A record amount of renewable energy has been added to global electricity generation in recent years. Among the renewable energy sources, solar photovoltaic (PV) is the most popular energy source integrated into low voltage distribution networks. However, the voltage limits and current-carrying capacity of the conductors become a barrier to maximizing the PV-hosting capacity in low voltage distribution networks. This paper presents an optimization approach to maximize the PV-hosting capacity in order to fully utilize the existing low voltage distribution network assets. To achieve the maximum PV-hosting capacity of the network, a novel method based on the dynamic line rating of the low voltage distribution network, the coordinated operation of voltage control methods and the PV re-phasing technique was introduced and validated using a case study. The results show that the proposed methodology can enhance the PV-hosting capacity by 53.5% when compared to existing practices.

The rising demand for electricity, economic benefits, and environmental pressures related to the use of fossil fuels are driving electricity generation mostly from renewable energy sources. One of the main challenges in renewable energy generation is uncertainty involved in forecasting because of the intermittent nature of renewable sources. The demand also varies according to the time of day, the season, the location, the climate, and the availability of resources. Microgrids offer a potential solution for the integration of small-scale renewable energy sources and loads along with energy storage systems and other non-renewable sources. However, intermittent generation and varying demand need to be matched to provide stable power to consumers. Therefore, it is crucial to design an energy management system to effectively manage the energy sources and supply loads for reliable and efficient operation. This paper reviews different techniques proposed in the literature to achieve the obje... [more]

Photovoltaic-thermal (PVT) technologies have demonstrated several attractive features, such as higher power and comparative efficiencies. Improving the thermal recovery from the PVT system would further improve the power output and the efficiency of the PVT system. This paper identifies the best operating factors of nanofluid-based PV thermal/nano-enhanced phase change material using artificial intelligence. The target is the maximization of thermal energy and exergy outputs. The suggested approach combines ANFIS modelling and particle swarm optimization (PSO). Four operating factors are taken into consideration: PCM (phase change material) layer thickness, HTF (heat transfer fluid) mass flow rate, MFNPCM (“mass fraction of nanoparticles in PCM”) and MFNfluid (“mass fraction of nanoparticles in nanofluid”). Using a dataset, an “adaptive neuro-fuzzy inference system” (ANFIS) model has been established for simulating the thermal energy and exergy outputs in terms of the mentioned operati... [more]

One of the most crucial control aspects in electric power networks is ensuring constant voltage levels throughout different circumstances. To overcome this problem, an automatic voltage regulator (AVR) is installed in the electrical power networks to preserve the voltage at its allowable range. In this paper, a fuzzy-based PID controller was used to enhance the AVR dynamic performance under several operating conditions. Moreover, an Equilibrium Optimizer (EO) algorithm was used to initialize the controller gains. The validation of the proposed controller was proven through three different systems. The first was a simple AVR system under fixed and dynamic references. The proposed fuzzy EO PID controller proved its superiority in this case through the reduction of voltage overshoot by around 3−28% compared with the reported methods in the literature. Then, the fault-ride through capability of the proposed controller was proven through the second system, which was the Kundur two-area syst... [more]

In buildings with good-quality thermal insulation of external partitions, the main component of the building’s heat balance is the heat demand for ventilation. The reduction of this energy demand cannot be achieved at the expense of thermal comfort of the occupants and indoor air quality. The aim of this article is to analyze the impact of various ventilation strategy (natural and mechanical) on heating demand, thermal comfort, and CO2 concentration in a single-family house located in Poland. The benefits of using fans integrated with the earth tube were tested. The study was based on the numerical energy simulation of a multi-zone building model for the entire calendar year. Contam, EnergyPlus, and Python programs were used to perform calculations. The thermal model was validated on the results of temperature measurements in the building. To obtain the best solutions, the parameters of the systems considered have been optimized with the use of genetic algorithms. Various optimal param... [more]

The operation of industrial supply technology is a broad field for optimization. Industrial cooling plants are often (a) composed of several components, (b) linked using network technology, (c) physically interconnected, and (d) complex regarding the effect of set-points and operating points in every entity. This leads to the possibility of overall optimization. An example containing a cooling tower, water circulations, and chillers entails a non-linear optimization problem with five dimensions. The decomposition of such a system allows the modeling of separate subsystems which can be structured according to the physical topology. An established method for energy performance indicators (EnPI) helps to formulate an optimization problem in a coherent way. The novel optimization algorithm OptTopo strives for efficient set-points by traversing a graph representation of the overall system. The advantages are (a) the ability to combine models of several types (e.g., neural networks and polyn... [more]

