As the world is keen on cleaner and sustainable energy, hydrogen energy has the potential to be part of the green energy transition to replace fossil fuels and mitigate climate change. However, hydrogen energy storage is a difficult task since physical storage in the form of compressed gas under high pressure is associated with safety issues. Another form of hydrogen storage is material-based storage, which is the safest way to store hydrogen energy in a particulate matter, known as metal hydrides. Metal hydrides can store hydrogen at room temperature and use less volume to store the same amount of hydrogen compared to classical gas tanks. The challenges with the metal hydrides reactor are their slow charging process and the requirement of proper thermal management during the charging process. In this study, a metal hydride reactor model is developed in COMSOL Multiphysics, and the associated heat transfer simulations are performed. The main objective of this research is to optimize th... [more]

In nonlinear Model Predictive Control (MPC) algorithms, the number of cost-function evaluations and the resulting calculation time depend on the initial solution to the nonlinear optimisation task. Since calculations must be performed fast on-line, the objective is to minimise these indicators. This work discusses twelve initialisation strategies for nonlinear MPC. In general, three categories of strategies are discussed: (a) five simple strategies, including constant and random guesses as well as the one based on the previous optimal solution, (b) three strategies that utilise a neural approximator and an inverse nonlinear static model of the process and (c) four hybrid original methods developed by the authors in which an auxiliary quadratic optimisation task is solved or an explicit MPC controller is used; in both approaches, linear or successively linearised on-line models can be used. Efficiency of all methods is thoroughly discussed for a neutralisation reactor benchmark process... [more]

Even though many studies have been deployed to determine the optimal planning and operation of microgrids, limited research was discussed to determine the optimal microgrids’ geographical boundaries. This paper proposes a zonal-based optimal microgrid identification model aiming at identifying the optimal microgrids topology in the current distribution systems through zoning the network into several clusters. In addition, the proposed model was developed as a mixed-integer linear programming (MILP) problem that identifies the optimal capacity and location of installing distributed energy resources (DERs), including but not limited to renewable energy resources and Battery Energy Storage Systems (BESS), within the determined microgrid’s boundaries. Moreover, it investigates the impact of incorporating the BESS in boosting the DERs’ penetration on the optimal centralized microgrid. Numerical simulations on the IEEE-33 bus test system demonstrate the features and effectiveness of the prop... [more]

As a direct energy converter between heat and electricity, thermoelectric generators (TEGs) have potential applications including recovery of waste heat, and solar thermoelectric power generation. Geometric parameter and material are two critical factors to improve the TEG performance. However, the strategies base on structure design and material development are always separated. There are limited studies on the effects of consolidating them simultaneously. Here, an idea of segmented material coupled with irregularly variable cross-section design was conceived to further improve the TEG output power. The performance of TEGs with rectangular leg, segmented leg, variable cross-sectional leg, and the new design are compared. The coupling effects between various mechanisms are revealed, which are responsible for the superior performance provided by the developed design. Based on this knowledge, a multiparameters optimization was performed through the genetic algorithm to reach the optimal... [more]

The use of a cobalt-iron (VaCoFe) core is investigated as an alternative to silicon-iron (FeSi) in the design of interior permanent magnet synchronous motors (IPMSM). Considering VaCoFe and FeSi cores, a spoke-type IPMSM geometry is optimized for a torque range up to 40 N·m, providing a general comparative analysis between materials. This is done considering the application of a four-motor competition vehicle’s powertrain. A genetic optimization algorithm is coupled to the motor’s electromagnetic and thermal hybrid analytical/finite-element model to provide sufficiently accurate results within a feasible time. VaCoFe allows an estimated increase of up to 64% in torque for the same efficiency level, or up to 5% in efficiency for the same torque. After optimization and using a detailed time-dependent model, a potential 3.2% increase in efficiency, a core weight reduction of 4.1%, and a decrease of 9.6% in the motor’s core volume were found for the VaCoFe at 20 N·m. In addition, for the s... [more]

Changing the fuel mix used in the heating industry, i.e., switching to greener fuels, is one of the possible solutions to prevent rising costs for final consumers in the context of rising emission allowance prices. This paper presents a methodology that offers the possibility to perform a comprehensive technical and economic assessment of a theoretical solution—changing the fuel mix of centralized heating sources—and other strategic decisions within a district’s heating systems. Emphasis is placed on fuels with a negative price, such as municipal waste. The presented approach can also be used to assess the effect of other significant changes related to the configuration of district heating systems on the economy of the plant, such as the impact of a decrease in heat demand and implementation of a steam turbine. The key benefit of this paper is an approach based on mathematical modelling of the operation of individual boilers with different operating parameters in terms of their start-u... [more]

