A space solar power station (SSPS) has become a huge potential candidate to provide abundant and clean electrical energy for terrestrial users by collecting and converting solar power in space. In this paper, an innovative two-layer ring truss-based SSPS is proposed. It consists of the top layer concentrator-based spherical one-time reflection region, the bottom layer space radiator using symmetric or asymmetric cable networks, a ring truss for a supporting structure, a photoelectric conversion system, and transmitting antennas. The construction strategies including the triangular facets modularity of top layer concentrator, area requirement of bottom layer space radiator, two-segment optimization design of generatrix of photoelectric conversion system, and aperture derivation of transmitting antenna are carried out. Then, the performance analysis mainly including the modularization theory error calculation, energy collection and distribution, and thermal characteristics in orbit of th... [more]

Coal-fired power plants are widely used to achieve a power balance in grids with renewable energy, which leads to new requirements for speediness in load dispatch. This paper presents a nondominated-sorting grey wolf optimizer algorithm (NSGWO) for the multiobjective load dispatch of coal-fired power plants that employed efficient nondominated sorting, a reference-point selection strategy, and a simulated binary crossover operator. The optimization results of the benchmark functions indicated that the NSGWO algorithm had a better accuracy and a better distribution than the traditional multiobjective grey wolf optimizer algorithm. Regarding the load dispatch of economy, environmental protection, and speediness strategies, the NSGWO had the best performance of all the simulated algorithms. The optimal-compromise solutions of the economy and speediness strategies of the NSGWO algorithm had a good distribution, which elucidated that this novel algorithm was favorable to allowing coal-fired... [more]

We invert gravity and magnetic anomalies for basement relief at the Harrat Rahat Volcanic Field (HRVF) for the purpose of evaluating its geothermal energy prospects. HRVF is dominated by basaltic scoria cones and other volcanic rocks overlying the Proterozoic basement. The area considered for this study is located within the northern HRVF and consists mainly of alkali basalts with lesser amounts of benmoreite, mugearite, hawaiite, and trachyte. Our approach adopts a global optimization technique using Particle Swarm Optimization with automated parameter selection, and a two-dimensional gravity-magnetic (GM) forward modeling procedure. The results of the PSO-based approach indicate a depth to the basement at 0.10−624 m, with greater depths within the central region of a solitary anomalous density body in the HRVF. The obtained basement geometry is corroborated by the depth estimates obtained from other potential field inversion methods. The regions with higher prospects are mapped for a... [more]

With increasing concerns on transportation decarbonization, fuel cell hybrid trains (FCHTs) attract many attentions due to their zero carbon emissions during operation. Since fuel cells alone cannot recover the regenerative braking energy (RBE), energy storage devices (ESDs) are commonly deployed for the recovery of RBE and provide extra traction power to improve the energy efficiency. This paper aims to minimize the net hydrogen consumption (NHC) by co-optimizing both train speed trajectory and onboard energy management using a time-based mixed integer linear programming (MILP) model. In the case with the constraints of speed limits and gradients, the NHC of co-optimization reduces by 6.4% compared to the result obtained by the sequential optimization, which optimizes train control strategies first and then the energy management. Additionally, the relationship between NHC and employed ESD capacity is studied and it is found that with the increase of ESD capacity, the NHC can be reduce... [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]

The optimization of injection−production parameters is an important step in the design of gas injection development schemes, but there are many influencing factors and they are difficult to determine. To solve this problem, this paper optimizes injection-production parameters by combining an improved particle swarm optimization algorithm to study the relationship between injection-production parameters and the net present value. In the process of injection-production parameter optimization, the particle swarm optimization algorithm has shortcomings, such as being prone to fall into local extreme points and slow in convergence speed. Curve adaptive and simulated annealing particle swarm optimization algorithms are proposed to further improve the optimization ability of the particle swarm optimization algorithm. Taking the Tarim oil field as an example, in different stages, the production time, injection volume and flowing bottom hole pressure were used as input variables, and the optima... [more]

