Micro-grids’ operations offer local reliability; in the event of faults or low voltage/frequency events on the utility side, micro-grids can disconnect from the main grid and operate autonomously while providing a continued supply of power to local customers. With the ever-increasing penetration of renewable generation, however, operations of micro-grids become increasingly complicated because of the associated fluctuations of voltages. As a result, transformer taps are adjusted frequently, thereby leading to fast degradation of expensive tap-changer transformers. In the islanding mode, the difficulties also come from the drop in voltage and frequency upon disconnecting from the main grid. To appropriately model the above, non-linear AC power flow constraints are necessary. Computationally, the discrete nature of tap-changer operations and the stochasticity caused by renewables add two layers of difficulty on top of a complicated AC-OPF problem. To resolve the above computational diffi... [more]

Using cascade utilization between multiple energy sources to realize multi-energy complementarity can significantly improve the economic benefits and energy utilization of integrated energy service providers. Integrated energy service providers consider the cascade utilization of energy in the regional energy system. Through the demand response management of user power loads and different qualities of heat energy, the energy loss of the system can be reduced and the energy utilization efficiency of the system can be further improved. In this paper, we creatively establish a multi-objective optimization model with the goal of a minimum total cost and minimum exergy loss, considering cross elasticity, which is solved with the constraints of equipment operation and the energy balance in the region. The calculation example proves that the implementation of energy cascade utilization and demand response management for different users, by integrated energy service providers, can effectively... [more]

In this paper, driving strategy optimization for a track is proposed for an energy efficient battery electric vehicle dedicated to the Shell Eco-marathon. A measurement-based mathematical vehicle model was developed to simulate the behavior of the vehicle. The model contains complicated elements such as the vehicle’s cornering resistance and the efficiency field of the entire powertrain. The validation of the model was presented by using the collected telemetry data from the 2019 Shell Eco-marathon competition in London (UK). The evaluation of applicable powertrains was carried out before the driving strategy optimization. The optimal acceleration curve for each investigated powertrain was defined. Using the proper powertrain is a crucial part of energy efficiency, as the drive has the most significant energy demand among all components. Two tracks with different characteristics were analyzed to show the efficiency of the proposed optimization method. The optimization results are compa... [more]

Recently, the integration of distributed generation and energy systems has been associated with new approaches to plant operations. As a result, it is becoming increasingly important to improve management skills related to distributed generation and demand aggregation through different types of virtual power plants (VPPs). It is also important to leverage their ability to participate in electricity markets to maximize operating profits. The present study focuses on VPP concepts, its different potential services, various control methodologies, distinct optimization approaches, and some practical implemented real cases. To this end, a comprehensive review of the most recent scientific literature is conducted. The paper concludes with remained challenges and future trends in the topic.

Permanent magnet synchronous motors (PMSMs) are the main source of power in modern machine tools and are required to generate a high torque over a wide speed range in order to improve manufacturing efficiency. This study sets out to optimize the rotor design of a PMSM with a rated power, rated speed, rated torque and maximum speed of 34 kW, 2250 rpm, 144.3 N·m and 11,250 rpm, respectively. A multi-objective optimization algorithm is employed to determine the rotor design parameters which maximize the output torque of the PMSM over three different load conditions (no load, rated load and maximum speed load). ANSYS multi-physics simulations are conducted to examine the electromagnetic, the structural field, temperature/flow field, demagnetization parament analysis and map analysis of global characteristics of the optimized PMSM. In general, the results show that the optimized PMSM provides a high torque and high-speed expansion performance, and thus facilitates a wide range of applicatio... [more]

Feature selection is the procedure of extracting the optimal subset of features from an elementary feature set, to reduce the dimensionality of the data. It is an important part of improving the classification accuracy of classification algorithms for big data. Hybrid metaheuristics is one of the most popular methods for dealing with optimization issues. This article proposes a novel feature selection technique called MetaSCA, derived from the standard sine cosine algorithm (SCA). Founded on the SCA, the golden sine section coefficient is added, to diminish the search area for feature selection. In addition, a multi-level adjustment factor strategy is adopted to obtain an equilibrium between exploration and exploitation. The performance of MetaSCA was assessed using the following evaluation indicators: average fitness, worst fitness, optimal fitness, classification accuracy, average proportion of optimal feature subsets, feature selection time, and standard deviation. The performance w... [more]