The residential sector is a major contributor to the global energy demand. The energy demand for the residential sector is expected to increase substantially in the next few decades. As the residential sector is responsible for almost 40% of overall electricity consumption, the demand response solution is considered the most effective and reliable solution to meet the growing energy demands. Home energy management systems (HEMSs) help manage the electricity demand to optimize energy consumption without compromising consumer comfort. HEMSs operate according to multiple criteria, including electricity cost, peak load reduction, consumer comfort, social welfare, environmental factors, etc. The residential appliance scheduling problem (RASP) is defined as the problem of scheduling household appliances in an efficient manner at appropriate periods with respect to dynamic pricing schemes and incentives provided by utilities. The objectives of RASP are to minimize electricity cost and peak lo... [more]

Maximum power-point-tracking techniques applied for partially shaded photovoltaic array yield maximum power output via operating the panel at its most efficient voltage. Considering the noticeable issues existing with the available methods, including steady-state oscillations, poor tracking capability and complex procedures, a new bioinspired Spotted-Hyena Optimizer (SHO) is proposed. It follows simple implementation steps, and does not require additional controller-parameter tuning to track the optimal power point. To validate the versatility of the proposed method, the SHO algorithm is applied to track the maximum power of different string arrangements under six partial-shade conditions. Further, to authenticate SHO’s methods, its results are compared with perturb-and-observe (P&O), and particle-swarm-optimization (PSO) methods. As a result of its implementation, it is observed that the tracking speed of SHO towards the global convergence for four patterns under 4S2P are 0.34 s, 0.24... [more]

The vehicle-to-grid concept emerged very quickly after the integration of renewable energy resources because of their intermittency and to support the grid during on-peak periods, consequently preventing congestion and any subsequent grid instability. Renewable energies offer a large source of clean energy, but they are not controllable, as they depend on weather conditions. This problem is solved by adding energy storage elements, implementing a demand response through shiftable loads, and the vehicle-to-grid/vehicle-to-home technologies. Indeed, an electric vehicle is equipped with a high-capacity battery, which can be used to store a certain amount of energy and give it back again later when required to fulfill the electricity demand and prevent an energy shortage when the main-grid power is limited for security reasons. In this context, this paper presents a comparative study between two home microgrids, in one of which the concept of vehicle-to-home is integrated to provide a case... [more]

This study proposes a computational design method for determining a hybrid power system’s sizing and ratio values that combines the national electric, solar cell, and fuel cell power sources. The inequality constraints associated with the ranges of power storage exchange and the stored energy are reflected as penalty functions in the overall cost function to be minimized. Using the energy hub model and the actual data for the solar cell power and the load of the residential sector in one Korean city for one hundred days, we optimize the ratio of fuel cell energy and solar cell energy to 0.46:0.54 through our proposed approach. We achieve an average cost-reduction effect of 19.35% compared to the cases in which the fuel-cell energy ratio is set from 0.1 to 0.9 in 0.1 steps. To optimize the sizing and the ratio of fuel-cell energy in the hybrid power system, we propose the modified version of the univariate dynamic encoding algorithm for searches (uDEAS) as a novel optimization method. T... [more]

Optimal dispatch is a major concern in the optimization of hybrid energy systems (HESs). Efficient and effective dispatch models that satisfy the load demand at the minimum net present cost (NPC) are crucial because of the high capital costs of renewable energy technologies. The dispatch algorithms native to hybrid optimization of multiple energy resources (HOMER) software, cycle-charging (CC) and load-following (LF), are powerful for modeling and optimizing HESs. In these control strategies, the decision to use fuel cell systems (FCs) or battery energy storage systems (BESs) at each time step is made based on the lowest cost choice. In addition, the simultaneous operation of a FC with a BES reduces the operating efficiency of the FC. These deficiencies can affect the optimal design of HESs. This study introduces a dispatch algorithm specifically designed to minimize the NPC by maximizing the usage of FCs over other components of HESs. The framework resolves the dispatch deficiencies o... [more]

Economic dispatch optimization and power management are the main concerns for a microgrid (MG). They are always studied and are considered to achieve an efficient operation of the MG by simplifying the control process and decreasing losses. The integration of a small-scale wind turbine (SSWD) into a direct current (DC) MG has an impact on its power and energy management. Excess power produced by renewable energy sources (RESs) is one of the problems that face the reliability of the MG and should be resolved. For this reason, a supervisory system is suggested to manage the excess of power. During the supervision process, some criteria, such as the physical limits and tariffs of the components are taken into account. Then, the suggested power management strategy aims to achieve an instantaneous power balance considering a rule-based power and depends on the above-mentioned criteria. To better meet the power balance, it is necessary to explore the constraints related to the control and su... [more]

