An improved mathematical model and an improved particle swarm optimization (IPSO) are proposed for the complex design parameters and conflicting design goals of the indoor luminaire layout (ILL) problem. The ILL problem is formulated as a nonlinear constrained mixed-variable optimization problem that has four decision variables. For a general lighting scheme (GLS), the number and location of luminaires can be uniquely determined by optimizing four decision variables, which avoid using program loops to determine the number of luminaires. We improve the particle swarm optimization (PSO) in three aspects: (1) up-down probabilistic rounding (UDPR) method proposed to solve mixed integer, (2) improving the velocity of the best global particle, and (3) using nonlinear inertia weights with random items. The IPSO has better optimization results in an office study compared with the PSO and genetic algorithm (GA). The results are validated by DIALux simulation software, and a maximum deviation of... [more]

Distributed generation is a vital component of the national economic sustainable development strategy and environmental protection, and also the inevitable way to optimize energy structure and promote energy diversification. The power generated by renewable energy is unstable, which easily causes voltage and frequency fluctuations and power quality problems. An adaptive online adjustment particle swarm optimization (AOA-PSO) algorithm for system optimization is proposed to solve the technical issues of large-scale wind and light abandonment. Firstly, a linear adjustment factor is introduced into the particle swarm optimization (PSO) algorithm to adaptively adjust the search range of the maximum power point voltage when the environment changes. In addition, the maximum power point tracking method of the photovoltaic generator set with direct duty cycle control is put forward based on the basic PSO algorithm. Secondly, the concept of recognition is introduced. The particles with strong r... [more]

The importance of power in society is indisputable. Virtually all economic activities depend on electricity. The electric power systems are complex, and move studies in different areas are motivated to make them more efficient and solve their operational problems. The smart grids emerged from this approach and aimed to improve the current systems and integrate electric power using alternative and renewable sources. Restoration techniques of these networks are being developed to reduce the impacts caused by the usual power supply interruptions due to failures in the distribution networks. This paper presents the development and evaluation of the performance of a multi-objective version of the Bacterial Foraging Optimization Algorithm for finding the minor handling switches that maximize the number of buses served, keeping the configuration radial system and within the limits of current in the conductors and bus voltage. An electrical system model was created, and routines were implement... [more]

Many electric vehicles (EVs) are using today’s distribution grids, and their flexibility can be highly beneficial for the grid operators. This flexibility can be best exploited by DC power networks, as they allow charging and discharging without extra power electronics and transformation losses. From the grid control perspective, algorithms for planning EV charging are necessary. This paper studies the problem of EV charging planning under limited grid capacity and extends it to the partially observable case. We demonstrate how limited information about the EV locations in a grid may disrupt the operation planning in DC grids with tight constraints. We introduce two methods to change the grid topology such that partial observability of the EV locations is resolved. The suggested models are evaluated on the IEEE 16 bus system and multiple randomly generated grids with varying capacities. The experiments show that these methods efficiently solve the partially observable EV charging plann... [more]

The green innovations in the energy sector are smart solutions to meet the excessive power requirements through renewable energy resources (RERs). These resources have forwarded the revolutionary relief in control of carbon dioxide gaseous emissions from traditional energy resources. The use of RERs in a heuristic manner is necessary to meet the demand side management in microgrids (MGs). The pricing scheme limitations hinder the profit maximization of MG and their customers. In addition, recent pricing schemes lack mechanistic underpinning. Therefore, a dynamic electricity pricing scheme through linear regression is designed for RERs to maximize the profit of load customers (changeable and unchangeable) in MG. The demand response optimization problem is solved through the particle swarm optimization (PSO) technique. The proposed dynamic electricity pricing scheme is evaluated under two different scenarios. The simulation results verified that the proposed dynamic electricity pricing s... [more]

The charging loads of electric vehicles (EVs) at residential premises are controlled through a tariff system based on fixed timing. The conventional tariff system presents the herding issue, such as with many connected EVs, all of them are directed to charge during the same off-peak period, which results in overloading the power grid and high charging costs. Besides, the random nature of EV users restricts them from following fixed charging times. Consequently, the real-time pricing scenarios are natural and can support optimizing the charging load and cost for EV users. This paper aims to develop charging cost optimization algorithm (CCOA) for residential charging of EVs. The proposed CCOA coordinates the charging of EVs by heuristically learning the real-time price pattern and the EV’s information, such as the battery size, current state-of-charge, and arrival & departure times. In contrast to the holistic price, the CCOA determines a threshold price value for each arrival and depart... [more]

