number of stops and specifically where it is possible to recharge taking into account the actual charging stations (CSs) located along the trip and the time of recharge during the stops as a function of the state of charge (SoC) of the vehicle. Using this approach, it was possible to evaluate the suitable coverage of the CSs... [more]

The aim of this study is to optimize a four-cylinder, double-acting α-type Stirling engine with wobble-yoke mechanism using an optimization scheme incorporated with an efficient thermodynamic model. In this study, the non-ideal adiabatic thermodynamic model is improved by taking into account factors including pressure drops due to the sudden expansion or contraction of flow cross-sectional areas in the engine, multiple nodes in the regenerator adopted to accurately capture the temperature gradient in the regenerator, and the dependence of the transport properties (thermal conductivity and dynamic viscosity) of the working fluid on temperature and pressure. A parametric analysis is firstly performed to identify the designed parameters that need to be optimized. In this study, engine optimization is carried out by using the simplified conjugate-gradient method (SCGM). The effects of the weighting coefficients of the objective function are studied. For a particular case considered, the op... [more]

Off-grid power systems based on photovoltaic and battery energy storage systems are becoming a solution of great interest for rural electrification. The storage system is one of the most crucial components since inappropriate design can affect reliability and final costs. Therefore, it is necessary to adopt reliable models able to realistically reproduce the working condition of the application. In this paper, different models of lithium-ion battery are considered in the design process of a microgrid. Two modeling approaches (analytical and electrical) are developed based on experimental measurements. The derived models have been integrated in a methodology for the robust design of off-grid electric power systems which has been implemented in a MATLAB-based computational tool named Poli.NRG (POLItecnico di Milano—Network Robust desiGn). The procedure has been applied to a real-life case study to compare the different battery energy storage system models and to show how they impact on t... [more]

Acrylic acid, a versatile chemical intermediate, is typically manufactured via a two-step process involving the selective oxidation of propylene and acrolein. This work presents an optimized simulation on Aspen Plus® (AspenTech, Bedford, MA, USA) of the production of acrylic acid, with focus on the optimum design and operation of the reactor train, and modification for reduction in energy usage. In the propylene oxidation reactor, an inert pre-heating zone was designed to make use of the excess energy present in the exothermic process fluid and carried within the molten salt cooling fluid circuit. In the acrolein oxidation reactor, injection of cold air was used as a means to absorb the reaction heat. The optimization methodology employed aimed to minimize the total capital expenditure (i.e., equipment sizing) and operating costs (heat exchange network) for the required acrylic acid production and design constraints. The design constraints were based on the selected reaction kinetics a... [more]

The integration of distributed energy resources (DERs), e.g., electric vehicles (EVs) and renewable distributed generation (DG), in the electrical distribution system (EDS) brings advantages to society, but also introduces technical challenges (e.g., overloading and voltage issues). A DER aggregator, which has agreements with DERs to manage their consumption/generation, could collaborate with the EDS operator to mitigate those technical challenges. Previous approaches have mainly focused on the aggregator’s strategy to manage demand, aiming at the maximization of profits. Therefore, methods to support the aggregator’s strategy need to be extended to facilitate the integration of renewable DG, leading to an enhanced coordination of DERs. This paper proposes a linear programming model for the aggregator’s coordination strategy to maximize its profit through the management of DERs and the participation in the day-ahead reserve market. The model uses EV charging control to provide up/down... [more]

Seasonal storage of thermal energy, by pumping heated water through a borehole array in the summer, and reversing the water flow to extract heat in the winter, can ameliorate some of the intermittency of renewable energy sources. Simulation can be a valuable tool in enhancing the efficiency of such storage systems. This paper develops a simple, efficient mathematical model of spatial temperature dynamics that focuses on the radial water flow in a cylindrical borehole array. The model calculates the time course of the temperature difference between outgoing and incoming water accurately, and allows new optimization strategies to be explored easily. A strategy based on discharging water heated by the array before it reaches the array center can increase the storage capacity by 25% for a system with a 20% smaller radius than the well-studied Drake Landing system. If the density of boreholes is also doubled, the improvement is 29%.