Using renewable energy sources instead of fossil fuels is one of the best solutions to overcome greenhouse gas (GHG) emissions. However, in designing clean power generation microgrids, the economic aspects of using renewable energy technologies should be considered. Furthermore, due to the unpredictable nature of renewable energy sources, the reliability of renewable energy microgrids should also be evaluated. Optimized hybrid microgrids based on wind and solar energy can provide cost-effective power generation systems with high reliability. These microgrids can meet the power demands of the consuming units, especially in remote areas. Various techniques have been used to optimize the size of power generation systems based on renewable energy to improve efficiency, maintain reliability, improve the power grid’s resilience, and reduce system costs. Each of these techniques has shown its advantages and disadvantages in optimizing the size of hybrid renewable energy systems. To increase t... [more]

The number of microgrids within a smart distribution grid can be raised in the future. Microgrid-based distribution network reconfiguration is analyzed in this research by taking demand response programs and power-sharing into account to optimize costs and reduce power losses. The suggested method determined the ideal distribution network configuration to fulfil the best scheduling goals. The ideal way of interconnecting switches between microgrids and the main grid was also identified. For each hour of operation, the ideal topology of microgrid-based distribution networks was determined using optimal power flow. The results were produced with and without the use of a demand response program and power-sharing in each microgrid. Different load profiles, such as residential, industrial, commercial, and academic, were taken into account and modified using appropriate demand response programs and power-sharing using the Artificial Bee Colony algorithm. Various scenarios were explored indep... [more]

The aim of this manuscript is to introduce solutions to optimize economic dispatch of loads and combined emissions (CEED) in thermal generators. We use metaheuristics, such as particle swarm optimization (PSO), ant lion optimization (ALO), dragonfly algorithm (DA), and differential evolution (DE), which are normally used for comparative simulations, and evaluation of CEED optimization, generated in MATLAB. For this study, we used a hybrid model composed of six (06) thermal units and thirteen (13) photovoltaic solar plants (PSP), considering emissions of contaminants into the air and the reduction in the total cost of combustibles. The implementation of a new method that identifies and turns off the least efficient thermal generators allows metaheuristic techniques to determine the value of the optimal power of the other generators, thereby reducing the level of pollutants in the atmosphere. The results are presented in comparative charts of the methods, where the power, emissions, and... [more]

This paper presents a novel methodology for planning and operating biogas energy systems based on the transactive energy concept to determine multilevel operating regimes for distributed generation. The developed model is used to manage the production, storage, and dispatch of biogas energy systems to meet the load demands of the biogas producer and support the operation of the distribution network operator. An Integer Linear Programming (ILP) is fitted to optimize the biogas production of the biogas producer, including the operation of the biogas storage systems and their interaction with the network operator. The model’s objective is to maximize benefits for the participating agents in a transactive energy context. The model’s effectiveness is validated using seven case studies involving biogas systems having different operating ranges and modes to achieve enhanced flexibility and reliability for the system operation with a large proportion of intermittent energy resources. The simul... [more]

Two methods for estimating the near-optimal positions and sizes of capacitors in radial distribution networks are presented. The first model assumes fixed-size capacitors, while the second model assumes controllable variable-size capacitors by changing the tap positions. In the second model, we limit the number of changes in capacitor size. In both approaches, the models consider many load scenarios and aim to obtain better voltage profiles by minimizing voltage deviations and active power losses. We use two recently developed heuristic algorithms called Salp Swarm Optimization algorithm (SSA) and Dragonfly algorithm (DA) to solve the proposed optimization models. We performed numerical simulations using data by modifying an actual distribution network in Almaty, Kazakhstan. To mimic various load scenarios, we start with the baseline load values and produce random variations. For the first model, the optimization algorithms identify the near-optimal positioning and sizes of fixed-size... [more]

Entropy generation is always a matter of concern in a heat transfer system. It denotes the amount of energy lost as a result of irreversibility. As a result, it must be reduced. The present work considers an investigation on the turbulent forced convective heat transfer and entropy generation of Al2O3-Ethylene glycol (EG) nanofluid inside a circular tube subjected to constant wall temperature. The study is focused on the development of an analytical framework by using mathematical models to simulate the characteristics of nanofluids in the as-mentioned thermal system. The simulated result is validated using published data. Further, Genetic algorithm (GA) and DIRECT algorithm are implemented to determine the optimal condition which yields minimum entropy generation. According to the findings, heat transfer increases at a direct proportion to the mass flow, Reynolds number (Re), and volume concentration of nanoparticles. Furthermore, as Re increases, particle concentration should be decr... [more]

