A tritium breeding blanket (TBB) is an essential component in a fusion reactor, which has functions of tritium breeding, energy generation and neutron shielding. Tritium breeding ratio (TBR) is a key parameter to evaluate whether the TBB could produce enough tritium to achieve tritium self-sufficiency (TBR > 1) for a fusion reactor. Current codes or software struggle to meet the requirements of high efficiency and high automation for neutronic optimization of the TBB. In this paper, the multiphysics coupling and automatic neutronic optimization method study for a solid breeder TBB is performed, and a corresponding code is developed. A typical module of China fusion engineering test reactor (CFETR) helium cooled ceramic breeder (HCCB) TBB was selected, and a 3D neutronics model of an initial scheme is developed. The automatic neutronic optimization was performed by using the developed code for verification. Results indicate that the TBR could increase from 1.219 to 1.282 (~5.17% improve... [more]

The high and growing share of renewable sources and the more important role of Distributed Energy Resources (DERs) in the Distribution System (DS) is leading to a need for more efficient coordination of those sources. In future power systems, TSO−DSO coordination will play a key role in providing flexibility services. Lack of proper coordination of sources may lead to congestion in the network or to a lack of possibility to generate or consume energy on a requested level. The crucial aspect is that the TSO−DSO coordination must be based on an active role of all participants: TSO, DSO, generation units and the demand. This paper presents the possible application of the TSO−DSO coordination by providing the flexibility services from DS to the Transmission System (TS). The paper presents the complex optimization of TS, DS and its coordination. The main goal of the paper is to show the possibility of the application of the flexibility market into the current system design. It requires the... [more]

A theoretical−experimental annual analysis of a hybrid industrial direct−indirect solar air heating system performance for drying was conducted considering temperatures, useful energy Qu, efficiency η, and solar fraction SF. The direct solar air heating system located in Morelos, México, has flat-plate solar air collectors, and the indirect system has flat-plate solar water collectors, a thermal storage tank, a cross-flow fin, and a tube heat exchanger. A validated TRNSYS program modeled the process; the validation was carried out by comparing each component outlet temperature and useful energy with the respective experimental field data. The analysis considered annual usage over seven days a week, nine hours a day (from 09:00 to 18:00 h), and three operation modes. For the direct, indirect, and hybrid operation modes, the Qu values were 31.60, 55.19, and 75.18 MWh/yr; the annual η values were 0.44, 0.41, and 0.42; and the annual SF values were 0.45, and 0.73 for the indirect and hybri... [more]

Load flow analysis is an essential tool for the reliable planning and operation of interconnected power systems. The constant increase in power demand, apart from the increased intermittency in power generation due to renewable energy sources without proportionate augmentation in transmission system infrastructure, has driven the power systems to function nearer to their limits. Though the power flow (PF) solution may exist in such circumstances, the traditional Newton−Raphson based PF techniques may fail due to computational difficulties owing to the singularity of the Jacobian Matrix during critical conditions and faces difficulties in solving ill-conditioned systems. To address these problems and to assess the impact of large-scale photovoltaic generator (PVG) integration in power systems on power flow studies, a derivative-free quasi-oppositional heap-based optimization (HBO) (QOHBO) technique is proposed in the present paper. In the proposed approach, the concept of quasi-oppositi... [more]

Nowadays, many organizations and individual users are employing cloud services extensively due to their efficiency, reliability and low cost. A key aspect for cloud data centers is to achieve management methods to reduce energy consumption, increasing the profit and reducing the environmental impact, which is critical in the deployment of leading-edge technologies today such as blockchain and digital finances, IoT, online gaming and video streaming. In this review, various clustering, optimization, and machine learning methods used in cloud resource allocation to increase the energy efficiency and performance are analyzed, compared and classified. Specifically, on the one hand, we discuss how clustering methods and optimization techniques are widely applied in energy management due to their capacity to provide solutions for energy consumption reduction. On the other hand, we study how multi-objective optimization methods focus on reducing energy consumption as well as service level agr... [more]

At present, magnetically coupled resonance wireless power transfer (MCRWPT) is the main technology used in electric vehicle wireless power transfer (WPT) due to its advantages of high transmission power and high efficiency. The resonant compensation circuit of the system generally adopts the double LCC (DLCC) structure, which has many capacitor and inductor components. Therefore, it is necessary to optimize the circuit parameters to improve the transmission performance of the system. In this study, the DLCC compensation circuit was modeled and analyzed to lay the foundation for parameter optimization. Secondly, the size parameters of the energy transmitting and receiving coil were determined, and the influence of the change of the primary and secondary compensation inductance on the circuit element stress and output performance was analyzed to determine the optimal compensation inductance value. Thirdly, the realization condition of zero voltage switching (ZVS) was analyzed, the relati... [more]