Vehicle-to-grid (V2G) technology heralds great promise as a demand-side resource to contribute to more efficient grid management and promote the use of decentralized renewable energy. In this light, we propose a new optimization model for the sustainable energy and reserve market management in renewable-driven microgrid (RMG) plug-in electric vehicles (PEVs) parking lot systems. The RMG is composed of a hybrid photovoltaic/wind/hydrogen energy and storage system, along with local dispatchable generation units and bidirectional grid connection. The RMG is coupled to a smart PEVs parking lot, which is equipped with grid-to-vehicle (G2V) and V2G technologies allowing for not only PEVs aggregation and control but also optimal allocation of energy resources. Time-of-use (TOU) prices are considered in a demand response program (DRP) to enhance both economic and environmental performances by encouraging end-users to shift their energy demands from peak to off-peak time periods. Additionally,... [more]

Biodiesel is a proven alternative fuel that can serve as a substitute for petroleum diesel due to its renewability, non-toxicity, sulphur-free nature and superior lubricity. Waste-based non-edible oils are studied as potential biodiesel feedstocks owing to the focus on the valorisation of waste products. Instead of being treated as municipal waste, waste coffee grounds (WCG) can be utilised for oil extraction, thereby recovering an energy source in the form of biodiesel. This study evaluates oil extraction from WCG using ultrasonic and Soxhlet techniques, followed by biodiesel conversion using an ultrasonic-assisted transesterification process. It was found that n-hexane was the most effective solvent for the oil extraction process and ultrasonic-assisted technology offers a 13.5% higher yield compared to the conventional Soxhlet extraction process. Solid-to-solvent ratio and extraction time of the oil extraction process from the dried waste coffee grounds (DWCG) after the brewing proc... [more]

Artificial lift methods have applications in oil wells where oil production is no longer possible due to natural reservoir energy, so this necessary energy is added by introducing lift methods. In order to achieve optimum production, the selection of an artificial lift method is very important. This paper uses fuzzy logic as a mathematical and conceptual model for selection of the optimal artificial lift method. The outcome or IF-THEN rules, as the central part of the model, is based on empirical data from the selected oil fields. Results are presented in two ways: according to the surfaces of irregular geometric bodies, and their gravity with the scattering of results, i.e., on smaller and greater possibilities of interpreting results when there are small differences in outputs. Finally, a sensitivity analysis of the model is presented.

This paper aims at the optimal designing of a stand-alone microgrid (PV/wind/battery/diesel) system, which can be utilized to meet the demand load requirements of a small residential area in Kasuga City, Fukuoka. The simulation part is developed to estimate the electrical power generated by each component, taking into account the variation of the weather parameters, such as wind, solar irradiation, and ambient temperature. The optimal system design is then based on the Particle Swarm Optimization (PSO) method to find the optimal configuration of the proposed system, using the least-cost perspective approach.

Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs ch... [more]

In recent decades, many EU and national regulations have been issued in order to increase the energy efficiency in different sectors and, consequently, to reduce environmental pollution. In the building sector, energy efficiency interventions are usually based on the use of innovative insulated materials and on the installation of cogeneration and tri-generation units, as well as solar technologies. New and retrofitted buildings are more and more commonly being called “smart buildings”, since they are characterized by the installation of electric and thermal power generation units, energy storage systems, and flexible loads; the presence of such technologies determines the necessity of installing Building Energy Management Systems (BEMSs), which are used to optimally manage their operation. The present paper proposes a BEMS for a smart building, equipped with plants based on renewables (photovoltaics, solar thermal panels, and geothermal heat pump), where the heating and cooling demand... [more]

Within the framework of blade aerodynamic design, the maximum aerodynamic efficiency, power production, and minimum thrust force are the targets to obtain. This paper describes an improved optimization framework for blade aerodynamic design under realistic conditions, while considering multiple design parameters. The relationship between the objective function and the design parameters, such as the chord length, maximum chord, and twist angle, were obtained by using the second-order response surface methodology (RSM). Moreover, the identified parameters were organized to optimize the aerodynamic design of the blades. Furthermore, the initial and optimized blade geometries were compared and showed that the performance of the optimized blade improved significantly. In fact, the efficiency was increased by approximately 10%, although its thrust was not varied. In addition, to demonstrate the improvement in the resulting optimized blades, the annual energy production (AEP) was estimated wh... [more]

Anode-supported solid oxide fuel cells (SOFCs) model based on artificial neural network (ANN) and optimized design variables were modeled. The input parameters of the anode-supported SOFC model developed in this study are as follows: current density, temperature, electrolyte thickness, anode thickness, anode porosity, and cathode thickness. Voltage was estimated from the SOFC model with the input parameters. Numerical results show that the SOFC model constructed in this study can represent the actual SOFC characteristics very well. There are four design parameters to be optimized: electrolyte, anode, cathode thickness, and anode porosity. To derive the optimal combination of the design parameters, we have used a multi-armed bandit algorithm (MAB), and developed a methodology for deriving near-optimal parameter set without searching for all possible parameter sets.

