The real-time and accurate calculation of electricity indirect carbon emissions is not only the critical component for quantifying the carbon emission levels of the power system but also an effective mean to guide ele...The real-time and accurate calculation of electricity indirect carbon emissions is not only the critical component for quantifying the carbon emission levels of the power system but also an effective mean to guide electricity users in carbon reduction and promote power industry low-carbon transformation.Fundamentally,calculating indirect carbon emissions involves allocating direct carbon emission data from the power source side,indicating that accurate indirect emission results rely on the precise measurement of power source emissions.However,existing research on indirect carbon emissions in large-scale power systems rarely accounts for variations in carbon emission characteristics under different operating conditions of power sources,such as rated/non-rated operating conditions and ramping up/down conditions,making it difficult to reflect source-side and load-side carbon emission information variation during providing ancillary services.Quadratic and exponential functions are proposed to characterize the energy consumption profiles of coal-fired and gas-fired power generation,respectively,to construct a refined carbon emission model for power sources.By leveraging the theory of power system carbon flow,we analyze how variable operating conditions of power sources impact indirect carbon emissions.Case studies demonstrate that changes in power source emissions under variable conditions have a significant effect on the indirect carbon emissions of power grids.展开更多
To address the issues of high costs and low component utilization caused by the independent configuration of hybrid DC circuit breakers(HCBs)and DC power flow controllers(DCPFCs)at each port in existing DC distributio...To address the issues of high costs and low component utilization caused by the independent configuration of hybrid DC circuit breakers(HCBs)and DC power flow controllers(DCPFCs)at each port in existing DC distribution networks,this paper adopts a component sharing mechanism to propose a composite multi-port hybrid DC circuit breaker(CM-HCB)with DC power flow and fault current limitation abilities,as well as reduced component costs.The proposed CM-HCB topology enables the sharing of the main breaker branch(MB)and the energy dissipation branch,while the load commutation switches(LCSs)in the main branch are reused as power flow control components,enabling flexible regulation of power flow in multiple lines.Meanwhile,by reconstructing the current path during the fault process,the proposed CM-HCB can utilize the internal coupled inductor to limit the current rise rate at the initial stage of the fault,significantly reducing the requirement for breaking current.A detailed study on the topological structure,steady-state power flow regulation mechanism,transient fault isolation mechanism,control strategy and characteristic analysis of the proposed CM-HCB is presented.Then,a Matlab/Simulink-based meshed three-terminal DC grid simulation platform with the proposed CM-HCB is built.The results indicate that the proposed CM-HCB can not only achieve flexible power flow control during steady-state operation,but also obtain current rise limitation and fault isolation abilities under short-circuit fault conditions,verifying its correctness and effectiveness.Finally,a comparative economic analysis is conducted between the proposed CM-HCB and the other two existing solutions,confirming that its component sharing mechanism can significantly reduce the number of components,lower system costs,and improve component utilization.展开更多
To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hyb...To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hybrid modular multilevel converter–capacitor-commutated line-commutated converter(MMC-CLCC)HVDC transmission system and its corresponding control strategy.First,the system topology is constructed,and a submodule configuration method for the MMC—combining full-bridge submodules(FBSMs)and half-bridge submodules(HBSMs)—is proposed to enable direct power flow reversal.Second,a hierarchical control strategy is introduced,includingMMCvoltage control,CLCC current control,and a coordinationmechanism,along with the derivation of the hybrid system’s power flow reversal characteristics.Third,leveraging the CLCC’s fast current regulation and theMMC’s negative voltage control capability,a coordinated power flow reversal control strategy is developed.Finally,an 800 kV MMC-CLCC hybrid HVDC system is modeled in PSCAD/EMTDC to validate the power flow reversal performance under a high proportion of full-bridge submodule configuration.Results demonstrate that the proposed control strategy enables rapid(1-s transition)and smooth switching of bidirectional power flow without modifying the structure of primary equipment:the transient fluctuation ofDC voltage from the rated value(UdcN)to themaximumreverse voltage(-kUdcN)is less than 5%;the DC current strictly follows the preset characteristic curve with a deviation of≤3%;the active power reverses continuously,and the system maintains stable operation throughout the reversal process.展开更多