Hydrogen and renewable electricity-based microgrid is considered to be a promising way to reduce carbon emissions, promote the consumption of renewable energies and improve the sustainability of the energy system. In view of the fact that the existing day-ahead optimal operation model ignores the uncertainties and fluctuations of renewable energies and loads, a two-stage energy management model is proposed for the sustainable wind-PV-hydrogen-storage microgrid based on receding horizon optimization to eliminate the adverse effects of their uncertainties and fluctuations. In the first stage, the day-ahead optimization is performed based on the predicted outpower of WT and PV, the predicted demands of power and hydrogen loads. In the second stage, the intra-day optimization is performed based on the actual data to trace the day-ahead operation schemes. Since the intra-day optimization can update the operation scheme based on the latest data of renewable energies and loads, the proposed t... [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 work describes a systematic optimization strategy for designing hypersonic inlet intakes. A Reynolds-averaged Navier-Stokes database is mined using genetic algorithms to develop ideal designs for a priori defined targets. An intake geometry from the literature is adopted as a baseline. Thus, a steady-state numerical assessment is validated and the computational grid is tuned under nominal operating conditions. Following validation tasks, the model is used for multi-objective optimization. The latter aims at minimizing the drag coefficient while boosting the static and total pressure ratios, respectively. The Pareto optimal solutions are analyzed, emphasizing the flow patterns that result in the improvements. Although the approach is applied to a specific setup, the method is entirely general, offering a valuable flowchart for designing super/hypersonic inlets. Notably, because high-quality computational fluid dynamics strategies drive the innovation process, the latter accounts for... [more]

This paper analyzes the potential for deep renovation of an apartment building to the level of a passive house in different contexts in the continental part of Europe. The examined variables include different local climatic conditions, levels of economic development, and levels of market development (energy prices, energy footprint, labor prices, etc.) as well as different energy efficiency retrofit scenarios in four different countries. The adequate methodology was developed here in order to obtain an optimal solution for deep renovation in each context. The proposed methodology was based on the interaction of energy simulation and mathematical optimization. In this model, the energy performances of a building are determined with the EnergyPlus package and the optimal solution was obtained by using a mixed-integer non-linear programming model. The results demonstrate that the optimal solution for each analyzed location cannot provide cost-effectiveness over the lifetime of a building,... [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]

To improve the accuracy of park load forecasting, a combined forecasting method for short-term park load is proposed based on complementary ensemble empirical mode decomposition (CEEMD), sample entropy, the satin bower bird optimization algorithm (SBO), and the least squares support vector regression (LSSVR) model. Firstly, aiming at the random fluctuation of park load series, the modes with different characteristic scales are divided into low-frequency and high-frequency according to the calculation of sample entropy, which is based on the decomposition of historical park load data modes by CEEMD. The low-frequency is forecast by multiple linear regression (MLR), and the high-frequency component is the training input of the LSSVR forecasting model. Secondly, the SBO algorithm is adopted to optimize the regularization parameters and the kernel function width of LSSVR. Then, the park load forecasting model of each sequence component is built. The forecast output of each sequence compone... [more]

Although there are opportunities to reduce electrical energy demand in unit processes of mechanical pulp-based paper and paperboard production, this may not be financially beneficial. This is generally because energy optimization opportunities connected to reduced refiner electricity demand in mechanical pulping systems also results in less steam available for the drying of the paper. As modern high consistency refiner systems produce approximately one ton of steam for each MWh of electricity when producing one ton of pulp, a reduction in electric energy demand leads to increased fuel demand in steam boilers to compensate for the steam shortage. In this study, we investigated what the financial and environmental situation would look like if we were to expand the system border from a paper mill to a larger system consisting of a mechanical pulp-based paper or paperboard mill, a district heating system with an incineration boiler and a chemical pulp mill. Mechanical pulp production has a... [more]