The design of new dual-purpose thermal desalination plants is a combinatory problem because the optimal process configuration strongly depends on the desired targets of electricity and freshwater. This paper proposes a mathematical model for selecting the optimal structure, the operating conditions, and sizes of all system components of dual-purpose thermal desalination plants. Electricity is supposed to be generated by a combined-cycle heat and power plant (CCHPP) with the following candidate structures: (a) one or two gas turbines; (b) one or two additional burners in the heat recovery steam generator; (c) the presence or missing a medium-pressure steam turbine; (d) steam generation and reheating at low pressure. Freshwater is supposed to be obtained from two candidate thermal processes: and (e) a multi-effect distillation (MED) or a multi-stage flash (MSF) system. The number of effects in MED and stages in MSF are also discrete decisions. Different case studies are presented to show... [more]

The complexity and uncertainty of power sources connected to transmission networks need to be considered. Planners need information on the sustainability and economics of transmission network expansion planning (TNEP). This work presents a newly proposed method for TNEP that considers high-penetration solar energy by using the particle swarm optimization (PSO) algorithm. The power sources, thermal and hydropower plants, and conditions of load were set in the account, including an uncertain power source and solar energy (PV). The optimal sizing and locating of the PV to be connected to the network were determined by the PSO. The PV grid code was set in the account. The new line’s investment cost and equipment was analyzed. The PV cost was considered based on the power loss, and the system’s reliability was improved. The IEEE 118 bus test system and Lao PDR’s system were requested to test the proposed practice. The results demonstrate that the proposed TNEP method is robust and feasible.... [more]

This paper examines the issue of strategic planning of fuel supplies in combined heat and power systems. This is a major challenge in energy modeling because heating-degree day calculation methods only address short-term horizons and are not suitable for the long-term planning of fuel supplies. In this work, a comprehensive method is proposed for strategic fuel supply planning of independent heat producers. The method considers changes in the market dynamics of residential and commercial properties, the annual rate of customer acquisition by the network operator, customer disconnections, as well as the thermal modernization of buildings for estimating the long-term thermal energy demand of an urban area. Moreover, the method develops a mathematical model to minimize production costs, taking into account the technical constraints of the system. The proposed strategic planning tool, in addition to information on the quantities of fuel consumed for heat and electricity production, also pr... [more]

With increased interests in affordable energy resources, a cleaner environment, and sustainability, more objectives and operational obligations have been introduced to recent power plant control systems. This paper presents a verified load frequency model predictive control (MPC) that aims to satisfy the load demand of three practical generation technologies, which are wind energy systems, clean coal supercritical (SC) power plants, and dual-fuel gas turbines (GTs). Simplified state-space models for the two thermal units were constructed by concepts of subspace identification, whereas the individual wind turbine integration was implicated by the Hammerstein−Wiener (HW) model and then augmented from the output to simulate the effect of a wind farm, assuming similar power harvesting from all turbines in the farm. A practical strategy of control was then suggested, which was as follows: with a changing load demand, the available harvested wind energy must be fully admitted to the network... [more]

This paper reviews the current techniques used in energy management systems to optimize energy schedules into microgrids, accounting for uncertainties for various time frames (day-ahead and real-time operations). The current uncertainties affecting applications, including residential, commercial, virtual power plants, electric mobility, and multi-carrier microgrids, are the main subjects of this article. We outline the most recent modeling approaches to describe the uncertainties associated with various microgrid applications, such as prediction errors, load consumption, degradation, and state of health. The modeling approaches discussed in this article are probabilistic, possibilistic, information gap theory, and deterministic. Then, the paper presents and compares the current optimization techniques, considering the uncertainties in their problem formulations, such as stochastic, robust, fuzzy optimization, information gap theory, model predictive control, multiparametric programming... [more]

This review deals with the simulation and optimization of the dry- and wet-torrefaction processes of lignocellulosic biomass. The torrefaction pretreatment regards the production of enhanced biofuels and other materials. Dry torrefaction is a mild pyrolytic treatment method under an oxidative or non-oxidative atmosphere and can improve lignocellulosic biomass solid residue heating properties by reducing its oxygen content. Wet torrefaction usually uses pure water in an autoclave and is also known as hydrothermal carbonization, hydrothermal torrefaction, hot water extraction, autohydrolysis, hydrothermolysis, hot compressed water treatment, water hydrolysis, aqueous fractionation, aqueous liquefaction or solvolysis/aquasolv, or pressure cooking. In the case of treatment with acid aquatic solutions, wet torrefaction is called acid-catalyzed wet torrefaction. Wet torrefaction produces fermentable monosaccharides and oligosaccharides as well as solid residue with enhanced higher heating va... [more]

In Ecuador, the implementation of hydroelectric power plants has had a remarkable growth in the energy sector due to its high efficiency, low environmental impact, and opportunities to generate employment. One of the sectors with the greatest benefits from this type of energy has been the rural sector, where several small-scale hydroelectric plants (0.5 MW−10 MW) have been installed, usually with Pelton turbines. Although these turbines are highly efficient, one of the challenges is to obtain the optimal geometry of the bucket to take advantage of the greatest amount of energy from the water, avoiding the separation of the fluid. In this context, this study focuses on the development of an analytical and iterative methodology that allows for the determining of the appropriate dimensions of the buckets to achieve maximum turbine efficiency. For that, a parametric model has been proposed considering the dimensions and main angles of the bucket, the net hydraulic head and the working flow... [more]