In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave pow...In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.展开更多
The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment,hindering the efficient utilization of renewable energy and the low-carbon development of...The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment,hindering the efficient utilization of renewable energy and the low-carbon development of energy systems.To enhance the consumption capacity of green power,the green power system consumption optimization scheduling model(GPS-COSM)is proposed,which comprehensively integrates green power system,electric boiler,combined heat and power unit,thermal energy storage,and electrical energy storage.The optimization objectives are to minimize operating cost,minimize carbon emission,and maximize the consumption of wind and solar curtailment.The multi-objective particle swarm optimization algorithm is employed to solve the model,and a fuzzy membership function is introduced to evaluate the satisfaction level of the Pareto optimal solution set,thereby selecting the optimal compromise solution to achieve a dynamic balance among economic efficiency,environmental friendliness,and energy utilization efficiency.Three typical operating modes are designed for comparative analysis.The results demonstrate that the mode involving the coordinated operation of electric boiler,thermal energy storage,and electrical energy storage performs the best in terms of economic efficiency,environmental friendliness,and renewable energy utilization efficiency,achieving the wind and solar curtailment consumption rate of 99.58%.The application of electric boiler significantly enhances the direct accommodation capacity of the green power system.Thermal energy storage optimizes intertemporal regulation,while electrical energy storage strengthens the system’s dynamic regulation capability.The coordinated optimization of multiple devices significantly reduces reliance on fossil fuels.展开更多
Power flow optimization control,which governs the energy flow among engine,battery,and motor,plays a very important role in plug-in hybrid electric vehicles(PHEVs).Its performance directly affects the fuel economy of ...Power flow optimization control,which governs the energy flow among engine,battery,and motor,plays a very important role in plug-in hybrid electric vehicles(PHEVs).Its performance directly affects the fuel economy of PHEVs.For the purpose of improving fuel economy,the electric system including battery and motor will be frequently scheduled,which would affect battery life.Therefore,a multi-objective optimization mechanism taking fuel economy and battery life into account is necessary,which is also a research focus in field of hybrid vehicles.Motivated by this issue,this paper proposes a multi-objective power flow optimization control strategy for a power split PHEV using game theory.Firstly,since the demand power of driver which is necessary for the power flow optimization control,cannot be known in advance,the demand power of driver can be modelled using a Markov chain to obtain predicted demand power.Secondly,based on the predicted demand power,the multi-objective optimization control problem is transformed into a game problem.A novel non-cooperative game model between engine and battery is established,and the benefit function with fuel economy and battery life as the optimization objective is proposed.Thirdly,under the premise of satisfying various constraints,the participants of the above game maximize their own benefit function to obtain the Nash equilibrium,which comprises of optimal power split scheme.Finally,the proposed strategy is verified compared with two baseline strategies,and results show that the proposed strategy can reduce equivalent fuel consumption by about 15%compared with baseline strategy 1,and achieve similar fuel economy while greatly extend battery life simultaneously compared with baseline strategy 2.展开更多
The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting obj...The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.展开更多
The average risk indices,such as the loss of load expectation(LOLE)and expected demand not supplied(EDNS),have been widely used in risk assessment of power systems.However,the average indices can't distinguish bet...The average risk indices,such as the loss of load expectation(LOLE)and expected demand not supplied(EDNS),have been widely used in risk assessment of power systems.However,the average indices can't distinguish between the events of low probability but high damage and the events of high probability but low damage.In order to ov+rcome these shortcomings,this paper proposes an extended risk analysis framework for the power system based on the partitioned multi-objective risk method(PMRM).展开更多