Energy Internet is a complex nonlinear system. There are many stakeholders in the load trading market, which is usually regarded as a multi-player gaming. Although gaming theory has been introduced to solve Multivariate Load trading problems, different conditions should be considered to accurately optimize the multivariate load trading problem. For example, the selling side needs to reduce the reserve capacity and improve profits, but the consumer side needs to reduce costs and minimize the impact on its own electricity consumption. These contradictory conditions require multiple Nash equilibrium to achieve obviously. To address this issue, a unified architecture of the power system cloud trading is constructed in this paper, which is combined with the multiple load classification of the power system. In addition, according to the power market operation mechanism, a price-guided multivariate load trading game strategy is designed. More importantly, a multivariate load trading optimizat... [more]

In the last decade, logistic systems based on small aerial vehicles (drones) have become attractive for urban delivery operations as a sustainable alternative to ground vehicles because they are not affected by the congestion of the road network, thus allowing for faster and more reliable services. Aerial logistic systems, however, require a substantially different approach to operations management and need specifically designed supportive infrastructures. While the research on urban aerial delivery mostly focuses on the optimization vehicle operations, the appropriate design of supportive infrastructures is seldom considered. This paper focuses on the energy efficiency of aerial logistic systems, and proposes a new original methodology to obtain a realistic estimate of the overall energy consumed by a swarm of drones employed for urban delivery, taking into account the extension of the area served and its specific features. The methodology proposed offers relevant information for the... [more]

Electric vehicles (EVs) have a lot of potential to play an essential role in the smart power grid. EVs not only can reduce the amount of emission yielded from fossil fuels but also can be considered as an energy storage system (ES) and a backup system. EVs could support the demand response (DR) strategy that is considered as utmost importance to shift electricity demand in peak hours. This article aims to assess the impact of the presence of EV on DR strategy in a home-microgrid (H-MG). In order to reach the optimal set point, our energy management system (EMS) has been merged with differential evolution (DE) method. The results were auspicious and showed that the proposed method could decrease market clearing price (MCP) by 26% and increase the performance of DR by 17%.

Deterministic forecasting models have been used through the years to provide accurate predictive outputs in order to efficiently integrate wind power into power systems. However, such models do not provide information on the uncertainty of the prediction. Probabilistic models have been developed in order to present a wider image of a predictive outcome. This paper proposes the lower upper bound estimation (LUBE) method to directly construct the lower and upper bound of prediction intervals (PIs) via training an artificial neural network (ANN) with two outputs. To evaluate the PIs, the minimization of a coverage width criterion (CWC) cost function is proposed. A particle swarm optimization (PSO) algorithm along with a mutation operator is further implemented, in order to optimize the weights and biases of the neurons of the ANN. Furthermore, wavelet transform (WT) is adopted to decompose the input wind power data, in order to simplify the pre-processing of the data and improve the accur... [more]

Hybrid electric aero-propulsion requires high power-density electric motors. The use of a constrained optimization method with the finite element analysis (FEA) is the best way to design these motors and to find the best solutions which maximize the power density. This makes it possible to take into account all the details of the geometry as well as the non-linear characteristics of magnetic materials, the conductive material and the current control strategy. Simulations were performed with a time stepping magnetodynamic solver while taking account the rotor movement and the stator winding was connected by an external electrical circuit. This study describes the magnetic FEA direct optimization approach for the design of Halbach array permanent magnet synchronous motors (PMSMs) and its advantages. An acceptable compromise between precision and computation time to estimate the electromagnetic torque, iron losses and eddy current losses was found. The finite element simulation was paired... [more]

Connected communities potentially offer much greater demand response capabilities over singular building energy management systems (BEMS) through an increase of connectivity. The potential increase in benefits from this next step in connectivity is still under investigation, especially when applied to existing buildings. This work utilizes EnergyPlus simulation results on eight different commercial prototype buildings to estimate the potential savings on peak demand and energy costs using a mixed-integer linear programming model. This model is used in two cases: a fully connected community and eight separate buildings with BEMS. The connected community is optimized using all zones as variables, while the individual buildings are optimized separately and then aggregated. These optimization problems are run for a range of individual zone flexibility values. The results indicate that a connected community offered 60.0% and 24.8% more peak demand savings for low and high flexibility scenar... [more]

This paper presents the analysis of the main reasons for a significant decrease in the intensity of diffusion processes during the formation of gas hydrates; solutions to this problem are proposed in a new process flow diagram for the continuous synthesis of gas hydrates. The physical processes, occurring at the corresponding stages of the process flow, have been described in detail. In the proposed device, gas hydrate is formed at the boundary of gas bubbles immersed in cooled water. The dynamic effects arising at the bubble boundary contribute to the destruction of a forming gas hydrate structure, making it possible to renew the contact surface and ensure efficient heat removal from the reaction zone. The article proposes an assessment technique for the main process parameters in the synthesis of hydrates based on the criterion of thermodynamic parameters optimization. The optimization criterion determines the relationship of intensity of heat and mass transfer processes at the phase... [more]