Commercial virtual power plants (CVPP) connect the form of renewable energy resource portfolio to the power market and reduce the risk of the unstable operation of a single renewable energy. Combining different kinds of large-scale renewable energy in CVPP to provide capacity services like base load, peak shaving, and valley-filling, etc., for the system loads is an urgent problem to be solved. Therefore, it is valuable to analyze the capacity allocation ratio of the CVPP to maximize the utilization of all kinds of energy, especially for the large-scale multi-energy base. This paper proposed a multi-energy coordinated operation framework by considering various load demands, including base load and peak shaving for the capacity allocation of CVPP based on the world’s largest renewable energy resource base on the upstream area of the Yellow River. The main procedures of this framework are as follows: (1) A paratactic model satisfying base load and peak shaving is proposed to determine th... [more]

Optimizing the schedule of thermal generators is probably the most important task when the operation of power systems is managed. This issue is known as the unit commitment problem in operational research. It has been profoundly studied in the literature, where several techniques have been proposed to address a computationally tractable solution. In turn, the ongoing changes of paradigms in energy markets focus the attention on the unit commitment problem as a powerful tool to handle new trends, such as the high renewable energy sources penetration or widespread use of non-conventional energy-storage technologies. A review on the unit commitment problem is propo- sed in this paper. The easy understanding of the diverse techniques applied in the literature for new researchers is the main goal of this state-of-art as well as identifying the research gaps that could be susceptible to further developments. Moreover, an overview of the evolution of the Mixed Integer Linear Programming formu... [more]

The optimization of overcurrent relays’ operation is a topic associated with protection coordination of distribution networks. Usually, this refers to medium-voltage networks, since they are protected by numerical relay devices, as opposed to low-voltage networks, where utility operators allocate fuses. Correct setting of relays and optimal coordination is becoming a serious challenge to Distribution Network Operators around the world, since their networks’ passive operation has been greatly altered in the past two decades. Distributed generation units, a growing liberalized electricity market and more stringent legislation for distribution network planning and operation by state regulatory bodies have all indirectly affected the evolving of protection philosophy for distribution networks. In this paper the traditional optimization problem of overcurrent relay operation will be addressed and critically examined from both a theoretical and practical point of view. Optimization function,... [more]

Hydraulic fracturing can be utilized to extract trapped hydrocarbon where integrated fracture networks do not exist for sufficient production. In this work, design parameters of a hydraulic acid fracturing of a tight carbonate reservoir in the Middle East were optimized. The effect of optimized hydraulic fracturing on production performance and rate was investigated. Using the petrophysical well logs, formation integrity tests, core data the Mechanical Earth Model (MEM) of the tight carbonate reservoir was created, which resulted in rock mechanical properties and in-situ stresses. The other required parameters for fracturing design were either measured or found from empirical correlations. Following a candidate selection of suitable layers for fracturing, the input parameters were loaded in GOHFER software to design and optimize the fracturing job. Finally, the production forecast was performed and compared with current conditions. The injection parameters (flow rate, total volume, and... [more]

The deflection magnet (DM) is the most important component of the Neutral Beam Injection (NBI) system of Experimental Advanced Superconducting Tokamak (EAST), which can magnetically deflect the un-neutralized charged particles after the neutralized process of the beam is extracted from the ion source, and then form a neutral beam injected into the tokamak. Under the operating conditions of the NBI system, by using the thermocouple monitoring system in the experiment, it can be found that the currently operating DM beam collimator has a quite high temperature rise. It is necessary to redesign the DM beam collimator to improve its heat transfer performance. The parallel arrangement of multiple rows of tubes is proposed as the basic method for the redesign of the beam collimator of DM, the thermal-fluid-structure analysis model of this redesign model is established and its temperature field, pressure field and stress field are analyzed. Taking the surface temperature of the beam collimato... [more]

The inconsistent irradiance, temperature, and unexpected behavior of the weather affect the output of photovoltaic (PV) systems, classified as partial or complex partial shading conditions. Under these circumstances, obtaining the maximum output power from PV systems becomes problematic. This paper proposes a population-based optimization model, the horse herd optimization algorithm (HOA), inspired by natural behavior, to solicit the maximum power under partial or complex partial shading conditions. It is an intelligent strategy inspired by the surprise pounce-chasing style of the horse herd model. The proposed technique outperforms the standard in different weather conditions, needs less computational time, and has a fast convergence speed and zero oscillations after reaching a power point’s maximum limit. A performance comparison of the HOA is achieved with conventional techniques, such as “perturb and observe” (P&O), the bio-inspired adaptive cuckoo search optimization (ACS), partic... [more]