Energy system integration enables raising operational synergies by coupling the energy infrastructures for electricity, methane, and hydrogen. However, this coupling reinforces the infrastructure interdependencies, increasing the need for integrated modeling of these infrastructures. To analyze the cost-efficient, sustainable, and secure dispatch of applied, large-scale energy infrastructures, an extensive and non-linear optimization problem needs to be solved. This paper introduces a nested decomposition approach with three stages. The method enables an integrated and full-year consideration of large-scale multi-energy systems in hourly resolution, taking into account physical laws of power flows in electricity and gas transmission systems as boundary conditions. For this purpose, a zooming technique successively reduces the temporal scope while first increasing the spatial and last the technical resolution. A use case proves the applicability of the presented approach to large-scale... [more]

Recently, non-rare-earth motors are attracting more and more attention due to the booming of the electric vehicle (EV) market and, more importantly, the increasing price of the rare-earth magnet material. This paper focuses on the performance comparison among a commercial interior permanent magnet (IPM) motor and two non-rare-earth motors, including a synchronous reluctance motor (SynRM) and a permanent-magnet-assisted synchronous reluctance motor (PMaSynRM). The design procedure to develop a high-torque-density, low-torque-ripple and high-efficiency SynRM is presented. Combined with a developed automatic modeling and simulation procedure, the finite element analysis (FEA)-based differential evolution (DE) algorithm is introduced for the SynRM rotor optimization. In order to fully inspire the potential of the SynRM, a novel method to optimize the motor split ratio is proposed under the constraint of the copper loss. In addition, different slot−pole combinations are investigated to maxi... [more]

The aim of this study is to improve the three-phase unbalanced voltage at the secondary side of a distribution transformer. The proposed method involves compensation sources injecting three different single-phase currents into the connected point of a grid. The computations of optimal single-phase currents are performed using the circuit analysis method and particle swarm optimization algorithm. An unbalanced three-phase power distribution system model is constructed, including a transformer Δ−Δ connection, V−V connection, load balance, load unbalance combination, and three single-phase compensation current sources. The results show that the voltage unbalance rate of the electricity user side is improved to less than 1%, and the three-phase total compensation apparent power is approximately 0 VA. In the future, the application of the model as an auxiliary service could be achieved by adding an energy storage system.

Piezoelectric energy harvesting from roadways, which converts ambient vibration energy of roads into electric energy, has a wide range of potential applications in intelligent transportation systems. On-site open-traffic tests revealed that energy harvested by piezoelectric energy harvester (PEH) units embedded in roadways is far less than the value in laboratories, which may be because the parameters of traffic flow load (frequency, distribution, wave shape, etc.) and the road structure are significantly different from the pre-established conditions in laboratories or even on-site tests with only one vehicle passing. To address this issue, an analytical model for piezoelectric energy harvesting from roadways under open-traffic conditions was proposed to examine the mechanical response of the road structure and the electrical performance of the stack PEH units embedded in the road. The influence of all parameters in the energy-harvesting system was then obtained with the scaling law me... [more]

Salinity gradient energy (SGE) allows the difference in salt concentration in two volumes of water to be harnessed and transformed into clean energy. The most advanced SGE technology is reverse electrodialysis (RED) cells. Recent studies have focused on ways to optimize the flow distribution in the compartments containing the water, for which it is necessary to consider the characteristics of the solutions, the cell dimensions, the operating conditions, as well as their influence on the hydrodynamics and mass transport in the system. In this study, two spacers with different gasket geometry were designed, fabricated, and compared experimentally through voltage and current measurements. The power output was computed, obtaining a maximum power density of 0.14 W/m2. Results show that the geometry of the cell components directly influences the physicochemical principles governing the RED process and is closely related to the cell output parameters. In turn, it is possible to increase the p... [more]

In the rapid promotion of China’s electricity spot market, a large number of electricity retailers and large consumers participate in power trading, of which medium- and long-term power trading accounts for a large proportion. In the electricity spot market, the previous medium- and long-term transactions need to be closely combined with the current spot market transaction settlement rules. This paper analyzes the trading strategy of large retailers in the power market. In order to effectively reduce the total electricity cost, it is necessary to optimize the medium- and long-term transactions based on three aspects: electricity quantity and benchmark price decisions of medium- and long-term contracts, the daily electricity decomposition method in the day-ahead (DA) market, and the daily load curve decomposition strategy. According to load history characteristics that are extracted by the X12 method, daily electricity is decomposed from the medium- and long-term electricity quantity in... [more]