Multi-speed transmission can greatly improve the power and economic performance of electric vehicles (EVs) compared with single-speed transmission. Gear ratio is the key design parameter of multi-speed transmission. Optimizing gear ratios can further improve vehicle performance. Most of the existing optimization methods of gear ratios take the power and economy of vehicles in gear as the optimization objectives, but rarely consider the shift performance of the transmission, such as shift time, friction, and shift jerk. Considering the shift performance in the process of gear ratio optimization can not only optimize the vehicle performance in gear, but also improve the shift performance of the transmission. Therefore, this paper proposes a multi-objective optimization method of gear ratios considering the shift performance. Firstly, a seamless three-speed automated manual transmission (AMT) of EVs is selected as the research object, the structure and the shift process without power inte... [more]

A new and efficient analytical optimization methodology for the design of rotor features is developed and used in interior permanent magnet motors (IPM). The analytical methodology is based on an extended winding function theory to include the IPM rotor’s primary and secondary reluctance paths and the non-homogeneous airgap of the rotor sculpt features. The shape and placement of the rotor features, derived from the analytical-based optimization process, show the improvement in torque average and torque ripple of the IPM machine at a fraction of computational effort. The analytical optimization results are validated with finite element analysis via an exhaustive search.

This editorial overviews the contents of the Special Issue “Machine Learning for Energy Systems 2021” and review the trends in machine learning (ML) techniques for energy system (ES) optimization [...]

The motor is an important component that affects the output performance of new energy vehicles (using new energy sources such as electric energy and hydrogen fuel energy to drive the motor and provide kinetic energy). Motors with high power and low noise can effectively improve the dynamic performance, passability and smoothness of new energy vehicles and bring a comfortable experience to driver and passengers. The magnetic field analytical model of the inner-mounted permanent magnet synchronous motor (IPMSM) is studied to improve its output quality. The motor is divided into four subdomains: the stator slot subdomain, the stator slot notch subdomain, the air-gap subdomain, and the permanent magnet (PM) subdomain. The general solution of the vector magnetic potential of each subdomain is solved, and the expression of magnetic flux density of each subdomain is derived. Meanwhile, the analytical model of the non-uniform air gap is established according to the uniform air-gap model. The m... [more]

Sustainable, stable, and cost-optimized operation of power grids must be the main objectives of power grid operators and electric utilities. The energy transition towards a preponderant green energy economy requires innovative solutions to enhance the power grid economic dispatches looking for a better allocation of the energy demand among the diverse renewable and fossil fuel energy plants. Green renewable energy systems must be preferred over fossil fuel generators when they are available. However, fossil plants are still required to be kept operational due to the variability and uncertainty of renewable energy plants. This study proposes a hybrid rational economic dispatch model that combines a cost minimization linear model enhanced with a fuzzy logic system for decision-making on wind and hydropower minimum and maximum generation levels. The model considers the intermittency of wind energy and recognizes the strategic value of hydropower as energy storage. The results of the model... [more]

A new optimization technique is proposed for solving optimization problems having single and multiple objectives, with objective functions such as generation cost, loss, and severity value. This algorithm was developed to satisfy the constraints, such as OPF constraints, and practical constraints, such as ram rate limits. Single and multi-objective optimization problems were implemented with the proposed hybrid fruit fly-based artificial bee colony (HFABC) algorithm and the non-dominated sorting hybrid fruit fly-based artificial bee colony (NSHFABC) algorithm. HFABC is a hybrid model of the fruit fly and ABC algorithms. Selecting the user choice-based solution from the Pareto set by the proposed NSHFABC algorithm is performed by a fuzzy decision-based mechanism. The proposed HFABC method for single-objective optimization was analyzed using the Himmelblau test function, Booth’s test function, and IEEE 30 and IEEE 118 bus standard test systems. The proposed NSHFABC method for multi-objec... [more]

Microgrid (MG) is a combination of distributed generators (DGs), energy storage systems (ESSs), and loads connected to distribution network that can either be in islanded mode or grid-tied mode. Similarly, a multi-microgrid (MMG) system is a number of interconnected MGs connected with a larger and complex distribution network. Recently, the MMG energy management has created new challenges due to the inherent intermittency, uncertainty, and probabilistic nature of renewable based DGs output and varying load demands. To ensure the efficient operation and optimal energy management in the MMGs, this work proposes a two-stage, a day-ahead, simultaneous energy management strategy (EMS) of the MMG system as well as the MG system. At the first stage, each MG assumes a day-ahead predicted load demand and DGs output. At the second stage, through EMS, the energy scheduling, minimization of the main grid dependency, and maximization of the stored energy in the ESS are managed simultaneously. Four... [more]