Pipe height in cylindrical neutron moderator is an important factor to flow pattern, temperature distribution and even the neutron characters. In this paper, the steady-state thermal analysis of cold neutron moderator is carrying out with different heights, conjugated heat transfer method and one-way coupled with a neutron transfer software. The different pipe heights, which is the jet-to-surface distances (H/D = 0.5~6), were compared using a 2D moderator model. The results show that vortex size and velocity gradient from container wall to vortex center vary with H/D, the center of recirculation zone nearly remain constant, and heat transfer effect is weakened on the target bottom surface. With H/D increasing, the velocity at bottom target surface is progressively decreased, and cooling effect is poor, leading to the rise in temperature. The optimal range cooling performance is (H/D) = 0.5~1 at Re = 1.7 × 105, and the enhancement of beam power further strengthens the thermal deposition... [more]

This study aimed to examine the energy and exergy indices of the rosemary drying process in a hybrid-solar dryer (HSD) and the effects of air-drying parameters on these thermodynamic indices. Drying experiments were carried out at four levels of air temperature (40, 50, 60, and 70 ∘C) and three levels of air velocity (1, 1.5, and 2 m/s). Energy and exergy were calculated by application of the first and second laws of thermodynamics. Based on the principal laws, energy efficiency, exergy losses, and exergetic improvement potential rate, were evaluated. The results showed that the energy utilization ratio (EUR) ranged from 0.246 to 0.502, and energy utilization (EU) ranged from 0.017 to 0.060 (kJ/s). Exergy loss and efficiency varied from 0.009 to 0.028 (kJ/s) and from 35.08% to 78.5%, respectively, and increased with increased temperature and air velocity. It was found that the exergy loss rate was affected by temperature and air velocity because the overall heat transfer coefficient wa... [more]

An intelligent control strategy is proposed in this paper which suggests the Optimum Power Quality Enhancement (OPQE) of grid-connected hybrid power systems with solar photovoltaic, wind turbines, and battery storage. Unified Power Quality Conditioner with Active and Reactive power (UPQC-PQ) is designed with Atom Search Optimization (ASO) based Fractional-order Proportional Integral Derivative (FOPID) controller in the proposed Hybrid Renewable Energy Sources (HRES) system. The main aim is to regulate voltage while reducing power loss and reducing Total Harmonic Distortion (THD). UPQC-PQ is used to mitigate the Power Quality (PQ) problems such as sag, swell, interruptions, real power, reactive power and THD reductions related to voltage/current by using ASO based FOPID controller. The developed technique is demonstrated in various modes: simultaneous to improve PQ reinforcement and RES power injection, PRES > 0, PRES = 0. The results are then compared to those obtained using previous l... [more]

The integration of the European markets has started with the successful coupling of spot markets (day-ahead and intra-day) and is expected to continue with the coupling of balancing markets. In this paper, the optimization model for the activation of manual frequency restoration reserve (mFRR) is presented. The model incorporates all order types agreed among the European transmission system operators (TSOs) to be included in the Manually Activated Reserves Initiative (MARI) project. Additionally, the model incorporates the buying curve (demand) of mFRR with the possible tolerance band defined by the TSOs, order clearing constraints and the cross-zonal capacity (CZC) constraints, forming a mixed integer linear programming model. The methodology employs two distinct steps: In the first step, an order conversion process is employed for the markets applying the central-scheduling scheme, and in the second step, the mFRR activation process is executed by solving the presented model. The who... [more]

With the increasing penetration of intermittent renewable energy generation, there is a growing demand to use the inherent flexibility within buildings to absorb renewable related disruptions. Heat pumps play a particularly important role, as they account for a high share of electricity consumption in residential units. The most common way of quantifying the flexibility is by considering the response of the building or the household appliances to external penalty signals. However, this approach neither accounts for the use cases of flexibility trading nor considers its impact on the prosumer comfort, when the heat pump should cover the stochastic domestic hot water (DHW) consumption. Therefore, in this paper, a new approach to quantifying the flexibility potential of residential heat pumps is proposed. This methodology enables the prosumers themselves to generate and submit the operating plan of the heat pump to the system operator and trade the alternative operating plans of the heat... [more]

This paper used different risk management indicators applied to the investment optimization performed by consumers in Distributed Generation (DG). The objective function is the total cost incurred by the consumer including the energy and capacity payments, the savings, and the revenues from the installation of DG, alongside the operation and maintenance (O&M) and investment costs. Probability density function (PDF) was used to model the price volatility in the long-term. The mathematical model uses a two-stage stochastic approach: investment and operational stages. The investment decisions are included in the first stage and which do not change with the scenarios of the uncertainty. The operation variables are in the second stage and, therefore, take different values with every realization. Three risk indicators were used to assess the uncertainty risk: Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and Expected Value (EV). The results showed the importance of migration from de... [more]