In this paper, a dual-stage modeling and optimization framework has been developed to obtain an optimal combination and size of wayside energy storage systems (WESSs) for application in DC rail transportation. Energy storage technologies may consist of a standalone battery, a standalone supercapacitor, a standalone flywheel, or a combination of these. Results from the dual-stage modeling and optimization process have been utilized for deducing an application-specific composition of type and size of the WESSs. These applications consist of different percentages of energy saving due to regenerative braking, voltage regulation, peak demand reduction, estimated payback period, and system resiliency. In the first stage, sizes of the ESSs have been estimated using developed detailed mathematical models, and optimized using the Genetic Algorithm (GA). In the second stage, the respective sizes of ESSs are simulated by developing an all-inclusive model of the transit system, ESS and ESS managem... [more]

Environmental and economic needs drive the increased penetration of intermittent renewable energy in electricity grids, enhancing uncertainty in the prediction of market conditions and network constraints. Thereafter, the importance of energy systems with flexible dispatch is reinforced, ensuring energy storage as an essential asset for these systems to be able to balance production and demand. In order to do so, such systems should participate in wholesale energy markets, enabling competition among all players, including conventional power plants. Consequently, an effective dispatch schedule considering market and resource uncertainties is crucial. In this context, an innovative dispatch optimization strategy for schedule planning of renewable systems with storage is presented. Based on an optimization algorithm combined with a machine-learning approach, the proposed method develops a financial optimal schedule with the incorporation of uncertainty information. Simulations performed w... [more]

, due to its high kernel-oil yield (±50%) and long productivity (±70 years), is considered to be a promising feedstock for biodiesel production. In addition, this plant, which can thrive on marginal lands, is classified as a non-edible oil since it contains a toxin known as eleostearic acid. The present study aimed to optimize the esterification step in biodiesel production from R.trisperma oil catalyzed using sulfonic ion exchange resin Lewatit K2640. The optimization step was performed using a response surface methodology through the incorporation of a central composite design. A kinetic study was performed as well, based on the assumption of a pseudo-homogeneous second-order model. Catalyst loading was found to have the most significant impact on acid value, followed by temperature and methanol-to-oil molar ratio. The optimal conditions for the esterification step were 92 °C temperature, 5.34% catalyst loading, and 5.82:1 methanol-to-oil molar ratio. The acid value and FFA conversio... [more]

In recent years, residential users have begun to be equipped with micro-CHP (combined heat and power) generation technologies with the aim of decreasing primary energy consumption and reducing environmental impact. In these systems, the prime mover supplies both thermal and electrical energy, and an auxiliary boiler and the national electrical grid are employed as supplementary systems. In this paper, a simulation model, which accounts for component efficiency and energy balance, was developed to replicate the interaction between the users and the energy systems in order to minimize primary energy consumption. The simulation model identified the optimal operation strategy of two residential users by investigating different energy system configurations by means of a dynamic programming algorithm. The reference scenario was compared to three different scenarios by considering independent energy systems, shared thermal and electrical energy storage and also the shared prime mover. Such a... [more]

Retrofitting of industrial heat recovery systems can contribute significantly to meeting energy efficiency targets for industrial plants. One issue to consider when screening retrofit design proposals is that industrial heat recovery systems must be able to handle variations, e.g., in inlet temperatures or heat capacity flow rates, in such a way that operational targets are reached. Consequently, there is a need for systematic retrofitting methodologies that are applicable to multi-period heat exchanger networks (HENs). In this study, a framework was developed to achieve flexible and cost-efficient retrofit measures of (industrial) HENs. The main idea is to split the retrofitting processes into several sub-steps. This splitting allows well-proven (single period) retrofit methodologies to be used to generate different design proposals, which are collected in a superstructure. By means of structural feasibility assessment, structurally infeasible design proposals can be discarded from fu... [more]

Smart cities directly rely on a variety of elements, including water, gas, electricity, buildings, services, transportation networks, and others. Lack of properly designed transportation networks may cause different economic and safety concerns. Highway−rail grade crossings are known to be a hazardous point in the transportation network, considering a remarkable number of accidents recorded annually between highway users and trains, and even solely between highway users at highway−rail grade crossings. Hence, safety improvement at highway−rail grade crossings is a challenging issue for smart city authorities, given limitations in monetary resources. In this study, two optimization models are developed for resource allocation among highway−rail grade crossings to minimize the overall hazard and the overall hazard severity, taking into account the available budget limitations. The optimization models are solved by CPLEX to the global optimality. Moreover, some heuristic algorithms are pr... [more]