In this work, a meta-heuristic optimization based method, known as the Firefly Algorithm (FA), to achieve the maximum power point (MPP) of a solar photo-voltaic (PV) system under partial shading conditions (PSC) is investigated. The Firefly Algorithm outperforms other techniques, such as the Perturb & Observe (P&O) method, proportional integral derivative (PID, and particle swarm optimization (PSO). These results show that the Firefly Algorithm (FA) tracks the MPP accurately compared with other above mentioned techniques. The PV system performance parameters i.e., convergence and tracking speed, is improved compared to conventional MPP tracking (MPPT) algorithms. It accurately tracks the various situations that outperform other methods. The proposed method significantly increased tracking efficiency and maximized the amount of energy recovered from PV arrays. Results show that FA exhibits high tracking efficiency (>99%) and less convergence time (<0.05 s) under PSCs with less power... [more]

River water source heat pump (RWSHP) systems are being proposed to reduce the energy consumption and carbon emissions of buildings. The RWSHP system is actively applied to large-scale buildings due to its stable performance. The application of RWSHP in large-scale facilities requires an accurate capacity design with considerations of building load, heat source, and environment conditions. However, most RWSHP systems are over-designed based on peak load of buildings. These design methods, based on peak loads, are economically and environmentally disadvantageous. Therefore, this paper aims to development an optimal design method, both economically and environmentally, for the RWSHP system. To develop this optimal design method, a simulation model was created with an optimization algorithm. The economics of the RWSHP system were calculated bases on present worth of annuity factor. Moreover, CO2 emissions were estimated using the life cycle climate performance proposed by the International... [more]

Effective methods for the design of high-performance electrical machines must use optimization techniques and precise and fast physical models. Convergence, precision and speed of execution are important issues, in addition to the ability to explore the entire domain of solutions. The finite element method (FEM) presents a high accuracy in the results but with high computational costs. Analytical models, on the other hand, solve the problem quickly but compromise the accuracy of the results. This work shows a comparison between an optimization made with an analytical electromagnetic model and a direct optimization with finite element field calculation for the optimal design of a Halbach array permanent magnet synchronous motor (PMSM). In the case of the analytical model, it is necessary to use an iterative method of correcting the model to obtain a valid solution. This method is known as Space Mapping (SM) and the analytical model can be improved with a reduced number of iterations wit... [more]

In the EU countries, almost 50% of the produced energy is used in residential buildings. More than 25% of this energy is used to produce domestic hot water, of which almost 80% is used to heat water in domestic hot water circulation systems. This is due to high expectations on the part of residents based on their comfort, in particular regarding the supply of heat for heating and domestic hot water. In the course of their long-term research conducted on real systems, the authors confirmed that the operation of domestic hot water distribution systems causes significant costs, mainly due to heat losses. Therefore, typical variants of energy optimization of such systems were analyzed. Tests have shown that selected solutions, such as the use of control automation, are not sufficient, and recommended additional thermal insulation may not be applicable due to technical reasons. With an aim of finding a solution to the problem, the publication analyzes operational data from an existing heat... [more]

Aiming at the phenomenon of a large amount of roof subsidence and rib caving in the gob-side roadway under the special “umbrella” coal pillar in isolated panel No. 325 of Yangcun Coal Mine, the stress distribution regularity of the gob-side roadway under a “umbrella” coal pillar was studied in detail by establishing mathematical models, theoretical analysis, and numerical simulations. The results show that the following: (1) The stress distribution regularity of the irregular coal pillar is actually the mechanical structure of irregular gob. (2) The abutment pressure of the gob is always distributed vertically along the edge of the gob. When the edge of the gob intersects diagonally with the gob roadway, the stress distribution of the surrounding rock of the roadway cannot be calculated only by the width of the coal pillar—the angle between the edge of the gob and the roadway should also be considered. (3) The abutment pressure at each cusp position in irregular gob extends in the oppo... [more]

Economic load dispatch (ELD) provides significant benefits to the operation of the power system. It appears to be a complex nonconvex optimization problem subject to several equal and unequal constraints. The greedy sine-cosine nonhierarchical gray wolf optimizer (G-SCNHGWO) is introduced in this study to solve complex nonconvex ELD optimization problems efficiently and robustly. The sine and cosine functions assist the search agents of the grey wolf optimizer (GWO) algorithm in avoiding trapping in a local optimum. In addition, the greedy nonhierarchical concept is integrated into GWO to enrich the optimization power of the conventional GWO algorithm. Simulations are implemented to validate the capability of the suggested algorithm in solving the different ELD problems. According to the results, the algorithm demonstrates very suitable performance compared to other state-of-the-art methods.