This article presents the results of hydraulic tests performed for a prototype gear micropump of a new design. The development of modern hydraulic systems is following two directions: the integration of hydraulic and electronic engineering and a reduction in the mass and the dimensions of the system. The scope of this research involved identifying static characteristics of the prototype gear pump, i.e., its efficiency, torque and power. The tests were performed for PZ0 pumps with the following specific deliveries (which are their design parameters), 0.25 cm3/rev, 0.315 cm3/rev, 0.5 cm3/rev, 0.8 cm3/rev, and 1.0 cm3/rev—with two different types of hydraulic oils, Azolla ZS 22 and HL 68. The operating parameters included the rotational speed, the discharge pressure and the flow rate. The obtained research results suggest an application of the decision tree induction-based classification method for identifying the most important design and operating parameters and their values influencing... [more]

Because electricity retailers must ensure that energy supply matches end-user demand, electricity that is not traded through bilateral contracts is typically traded in power exchanges which are subject to great price volatility. In Colombia, the spot price is a reflection of climate variability because approximately 70% of the country’s electricity is generated by large hydropower stations. In this study, we forecast 2018′s prices and calculated its corresponding purchase margins using the 2015 to 2017 bilateral contract prices for electricity plus power exchange price information and climate information. Our forecasts included climate uncertainty and evaluated two multi-period portfolio methods for deciding among three purchasing strategies: bilateral contracts in the regulated market, bilateral contracts in the non-regulated markets, and purchases in the power exchange. The results indicate that retailers should follow a middle course that is neither conservative nor risky. Creation... [more]

Post-Optimum Sensitivity Analysis (POSA) extends numerical design optimization to provide additional information on how the design and performance would change if various parameters and constraints were varied. POSA is challenging since it typically requires accurate gradients and gradient-based optimization problems that provide Lagrange multipliers. To overcome this problem, this paper introduces a technique to automatically tune gradients with statistical methods and algorithms to calculate the Lagrange multipliers after an optimization. This allows these methods to be applied to problems with noisy gradients or problems solved with gradient-free optimization algorithms. These methods have been applied to swept wind turbine blades. Swept blades can reduce wind turbine loads by twisting out of the wind when the wind speed increases. The methods have shown that introducing design freedom in the sweep, blade root flap-wise bending moments and blade tip deflection has a weaker influence... [more]

Recent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A six phase squirrel cage induction motor is designed and simulated by ANSYS Motor-CAD. In order to find the best fit method, simulation results are compared and applied to the motors for electric propulsion, considering the influence of design upon the motor performance. The six-phase squirrel cage induction motor is more energy efficient, reliable and cost effective for the electric propulsion compared to the conventional three phase motor. In this study, first the initial parameters of the six phase squirrel cage induction motor have been determined and then these parameters have been compared wi... [more]

This article approaches the optimal solution of energy sustainability based on the use of artificial intelligence (AI). The application of renewable energy sources (RES) and unit commitment (UC) is the basic idea of this concept. Therefore, a new approach to solving the UC problem is introduced. The proposed method has a simple procedure to obtain the popular solutions in an acceptable time interval, by creating a basic model of the schedule of the state of energy units RES. It is obvious that individual consumer units, of an operational nature, take hourly performance values by performing economic evaluations on them in the sense of cost optimization. This is conducted through an artificial intelligence (AI) algorithm by optimizing the dedicated cost function, simulated by annealing. Despite the acceptable solution obtained from these two steps, another shift is proposed, called the TDD process in a given consumer area. This process in the application of AI in the system of selection... [more]

This paper presents a method for multi-period optimization of natural gas and electric power systems incorporating gas-fired power plants to analyze the impact of the interdependence between those commodities, in terms of cost and energy supply. The proposed method considers electricity network constraints, such as voltage profile, electrical losses, and limits of the transmission lines, as well as the technical restrictions on the gas network, such as the diameter, length, pressure, and limits for those variables. The proposed method was applied to a 12-bus electric network and a 7-node gas network, and several interdependencies between the electricity and the natural gas system network can be observed. The results show how the restrictions cause the behavior of the gas-fired power plants—in a low demand stage, it is restricted even when the gas-fired power generation prices are below the hydraulic generation prices, while in scenarios of higher demand, saturated cargo flows are obser... [more]

We propose the conditions for maximum overall efficiency at the constraint of satisfying asymmetric load power requirements for each receiver, for multiple-receivers wireless power transfer. Previously, the limitation of multiple-receiver analysis was that only the efficiency was maximized, whereas the requirements of load power were neglected. In many cases, conventional efficiency maximization assigns insufficient power to receivers far from the transmitter, while supplying excessive power to receivers near the transmitter. To resolve this limitation, we maximize the efficiency at the constraints of specified load power for each receiver. The proposed closed-form equation provides an optimum TX coil current amplitude, and the optimum load resistances of each receiver, to achieve the maximum efficiency at the load power regulation.