China has abundant renewable energy resources.With the establishment of carbon peaking and carbon neutrality goals,renewable energy sources such as wind power and photovoltaics have undergone tremendous development.Ho...China has abundant renewable energy resources.With the establishment of carbon peaking and carbon neutrality goals,renewable energy sources such as wind power and photovoltaics have undergone tremendous development.However,because of the randomness and volatility of wind and photovoltaic power,the large-scale development of renewable energy faces challenges with accommodation and transmission.At present,the bundling of wind–photovoltaic–thermal power with ultra-high voltage transmission projects is the main development approach for renewable energy bases in western and northern China.Nonetheless,solving the problems of high carbon dioxide emission,carbon dioxide capture,and the utilization of thermal power is still necessary.Based on power-to-hydrogen,powerto-methanol,and oxygen-enriched combustion power generation technologies,this article proposes a power-to-hydrogen-andmethanol model based on the collaborative optimization of energy flow and material flow,which is expected to simultaneously solve the problems of renewable energy accommodation and low-carbon transformation of thermal power.Models with different ways of linking power to hydrogen and methanol are established,and an 8760-hour-time-series operation simulation is incorporated into the planning model.A case study is then conducted on renewable energy bases in the deserts of western and northern China.The results show that the power-to-hydrogen-and-methanol model based on the collaborative optimization of energy flow and material flow can greatly reduce the demand for hydrogen storage and energy storage,reduce the cost of carbon capture,make full use of by-product oxygen and captured carbon dioxide,and produce high-value chemical raw materials,thus exhibiting significant economic advantages.展开更多
On the basis of the theoretical analysis of a single-machine infinite-bus （SMIB）, using the modified linearized Phil- lips-Heffron model installed with unified power flow controller （UPFC）, the potential of the UP...On the basis of the theoretical analysis of a single-machine infinite-bus （SMIB）, using the modified linearized Phil- lips-Heffron model installed with unified power flow controller （UPFC）, the potential of the UPFC supplementary controller to enhance the dynamic stability of a power system is evaluated by measuring the electromechanical controllability through singular value decomposition （SVD） analysis. This controller is tuned to simultaneously shift the undamped electromeehanical modes to a prescribed zone in the s-plane. The problem of robust UPFC based damping controller is formulated as an optimization problem according to the eigenvalue-based multi-objective function comprising the damping factor, and the damping ratio of the undamped electromechanical modes to be solved using gravitational search algorithm （GSA） that has a strong ability to find the most optimistic results. The different loading conditions are simulated on a SMIB system and the rotor speed deviation, internal voltage deviation, DC voltage deviation and electrical power deviation responses are studied with the effect of this flexible AC transmission systems （FACTS） controller. The results reveal that the tuned GSA based UPFC controller using the proposed multi-objective function has an excellent capability in damping power system with low frequency oscillations and greatly enhances the dynamic stability of the power systems.展开更多
For the low utilization rate of photovoltaic power generation,taking a new energy power system constisting of concentrating solar power(CSP),photovoltaic power(PP)and battery energy storage system as an example,a mult...For the low utilization rate of photovoltaic power generation,taking a new energy power system constisting of concentrating solar power(CSP),photovoltaic power(PP)and battery energy storage system as an example,a multi-objective optimization scheduling strategy considering energy storage participation is proposed.Firstly,the new energy power system model is established,and the PP scenario generation and reduction frame based on the autoregressive moving average model and Kantorovich-distance is proposed.Then,based on the optimization goal of the system operation cost minimization and the PP output power consumption maximization,the multi-objective optimization scheduling model is established.Finally,the simulation results show that introducing energy storage into the system can effectively reduce the system operation cost and improve the utilization efficiency of PP.展开更多
The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayto...The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.展开更多
Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model. This model is aimed at maximizing the total sys...Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model. This model is aimed at maximizing the total system power generation and the minimum ten-day joint output. To effectively optimize the multi-objective model, a new algorithm named non-dominated sorting culture differential evolution algorithm(NSCDE) is proposed. The feasibility of NSCDE was verified through several well-known benchmark problems. It was then applied to the Jinping Wind-Solar-Hydro complementary power generation system. The results demonstrate that NSCDE can provide decision makers a series of optimized scheduling schemes.展开更多