The Polish economy is facing a huge challenge regarding the future of energy in Poland. The current energy system is very inefficient, it consumes huge resources that, like countries with high energy efficiency, could be allocated to the development of low-carbon and renewable energy networks. At the moment, the Polish energy sector, related to the coal monoculture, lacks electricity and the entire transmission system is obsolete. The solution may be distributed energy, which can ultimately satisfy energy supplies in less urbanized areas and in rural areas, while guaranteeing the sustainable development of these areas. In order to take up the challenge of better understanding and explaining such a complex reality, it was decided that the research framework of this article will be distributed energy in the region. The aim of the article is to ensure energy security in the conditions of innovative, ecological and open to competition regional energy using local energy resources. Currently... [more]

This study applies the Physical Optimum (PhO) as a reference value to rate the efficiency of two technical options for the oxygen supply of a hospital. The systematic comparison of the alternative processes using the PhO as a benchmark for the minimum input (exergy in this case) required to run a process with a certain benefit allows to determine the potential for optimization of each technology. Differences are analyzed by visualizing the losses of each individual production step in a process as well as by the resulting overall energy demand, including the primary energy. Possible alternatives are purchasing liquid oxygen from a cryogenic process or the production by means of Pressure Swing Adsorption (PSA) on site. The cryogenic production shows a lower exergy demand even though it also has a higher potential for optimization. Yet, the total losses, significantly impacted by the unavoidable transportation, sum up, resulting in the conclusion that the PSA is the preferable option over... [more]

With the increasing penetration of wind power, the uncertainty associated with it brings more challenges to the operation of the integrated energy system (IES), especially the power subsystem. However, the typical strategies to deal with wind power uncertainty have poor performance in balancing economy and robustness. Therefore, this paper proposes a distributionally robust joint chance-constrained dispatch (DR-JCCD) model to coordinate the economy and robustness of the IES with uncertain wind power. The optimization dispatch model is formulated as a two-stage problem to minimize both the day-ahead and the real-time operation costs. Moreover, the ambiguity set is generated using Wasserstein distance, and the joint chance constraints are used to ensure that the safety constraints (e.g., ramping limit and transmission limit) can be satisfied jointly under the worst-case probability distribution of wind power. The model is remodeled as a mixed-integer tractable programming issue, which ca... [more]

In this work, a novel agent-based day-ahead power management scheme is proposed for multiple-microgrid distribution systems with the intent of reducing operational costs and improving system resilience. The proposed power sharing algorithm executes within each microgrid (MG) locally, and the neighboring MGs cooperate via a multi-agent system cooperation scheme, established to model the communication among the agents. The power management for each agent is modeled as a multi-objective optimization problem (MOP) including two objectives: maximizing load coverage and minimizing the operating costs. The proposed MOP is solved using the Nondominated Sorting Genetic Algorithm (NSGA-II), where a set of Pareto optimal solutions is obtained for each agent through the NSGA-II. The final solution is obtained using an Analytical Hierarchical Process. The effectiveness of the proposed scheme is evaluated using a benchmark 4-MG distribution system. It is shown that the proposed power management sche... [more]

In this paper, the 12-slot/4-pole (12/4) synchronous reluctance motor (SynRM) with concentrated windings is proposed for low-cost hybrid vehicles. The non-linear magnetic equivalent circuit (MEC) model of the 12/4 SynRM is built to obtain the main electromagnetic characteristics such as coil flux, inductances, torque, etc. The magnetic saturation is also counted in by the MEC. Results calculated by MEC are validated by 2D finite element analysis (FEA). Then, aiming at larger average torque, lower torque ripple and lower total harmonic distortion (THD) in phase voltage, the parameter optimization method of the SynRM is proposed based on the Taguchi method and the MEC model. The proposed Taguchi-MEC method enables a fast optimization with satisfactory accuracy. Finally, the motor prototype is manufactured, and experimental validations are carried out.

In order to explore the axial electromagnetic dynamic balance force curve of a scroll compressor under the action of thermal energy, radial clearance, mechanism friction, and other factors in actual working conditions, an axial force exploration method that can automatically approach sections is proposed in this paper. Considering the dynamic response ability of the electromagnetic balance system, an automatic optimization algorithm of the partition number was proposed to find the optimal partition number in order to achieve the optimal tracking effect. An experimental platform was built to test the effect of the segmented tracking method on calibrating the deviation between the theoretical axial force curve and the real curve. The results show that the curve construction method proposed in this paper has convergence. This method can automatically and accurately construct the axial balance force curve required by the electromagnetic dynamic balance. Through the automatic optimization a... [more]

This research presents a novel optimization strategy for concentrating solar power (CSP) plants with thermal energy storage (TES) systems that aims to stabilize and reduce electricity prices in spot markets. In the current international scenario of initiatives with regulatory changes aiming to reduce climate change effects and therefore CO2 emissions, many countries are reducing the fossil fuel share in their respective electrical systems and increasing electrical renewable energy systems. These carbon free generation systems have inherent problems such as their intermittence which, combined with the lack of high-scale energy storage systems, cause a stability risk in electrical grid systems and require conventional fuel systems to match demand and production. In this research, we analyze spot price markets using a marginal price system that relies on natural gas and is quite sensitive to an increase in fuel prices, causing a direct increase in the final energy cost in systems with a h... [more]