This paper proposes a distributed robust multi-energy dynamic optimal power flow (DR-DOPF) model to overcome the uncertainty of new energy outputs and to reduce water spillage in hydropower plants. The proposed model uses an ambiguity set based on the Wasserstein metric to address the uncertainty of wind and solar power forecasting errors, rendering the model data-driven. With increasing sample size, the conservativeness of the ambiguity set was found to decrease. By deducing the worst-case expectation in the objective function and the distributed robust chance constraints, the exact equivalent form of the worst-case expectation and approximate equivalent form of the distributed robust chance constraints were obtained. The test results of the IEEE-118 and IEEE-300 node systems indicate that the proposed model could reduce water spillage by more than 85% and comprehensive operation cost by approximately 12%. With an increasing number of samples, the model could reduce conservativeness o... [more]

As many distributed power sources flood into the distribution network, the relationship between transmission and distribution grids in reactive power and voltage is becoming closer and closer. The traditional way of independent reactive power optimization in transmission and distribution grids is no longer appropriate. In this study, a collaborative and distributed reactive power optimization method for transmission and distribution grids based on the accelerated augmented Lagrangian (AAL) algorithm is proposed to adapt to the independence of the transmission and distribution grids in operation and management. The global reactive power optimization problem is decomposed into the transmission network subproblem and several distribution network subproblems. According to AAL, subproblems are solved in a distributed manner until the optimal global solution is finally reached after several iterations, and coordination between transmission and distribution grids is achieved only through the... [more]

The traditional decomposition−combination wind speed forecasting model has high complexity and a long calculation time. As a result, an ultra-short-term wind speed hybrid forecasting model based on a broad learning system (BLS) that combines improved variational mode decomposition (EPSO-VMD, EVMD) and subseries reconstruction (SR) is proposed in this work. The values of K and α in the EVMD are determined by minimum mean envelope entropy (MMEE) and enhanced particle swarm optimization (EPSO), and EVMD is used to decompose the original wind speed data. SR is applied to recombine the subseries obtained by EVMD to improve the forecasting efficiency. The sample entropy (SE) is used to quantify the subseries’ complexity, and they are then adaptively divided into high-entropy and low-entropy subseries. Adjacent high-entropy subseries of approximate entropy values are merged to obtain a new group of reconstructed high-entropy subseries, while the low-entropy subseries merge into a new subserie... [more]

The organic Rankine cycle (ORC) has been widely studied to recover waste heat from internal combustion engines in commercial on-road vehicles. To achieve a cost-effective ORC, a trade-off between factors such as costs, power outputs, back pressure, and weight needs to be carefully worked out. However, the trade-off is still a huge challenge in engine waste heat recovery. In this study, a thermoeconomic optimization study of a vehicle-mounted ORC unit is proposed to recover waste heat from various exhaust gas conditions of a light-duty vehicle. The optimization is carried out for four organic working fluids with different critical temperatures, respectively. Under the investigated working fluids, the lower specific investment cost (SIC) and higher mean net output power (MEOP) of ORC can be achieved using the organic working fluid with higher critical temperature. The maximum mean net output power is obtained by taking RC490 as working fluid and the payback period (PB) is 3.01 years when... [more]

Rapid industrial development and innovations in technology bring about the menace of congestion in deregulated power systems (DPS). The transmission lines are continuously working under a stressed condition with reduced power transfer capacity. In this situation, the power losses and voltage deviations at the load buses are increased and hence reduce the system stability. To mitigate congestion, improving available transfer capability (ATC) of the transmission system is one of the most feasible and practical solution. This paper focuses on the implementation of Thyristor Controlled Series capacitor (TCSC) to mitigate congestion by enhancing ATC and via reducing power losses. AC Power Transfer Distribution Factor (ACPTDF) is applied to calculate ATC and to find the location of TCSC. To optimize the TCSC parameter (reactance), a Teaching Learning Based Optimization (TLBO) is proposed in the present work. The proposed optimization is validated on the IEEE 30 Bus system. The results are va... [more]

This paper proposes centralized and distributed optimization models for V2G applications to provide frequency regulation in power systems and the electricity market. Battery degradation and dynamic EV usages such as EV driving period, driving distance, and multiple charging/discharging locations are modeled. The centralized V2G problem is formulated into the linear programming (LP) model by introducing two sets of slack variables. However, the centralized model encounters limitations such as privacy concerns, high complexity, and central failure issues. To overcome these limitations, the distributed optimal V2G model is developed by decomposing the centralized model into subproblems using the augmented Lagrangian relaxation (ALR) method. The alternating direction method of multipliers (ADMM) is used to solve the distributed V2G model iteratively. The proposed models are evaluated using real data from the Independent Electricity System Operator (IESO) Ontario, Canada. Simulation results... [more]