The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-obj...The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-objective genetic algorithm (GA) was designed. Based on the model of system, the quantitative formula of the road feel, sensitivity, and operation stability of the steering were induced. Considering the road feel and sensitivity of steering as optimization objectives, and the operation stability of steering as constraint, the multi-objective GA was proposed and the system parameters were optimized. The simulation results show that the system optimized by multi-objective genetic algorithm has better road feel, steering sensibility and steering stability. The energy of steering road feel after optimization is 1.44 times larger than the one before optimization, and the energy of portability after optimization is 0.4 times larger than the one before optimization. The ground test was conducted in order to verify the feasibility of simulation results, and it is shown that the pure electric bus equipped with the recirculating ball-type EPS system can provide better road feel and better steering portability for the drivers, thus the optimization methods can provide a theoretical basis for the design and optimization of the recirculating ball-type EPS system.展开更多
Increasing demand for water from all sectors presents a challenge for policy makers to improve water allocation policies for storage reservoirs. In addition, there are many other organisms and species present in river...Increasing demand for water from all sectors presents a challenge for policy makers to improve water allocation policies for storage reservoirs. In addition, there are many other organisms and species present in river waters that also require water for their survival. Due to the lack of awareness many times the minimum required quantity and quality of water for river ecosystem is not made available at downstream of storage reservoirs. So, a sustainable approach is required in reservoir operations to maintain the river ecosystem with environmental flow while meeting the other demands. Multi-objective, multi-reservoir operation model developed with Python programming using Fuzzy Linear Programing method incorporating environmental flow requirement of river is presented in this paper. Objective of maximization of irrigation release is considered for first run. In second run maximization of releases for hydropower generation is considered as objective. Further both objectives are fuzzified by incorporating linear membership function and solved to maximize fuzzified objective function simultaneously by maximizing satisfaction level indicator (λ). The optimal reservoir operation policy is presented considering constraints including Irrigation release, Turbine release, Reservoir storage, Environmental flow release and hydrologic continuity. Model applied for multi-reservoir system consists of four reservoirs, i.e., Jayakwadi Stage-I Reservoir (R1), Jayakwadi Stage-II Reservoir (R2), Yeldari Reservoir (R3), Siddheshwar Reservoir (R4) in Godavari River sub-basin from Marathwada region of Maharashtra State, India.展开更多
This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal ...This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal allocation and sizing of multiple PV-DG units to minimize power losses using a probabilistic PV model and time-series power flow analysis. Addressing the uncertainties in PV output due to weather variability and diurnal cycles is critical. A probabilistic assessment offers a more robust analysis of DG integration’s impact on the grid, potentially leading to more reliable system planning. The presented approach employs a genetic algorithm (GA) and a determined PV output profile and probabilistic PV generation profile based on experimental measurements for one year of solar radiation in Cairo, Egypt. The proposed algorithms are validated using a co-simulation framework that integrates MATLAB and OpenDSS, enabling analysis on a 33-bus test system. This framework can act as a guideline for creating other co-simulation algorithms to enhance computing platforms for contemporary modern distribution systems within smart grids concept. The paper presents comparisons with previous research studies and various interesting findings such as the considered hours for developing the probabilistic model presents different results.展开更多
Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constr...Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constrained Optimal Power Flow(SCOPF)using the Line Outage Distribution Factor(LODF)to enhance resilience in a renewable energy-integrated microgrid.The research examines a 30-bus system with 14 generators and an 8669 MW load demand,optimizing both single-objective and multi-objective scenarios.The single-objective opti-mization achieves a total generation cost of$47,738,while the multi-objective approach reduces costs to$47,614 and minimizes battery power output to 165.02 kW.Under contingency conditions,failures in transmission lines 1,22,and 35 lead to complete power loss in those lines,requiring a redistribution strategy.Implementing SCOPF mitigates these disruptions by adjusting power flows,ensuring no line exceeds its capacity.Specifically,in contingency 1,power in channel 4 is reduced from 59 to 32 kW,while overall load shedding is minimized to 0.278 MW.These results demonstrate the effectiveness of SCOPF in maintaining stability and reducing economic losses.Unlike prior studies,this work integrates LODF into SCOPF for large-scale microgrid applications,offering a computationally efficient contingency management framework that enhances grid resilience and supports renewable energy adoption.展开更多