The anticipated electrification of the transport sector may lead to significant increase in the future peak electricity demand, resulting in potential violations of network constraints. As a result, a considerable amount of network reinforcement may be required in order to ensure that the expected additional demand from electric vehicles that are to be connected will be safely accommodated. In this paper we present the Backwards Induction Framework (BIF), which we use for identifying the optimal investment decisions, for calculating the option value of smart charging of EV and the cost of stranded assets; these concepts are crystallized through illustrative case studies. Sensitivity analyses depict how the option value of smart charging and the optimal solution are affected by key factors such as the social cost associated with not accommodating the full EV capacity, the flexibility of smart charging, and the scenario probabilities. Moreover, the BIF is compared with the Stochastic Opt... [more]

It is of great significance to predict the energy performance of centrifugal pumps for the improvement of the pump design. However, the complex internal flow always affects the performance prediction of centrifugal pumps, particularly under low-flow operating conditions. Relying on the data-fitting method, a multi-condition performance prediction method for centrifugal pumps is proposed, where the performance relationship is incorporated into the particle swarm optimization algorithm, and the prediction model is optimized by automatically meeting the performance constraints. Compared with the experimental results, the performance under multiple operating conditions is well predicted by introducing performance constraints with the mean absolute relative error (MARE) for the head, power and efficiency of 0.85%, 1.53%,1.15%, respectively. By comparing the extreme gradient boosting and support vector regression models, the support vector regression is more suitable for the prediction of pe... [more]

This paper focuses on improving the operating efficiency of the Liquified Natural Gas (LNG) submerged pump system in the LNG receiving terminals and achieve energy saving. The minimum input energy consumption of the LNG submerged pump system is taken as the objective function, and an optimization model for the operation of the LNG submerged pump system with variable frequency speed is established. LINGO18.0 optimization software is used to solve the model to get the optimal LNG submerged pump operation plan that satisfies the constraints. Taking a certain LNG receiving terminal as an example, the operation optimization of its LNG submerged pump system is carried out, and the input energy consumption of the system before and after optimization is compared. The results show that the use of variable frequency pumps can reduce the energy consumption of the LNG submerged pump system of LNG receiving terminals, and the optimization model can reduce the input power consumption of the system b... [more]

The integration of pipeline energy storage in the control of a district heating system can lead to profit gain, for example by adjusting the electricity production of a combined heat and power (CHP) unit to the fluctuating electricity price. The uncertainty from the environment, the computational complexity of an accurate model, and the scarcity of placed sensors in a district heating system make the operational use of pipeline energy storage challenging. A vast majority of previous works determined a control strategy by a decomposition of a mixed-integer nonlinear model and significant simplifications. To mitigate consequential stability, feasibility, and computational complexity challenges, we model CHP economic dispatch as a Markov decision process. We use a reinforcement learning (RL) algorithm to estimate the system’s dynamics through interactions with the simulation environment. The RL approach is compared with a detailed nonlinear mathematical optimizer on day-ahead and real-tim... [more]

The pressure drop of a main steam and reheat steam system should be optimized during the design and operation of a thermal power plant to minimize operation costs. In this study, the pressure drop of the main steam pipe and reheat steam pipe of a 1000 MW secondary reheat unit are optimized by modulating the operation parameters and the cost of operation is explored. Optimal pipe specifications were achieved by selecting a bend pipe and optimizing the pipe specifications. The pressure loss of the main steam pipeline was optimized to 2.61% compared with the conventional pressure drop (5%), the heat consumption of steam turbine was reduced by about 0.63 kJ/(kW·h), the standard coal consumption was minimized by about 0.024 g/(kW·h), and the total income in 20 years is approximated to be CNY 217,700. The primary reheat system was optimized to 4.88%, the steam turbine heat consumption was reduced by about 7.13 kJ/(kW·h), the standard coal consumption decreased by about 0.276 g/(kW·h), and th... [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]