Geothermal heating is considered to be one of the low-carbon-energy technologies for building heating. Aiming at the problem that the operating cost and investment cost of geothermal heating systems are still high, the conventional geothermal heating system coupled with energy storage for office building heating is studied in this paper. Four operational strategy models of the coupled system are established based on time-of-use electricity prices. A genetic algorithm is used to find the optimal value of each decision variable using minimization of levelized cost of heat (LCOH) as the objective function. The influences of electricity and equipment prices on the optimal values of the decision variables are discussed. Four operation strategies are investigated. If only operating cost is considered in the optimization, comparison shows that the best operation strategy is the one giving high priority to use the energy storage tank for heating during the peak electricity period. However, if... [more]

Currently, solar energy is one of the leading renewable energy sources that help support energy transition into decarbonized energy systems for a safer future. This work provides a comprehensive review of mathematical modeling used to simulate the performance of photovoltaic (PV) modules. The meteorological parameters that influence the performance of PV modules are also presented. Various deterministic and probabilistic mathematical modeling methodologies have been investigated. Moreover, the metaheuristic methods used in the parameter extraction of diode models of the PV equivalent circuits are addressed in this article to encourage the adoption of algorithms that can predict the parameters with the highest precision possible. With the significant increase in the computational power of workstations and personal computers, soft computing algorithms are expected to attract more attention and dominate other algorithms. The different error expressions used in formulating objective functi... [more]

Spatial separation into acidogenic and methanogenic stages is considered a viable option to ensure process stability, energy efficiency and the better control of key anaerobic digestion (AD) parameters. The elucidation of the optimal modes of two-stage AD for the maximization of the recovery of biofuels (H2 and CH4) is still an urgent task, the main optimization criteria being the highest energy yield (EY) and energy production rate (EPR). In this work, a response surface methodology was used for an optimization of energy production from the two-stage mesophilic−thermophilic AD of cheese whey (CW). Three dilution rates of CW, providing values of 10.9, 14.53 and 21.8 g for the chemical oxygen demand (COD)/L in the influent and three hydraulic retention times (HRTs) (1, 2 and 3 days) in methanogenic biofilters at a constant HRT in an acidogenic biofilter of 0.42 days, were tested to optimize the EY and EPR. The desirability approach produced combined optimum conditions as follows: the di... [more]

Due to the increasing sales of extended-range hybrid vehicles and the increasingly stringent emission regulations for light vehicles in China, the performance and emission of diesel engines for range extenders in the plateau region have attracted increasing attention. In order to obtain the superior performance of diesel engines for range extenders operating at high altitudes, a multi-objective optimization of the optimal economic operating point of the diesel engine was performed at an altitude of 1960 m. A diesel engine system model with MC-EGR-VNT (MEV) technology was developed using GT-Power based on the data of the engine bench to analyze the effects of the Miller cycle (MC), exhaust gas recirculation (EGR), and variable nozzle turbine (VNT) technologies on the power, economy, and emission performance of high-speed diesel engines. The response surface method (RSM) design was carried out with the Miller cycle rate (MCR), EGR value opening, VNT nozzle opening as variable factors and... [more]

Knowledge of the influence of factors determining energy consumption in buildings is very important for the possibility of effective energy saving. This article describes the results of an original study on the analysis of the annual energy demand for heating (QH;nd), cooling (QC;nd), and annual usable energy demand (QH/C;nd = QH;nd + QC;nd) assumed as objective functions of a designed single-family building, which can be classified as a typical representative of currently built houses in Poland. It was assumed that the object of study was located in the climatic conditions of north-eastern Poland. The study takes into consideration three groups of selected parameters: architectural/spatial, structural, and physical properties of windows. The research was carried out in a single-family building, as energy consumption in residential buildings accounts for a significant part of the total energy consumption in buildings. In the group of architectural/spatial parameters, the heig... [more]

Pick-and-place operations are basic, and are currently the most common for robots operating in the industry. Massive applications makes it reasonable to ask whether, and to what extent these operations are realised in a way that guarantees rational energy consumption. In many cases, the answer to such a question is neither positive nor known. Therefore, this paper attempts to present a rational and systematic approach to the low-energy pick-and-place operations performed by robots. This paper describes a new approach for the robot’s tool centre point path planning, which enables the minimisation of energy consumption wherein productivity in preserved, and where care is taken for the persistence of the critical mechanical components of the robot cooperating with the autonomous mobile platform. The effectiveness of the described approach has been proven from the results of the theoretical, simulation, experimental and implementation tests carried out using an industrial articulated robot... [more]