Due to the climate-dependent nature of renewable energy sources(RESs),solving the optimal power flow(OPF)problem in power systems that integrate RESs,such as photovoltaic(PV)units and wind turbines(WTs),remains a sign...Due to the climate-dependent nature of renewable energy sources(RESs),solving the optimal power flow(OPF)problem in power systems that integrate RESs,such as photovoltaic(PV)units and wind turbines(WTs),remains a significant challenge.To address this problem,this study presents an effective framework that incorporates solar and wind power generation.To manage the nonconvex and nonlinear characteristics of the OPF problem,a modified physics-inspired algorithm termed the Enhanced Coulomb’s and Franklin’s laws Algorithm(ECFA),is deployed.In the proposed OPF model,the power generated from RESs is considered a dependent variable,while voltages at buses equipped with RESs serve as decision variables.Real-time data on solar irradiation and wind speed are used to model the power outputs of PV units and WTs,respectively.Although the Coulomb’s and Franklin’s law algorithm(CFA)offers some advantages,it underperforms on complex optimization tasks compared to SSA,BA,SCA,ABC,and CFA.The enhanced version of the CFA improves the search process across the feasible space by incorporating diverse interaction methods and enhancing exploitation capabilities.The performance of the proposed ECFA is assessed through comprehensive comparisons with state-of-the-art methods for solving the OPF problem.展开更多
Modern shipboard microgrids(SMGs)incorporating distributed energy resources(DERs)enhance energy resilience and reduce carbon emissions.However,the hierarchical control schemes of DERs bring challenges to the tradition...Modern shipboard microgrids(SMGs)incorporating distributed energy resources(DERs)enhance energy resilience and reduce carbon emissions.However,the hierarchical control schemes of DERs bring challenges to the traditional power flow methods.This paper devises a generalized three-phase power flow approach for SMGs that integrate hierarchically controlled DERs.The main contributions include:(1)a droop-controlled three-phase Newton power flow algorithm that automatically incorporates the droop characteristics of DERs;(2)a secondary-controlled three-phase power flow method for power sharing and voltage regulation;and(3)modified Jacobian matrices to incorporate various hierarchical control modes.Numerical results demonstrate the effectiveness of the devised approach in both balanced and unbalanced three-phase hierarchically controlled SMG systems with arbitrary config-urations.展开更多
To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and en...To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and environmental issues of ships,this study aims to improve the transportation efficiency of ships by providing a ship route induction method.Ship data from a certain bay during a defined period are collected,and an improved backpropagation neural network algorithm is used to forecast ship traffic.On the basis of the forecasted data and ship route induction objectives,dynamic programming of ship routes is performed.Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55%compared with statically induced routes.This method has promising engineering applications in improving ship navigation efficiency,promoting energy conservation,and reducing emissions.展开更多
基金supported by the Science and Technology Project of China Southern Power Grid Co.,Ltd.(ZBKTM20232244)the Project of National Natural of Science Foundation of China(52477103).
文摘The real-time and accurate calculation of electricity indirect carbon emissions is not only the critical component for quantifying the carbon emission levels of the power system but also an effective mean to guide electricity users in carbon reduction and promote power industry low-carbon transformation.Fundamentally,calculating indirect carbon emissions involves allocating direct carbon emission data from the power source side,indicating that accurate indirect emission results rely on the precise measurement of power source emissions.However,existing research on indirect carbon emissions in large-scale power systems rarely accounts for variations in carbon emission characteristics under different operating conditions of power sources,such as rated/non-rated operating conditions and ramping up/down conditions,making it difficult to reflect source-side and load-side carbon emission information variation during providing ancillary services.Quadratic and exponential functions are proposed to characterize the energy consumption profiles of coal-fired and gas-fired power generation,respectively,to construct a refined carbon emission model for power sources.By leveraging the theory of power system carbon flow,we analyze how variable operating conditions of power sources impact indirect carbon emissions.Case studies demonstrate that changes in power source emissions under variable conditions have a significant effect on the indirect carbon emissions of power grids.
基金funded by Youth Talent Growth Project of Guizhou Provincial Department of Education(No.Qianjiaoji[2024]21)National Natural Science Foundation of China(No.62461008 and No.52507211)Guizhou Provincial Key Technology R&D Program(No.[2024]General 049).