An emerging topic is electrical discharge (ED) coating with its application on complex shapes and cavities to repair components or act as functional coatings. Because it is a variant process of an electric discharge machine (EDM) with the ability to coat on electrically conductive substrates, there is a possibility that next-generation electrical discharge machining components may exploit the attachment phenomenon to enhance recast layer properties. Previously, researchers have obtained ED coating by mixing the powder in a dielectric medium and/or by using powder metallurgy electrodes. In this work, primarily, an insight in the formation of ED coating on-die sinks electrical discharge machine, using conventional electrode materials viz., bronze on titanium alloy (Ti-6Al-4V) is made. The bronze electrode on the titanium substrate obtained a crack-free copper coating of ~20 microns thickness. In order to perform the experiments, three combinations were made using five parameters: current... [more]

Under-frequency load shedding (UFLS) prevents a power grid from a blackout when a severe contingency occurs. UFLS schemes can be classified into two categories—event-based and response-driven. A response-driven scheme utilizes 81L relays with pre-determined settings while an event-based scheme develops a pre-specified look-up table. In this work, an event-based UFLS scheme is presented for use in an offshore standalone power grid with renewables to avoid cascading outages due to low frequency protection of wind power generators and photovoltaic arrays. Possible “N-1” and “N-2” forced outages for peak and off-peak load scenarios in summer and winter are investigated. For each forced outage event, the total shed load is minimized and the frequency nadir is maximized using particle swarm optimization (PSO). In order to reduce the computation time, initialization and parallel computing are implemented using MATLAB/Simulink because all forced outage events and all particles in PSO are mutua... [more]

With the increasing penetration of renewable energy generation, one of the major challenges is the problem of how to express the stochastic process of wind power and photovoltaic output as the exact probability density and distribution, in order to improve the security and accuracy of unit commitment results, a distributed robust security-constrained optimization model based on moment uncertainty is proposed, in which the uncertainty of wind and photovoltaic power is captured by two uncertain sets of first- and second-order moments, respectively. The two sets contain the probability distribution of the forecast error of the wind and photovoltaic power, and in the model, the energy storage is considered. In order to solve the model effectively, firstly, based on the traditional chance-constrained second-order cone transformation, according to the first- and second-order moments polyhedron expression of the distribution set, a cutting plane method is proposed to solve the distributed rob... [more]

In this article, the authors present methods based on hard coal that may ensure energy security for European Union countries. The research was carried out based on the example of Poland. The main reason for which coal is being gradually withdrawn from the energy mixes in EU countries is its negative impact on the natural environment and the health of citizens and economic factors related to domestic fuel production. The authors propose the creation of energy−chemical clusters as a solution to these problems. It is assumed that the clusters would operate following the principles of the circular economy. We also propose methods for the optimization of the production and transport costs within the cluster. Then, we conduct profitability analysis of the proposed waste management methods. At the level of the designated cluster, using network algorithms enabled us to reduce the transport costs by at least 50%. It is possible to obtain rare earth elements (REEs) worth USD 22,970 from 1 Mg of... [more]

The relay coordination problem is of dire importance as it is critical to isolate the faulty portion in a timely way and thus ensure electrical network security and reliability. Meanwhile a relay protection optimization problem is highly constraint and complicated problem to be addressed. To fulfill this purpose, Harris Hawk Optimization (HHO) is adapted to solve the optimization problem for Directional Over-current Relays (DOCRs) and numerical relays. As it is inspired by the intelligent and collegial chasing and preying behavior of hawks for capturing the prey, it shows quite an impressive result for finding the global optimum values. Two decision variables; Time Dial Settings (TDS) and Plug Settings (PS) are chosen as the decision variables for minimization of overall operating time of relays. The proposed algorithm is implemented on three IEEE test systems. In comparison to other state-of-the-art nature inspired and traditional algorithms, the results demonstrate the superiority of... [more]

Recent developments in electrical power systems are concerned not only with static power flow control but also with their control during dynamic processes. Smart Grids came into being when it was noticed that the traditional electrical power system structure was lacking in reliability, power flow control, and consistency in the monitoring of phasor quantities. The Phasor Measurement Unit (PMU) is one of the main critical factors for Smart Grid (SG) operation. It has the ability to provide real-time synchronized measurement of phasor quantities with the help of a Global Positioning System (GPS). However, when considering the installation costs of a PMU device, it is far too expensive to equip on every busbar in all grid stations. Therefore, this paper proposes a new approach for the Optimum Placement of the PMU problem (OPP problem) to minimize the installed number of PMUs and maximize the measurement redundancy of the network. Exclusion of the unwanted nodes technique is used in the pr... [more]