In order to solve the problems of the large volume and high cost of a six-pole hybrid magnetic bearing (SHMB) with displacement sensors, a displacement estimation method using a modified particle swarm optimization (MPSO) least-squares support vector machine (LS-SVM) is proposed. Firstly, the inertial weight of the MPSO is changed to achieve faster iterations, and the prediction model of an LS-SVM-based MPSO is built. Secondly, the prediction model is simulated and verified according to the parameters optimized by the MPSO, and the predicted values of MPSO and PSO are compared. Finally, static and dynamic suspension experiments and a disturbance experiment are carried out, which verify the robustness and stability of the displacement estimation method.

Energy disaggregation (ED), with minimal infrastructure, can create energy awareness and thus promote energy efficiency by providing appliance-level consumption information. However, ED is highly ill-posed and gets complicated with increase in number and type of devices, similarity between devices, measurement errors, etc. To design, test, and benchmark ED algorithms, the availability of open-access energy consumption datasets is crucial. Most datasets in the literature suit data-intensive pattern-based ED algorithms. Recently, optimization-based ED algorithms that only require information regarding the operational states of the devices are being developed. However, the lack of standard datasets and appropriate evaluation metrics is hindering the development of reproducible state-of-the-art optimization-based ED algorithms. Therefore, in this paper, we propose a dataset with multiple instances that are representative of the different challenges posed by ED in practice. Performance indi... [more]

The state of health and remaining useful life of lithium-ion batteries are key indicators for the normal operation of electrical devices. To address the problem of the capacity of lithium-ion batteries being difficult to measure online, in this paper, we propose an online method based on particle swarm optimization and support vector regression to estimation the state of health and remaining useful life. First, a novel health indicator is extracted from the discharge voltage to characterize the capacity of lithium-ion batteries. Then, based on the capacity degradation characteristics, support vector regression is used to predict the remaining useful life of these batteries, and particle swarm optimization is selected to optimize the parameters of the support vector regression, which effectively enhances the predictive performance of the model. Validated for the NASA battery aging dataset, when training with the first 40% of the dataset, the maximum error of the predicted remaining usef... [more]

To ensure effective heat recovery of thermoelectric generators, a cooling system is necessary to maintain the working temperature difference of the thermoelectric couples, which decreases continuously due to thermal diffusion. In order to evaluate and improve the thermoelectric performance of a concentric annular thermoelectric generator under various cooling methods, a comprehensive numerical model of the thermo-fluid-electric multi-physics field for an annular thermoelectric generator with a concentric annular heat exchanger was developed using the finite-element method. The effects of four cooling methods and different exhaust parameters on the thermoelectric performance were investigated. The results show that, in comparison to the cocurrent cooling pattern, the countercurrent cooling pattern effectively reduces temperature distribution non-uniformity and hence increases the maximum output power; however, it requires more thermoelectric semiconductor materials. Furthermore, when us... [more]

Engineering optimization is the subject of interest for many scientific research teams on a global scale; it is a part of today’s mathematical modelling and control of processes and systems. The attention in this article is focused on optimization modelling of technological processes of surface treatment. To date, a multitude of articles are devoted to the applications of mathematical optimization methods to control technological processes, but the situation is different for surface treatment processes, especially for anodizing. We perceive their lack more, so this state has stimulated our interest, and the article contributes to filling the gap in scientific research in this area. The article deals with the application of non-linear programming (NLP) methods to optimise the process of anodic oxidation of aluminium using MATLAB toolboxes. The implementation of optimization methods is illustrated by solving a specific problem from engineering practice. The novelty of this article lies i... [more]

Facing the challenges of grid stability brought by the large-scale access of new energy to the grid, as one of the important means of frequency regulation of the grid, the doubly-fed pumped-storage units (DFPSU) have great practical significance in the study of the joint frequency regulation strategy with the thermal power unit (TPU). In order to reduce the frequency regulation pressure on the grid caused by the large-scale entry of new energy sources, this paper proposes a joint frequency regulation strategy for the TPU and DFPSU. Based on establishing the optimal scheduling model of the system, taking into account the minimum total operating cost and the optimal time as goals, the chaotic particle swarm optimization (CPSO) is proposed to solve the model. Finally, through MATLAB simulation, the relevant examples are studied and analyzed, and the simulation results verify that the joint frequency regulation strategy in this paper can effectively improve the frequency regulation perform... [more]