文摘To address the issues of high costs and low component utilization caused by the independent configuration of hybrid DC circuit breakers(HCBs)and DC power flow controllers(DCPFCs)at each port in existing DC distribution networks,this paper adopts a component sharing mechanism to propose a composite multi-port hybrid DC circuit breaker(CM-HCB)with DC power flow and fault current limitation abilities,as well as reduced component costs.The proposed CM-HCB topology enables the sharing of the main breaker branch(MB)and the energy dissipation branch,while the load commutation switches(LCSs)in the main branch are reused as power flow control components,enabling flexible regulation of power flow in multiple lines.Meanwhile,by reconstructing the current path during the fault process,the proposed CM-HCB can utilize the internal coupled inductor to limit the current rise rate at the initial stage of the fault,significantly reducing the requirement for breaking current.A detailed study on the topological structure,steady-state power flow regulation mechanism,transient fault isolation mechanism,control strategy and characteristic analysis of the proposed CM-HCB is presented.Then,a Matlab/Simulink-based meshed three-terminal DC grid simulation platform with the proposed CM-HCB is built.The results indicate that the proposed CM-HCB can not only achieve flexible power flow control during steady-state operation,but also obtain current rise limitation and fault isolation abilities under short-circuit fault conditions,verifying its correctness and effectiveness.Finally,a comparative economic analysis is conducted between the proposed CM-HCB and the other two existing solutions,confirming that its component sharing mechanism can significantly reduce the number of components,lower system costs,and improve component utilization.
基金supported by Science and Technology Project of the headquarters of the State Grid Corporation of China(No.5500-202324492A-3-2-ZN).
文摘To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hybrid modular multilevel converter–capacitor-commutated line-commutated converter(MMC-CLCC)HVDC transmission system and its corresponding control strategy.First,the system topology is constructed,and a submodule configuration method for the MMC—combining full-bridge submodules(FBSMs)and half-bridge submodules(HBSMs)—is proposed to enable direct power flow reversal.Second,a hierarchical control strategy is introduced,includingMMCvoltage control,CLCC current control,and a coordinationmechanism,along with the derivation of the hybrid system’s power flow reversal characteristics.Third,leveraging the CLCC’s fast current regulation and theMMC’s negative voltage control capability,a coordinated power flow reversal control strategy is developed.Finally,an 800 kV MMC-CLCC hybrid HVDC system is modeled in PSCAD/EMTDC to validate the power flow reversal performance under a high proportion of full-bridge submodule configuration.Results demonstrate that the proposed control strategy enables rapid(1-s transition)and smooth switching of bidirectional power flow without modifying the structure of primary equipment:the transient fluctuation ofDC voltage from the rated value(UdcN)to themaximumreverse voltage(-kUdcN)is less than 5%;the DC current strictly follows the preset characteristic curve with a deviation of≤3%;the active power reverses continuously,and the system maintains stable operation throughout the reversal process.
文摘In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.
基金funded by the National Key Research and Development Program of China(2024YFE0106800)Natural Science Foundation of Shandong Province(ZR2021ME199).
文摘The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment,hindering the efficient utilization of renewable energy and the low-carbon development of energy systems.To enhance the consumption capacity of green power,the green power system consumption optimization scheduling model(GPS-COSM)is proposed,which comprehensively integrates green power system,electric boiler,combined heat and power unit,thermal energy storage,and electrical energy storage.The optimization objectives are to minimize operating cost,minimize carbon emission,and maximize the consumption of wind and solar curtailment.The multi-objective particle swarm optimization algorithm is employed to solve the model,and a fuzzy membership function is introduced to evaluate the satisfaction level of the Pareto optimal solution set,thereby selecting the optimal compromise solution to achieve a dynamic balance among economic efficiency,environmental friendliness,and energy utilization efficiency.Three typical operating modes are designed for comparative analysis.The results demonstrate that the mode involving the coordinated operation of electric boiler,thermal energy storage,and electrical energy storage performs the best in terms of economic efficiency,environmental friendliness,and renewable energy utilization efficiency,achieving the wind and solar curtailment consumption rate of 99.58%.The application of electric boiler significantly enhances the direct accommodation capacity of the green power system.Thermal energy storage optimizes intertemporal regulation,while electrical energy storage strengthens the system’s dynamic regulation capability.The coordinated optimization of multiple devices significantly reduces reliance on fossil fuels.