The high penetration of photovoltaic solar generation and electric vehicles in developing countries and with vertically integrated electricity markets with restrictive regulatory policies enhance demand management and the participation of prosumers in optimizing their resources. In this sense, the research presents a demand management methodology based on the prosumer model for recharging electric vehicles through optimization based on linear programming to minimize recharging costs, considering the stochasticity of the solar radiation variables, vehicular mobility patterns, consumer preferences, and optimal location of charging stations through surveys and predictive tools such as PVsyst and GAMS, in such a way that the energy demand for recharging electric vehicles is met. This way, the methodology reduces power demand peaks and mitigates the economic and technical impact on distribution networks. This case study has been modelled with real information from electric vehicles, distrib... [more]

Aerodynamic lift force acting on the solar structure is important while designing the counterweight for rooftop-mounted solar systems. Due to their unique configuration, the load estimated for solar structures using international building codes can be either higher or lower than the actual. Computational Fluid Dynamics(CFD) simulations haveproven to be an efficient tool for estimating wind loads on solar panels for design purposes and identifying critical design cases. Computational Fluid Dynamics (CFD) simulations usually require high computation power, and slight changes in geometry to find optimum configuration can be time-consuming. An optimization method to minimize lift force effects on solar photovoltaic (PV) arrays installed on rooftops usesthe Computational Fluid Dynamics (CFD)and genetic algorithms proposed in this paper. The tilt angle and pitch between two rows of solar panels were parameterized, and a genetic algorithm was used to search for aconfiguration resulting in min... [more]

The present study investigates low-grade heat utilization in ejector refrigeration systems under hot climatic conditions. A variable area ejector is used to maximize the harvested heat from the generator of the solar system at peak times. Exergy, economic, and exergoeconomic analyses are conducted to evaluate the performance of the system. A thermodynamic model of the system has been developed using Ebsilon Professional software. Available experimental and theoretical data validate the results. The effects of properties of the working fluids, ejector geometry, and operation conditions are also evaluated. It was found that the coefficient of performance of the system reached 0.45 at a generator pressure of 3 bars. Furthermore, it was noticed that the overall exergy efficiency could be increased for a fixed generator temperature while increasing the ejector area ratio. A value of 21% exergetic efficiency was calculated for the system. The exergoeconomic analysis of the system demonstrate... [more]

Norwegian offshore wind farms may be able to supply power to offshore oil and gas platforms in the near future thanks to the expeditious development of offshore wind technology. This would result in a reduction in CO2 emissions from oil and gas offshore installations, which are currently powered predominantly by gas turbines. The challenge with using wind power is that offshore oil and gas installations require a fairly constant and stable source of power, whereas wind power typically exhibits significant fluctuations over time. The purpose of this study is to perform a technical feasibility evaluation of using wind power to supply an offshore oil and gas installation on the basis of dynamic process simulations. Throughout the study, only the topside processing system is considered, since it is the most energy-intensive part of an oil and gas facility. An offshore field on the Norwegian Continental Shelf is used as a case study. The results indicate that, when the processing system ope... [more]

A novel asymmetric spoke-type interior permanent magnet (AS-IPM) machine is proposed in this paper. It utilizes the magnetic-field-shifting (MFS) effect to improve the torque performance, which achieves a high utilization ratio of both permanent magnet (PM) torque and reluctance torque. In addition, a general pattern of rotor topologies is proposed to represent all possible machine structures. Various rotor structures can be obtained by changing the design parameters of the general pattern. A non-dominated sorting genetic algorithm II (NSGA-II) is adopted to automatically search for optimal rotor configurations. With the aid of the optimization program, an asymmetric spoke-type rotor structure with improved performance is obtained. To showcase the advantages of the proposed machine, the electromagnetic performance is compared between a conventional spoke-type interior permanent magnet (S-IPM) machine and a proposed AS-IPM machine. The finite-element simulation results show that the opt... [more]

The direct reduction process has been developed and investigated in recent years due to less pollution than other methods. In this work, the first direct reduction iron oxide (DRI) modeling has been developed using artificial neural networks (ANN) algorithms such as the multilayer perceptron (MLP) and radial basis function (RBF) models. A DRI operation takes place inside the shaft furnace. A shaft furnace reactor is a gas-solid reactor that transforms iron oxide particles into sponge iron. Because of its low environmental pollution, the MIDREX process, one of the DRI procedures, has received much attention in recent years. The main purpose of the shaft furnace is to achieve the desired percentage of solid conversion output from the furnace. The network parameters were optimized, and an algorithm was developed to achieve an optimum NN model. The results showed that the MLP network has a minimum squared error (MSE) of 8.95 × 10−6, which is the lowest error compared to the RBF network mod... [more]