基金the National Natural Science Foundation of China(Grant Nos.51975048,U1764257 and 51705480)the Beijing Institute of Technology Research Fund Program for Young Scholars。
文摘Power flow optimization control,which governs the energy flow among engine,battery,and motor,plays a very important role in plug-in hybrid electric vehicles(PHEVs).Its performance directly affects the fuel economy of PHEVs.For the purpose of improving fuel economy,the electric system including battery and motor will be frequently scheduled,which would affect battery life.Therefore,a multi-objective optimization mechanism taking fuel economy and battery life into account is necessary,which is also a research focus in field of hybrid vehicles.Motivated by this issue,this paper proposes a multi-objective power flow optimization control strategy for a power split PHEV using game theory.Firstly,since the demand power of driver which is necessary for the power flow optimization control,cannot be known in advance,the demand power of driver can be modelled using a Markov chain to obtain predicted demand power.Secondly,based on the predicted demand power,the multi-objective optimization control problem is transformed into a game problem.A novel non-cooperative game model between engine and battery is established,and the benefit function with fuel economy and battery life as the optimization objective is proposed.Thirdly,under the premise of satisfying various constraints,the participants of the above game maximize their own benefit function to obtain the Nash equilibrium,which comprises of optimal power split scheme.Finally,the proposed strategy is verified compared with two baseline strategies,and results show that the proposed strategy can reduce equivalent fuel consumption by about 15%compared with baseline strategy 1,and achieve similar fuel economy while greatly extend battery life simultaneously compared with baseline strategy 2.
基金Projects(61105067,61174164)supported by the National Natural Science Foundation of China
文摘The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.
文摘The average risk indices,such as the loss of load expectation(LOLE)and expected demand not supplied(EDNS),have been widely used in risk assessment of power systems.However,the average indices can't distinguish between the events of low probability but high damage and the events of high probability but low damage.In order to ov+rcome these shortcomings,this paper proposes an extended risk analysis framework for the power system based on the partitioned multi-objective risk method(PMRM).
基金the financial support provided by the Major Program of Xiangjiang Laboratory(No.23XJ01006).
文摘China has abundant renewable energy resources.With the establishment of carbon peaking and carbon neutrality goals,renewable energy sources such as wind power and photovoltaics have undergone tremendous development.However,because of the randomness and volatility of wind and photovoltaic power,the large-scale development of renewable energy faces challenges with accommodation and transmission.At present,the bundling of wind–photovoltaic–thermal power with ultra-high voltage transmission projects is the main development approach for renewable energy bases in western and northern China.Nonetheless,solving the problems of high carbon dioxide emission,carbon dioxide capture,and the utilization of thermal power is still necessary.Based on power-to-hydrogen,powerto-methanol,and oxygen-enriched combustion power generation technologies,this article proposes a power-to-hydrogen-andmethanol model based on the collaborative optimization of energy flow and material flow,which is expected to simultaneously solve the problems of renewable energy accommodation and low-carbon transformation of thermal power.Models with different ways of linking power to hydrogen and methanol are established,and an 8760-hour-time-series operation simulation is incorporated into the planning model.A case study is then conducted on renewable energy bases in the deserts of western and northern China.The results show that the power-to-hydrogen-and-methanol model based on the collaborative optimization of energy flow and material flow can greatly reduce the demand for hydrogen storage and energy storage,reduce the cost of carbon capture,make full use of by-product oxygen and captured carbon dioxide,and produce high-value chemical raw materials,thus exhibiting significant economic advantages.
文摘On the basis of the theoretical analysis of a single-machine infinite-bus （SMIB）, using the modified linearized Phil- lips-Heffron model installed with unified power flow controller （UPFC）, the potential of the UPFC supplementary controller to enhance the dynamic stability of a power system is evaluated by measuring the electromechanical controllability through singular value decomposition （SVD） analysis. This controller is tuned to simultaneously shift the undamped electromeehanical modes to a prescribed zone in the s-plane. The problem of robust UPFC based damping controller is formulated as an optimization problem according to the eigenvalue-based multi-objective function comprising the damping factor, and the damping ratio of the undamped electromechanical modes to be solved using gravitational search algorithm （GSA） that has a strong ability to find the most optimistic results. The different loading conditions are simulated on a SMIB system and the rotor speed deviation, internal voltage deviation, DC voltage deviation and electrical power deviation responses are studied with the effect of this flexible AC transmission systems （FACTS） controller. The results reveal that the tuned GSA based UPFC controller using the proposed multi-objective function has an excellent capability in damping power system with low frequency oscillations and greatly enhances the dynamic stability of the power systems.
基金Science and Technology Project of State Grid Corporation of China(No.SGGSKY00FJJS1800140)。
文摘For the low utilization rate of photovoltaic power generation,taking a new energy power system constisting of concentrating solar power(CSP),photovoltaic power(PP)and battery energy storage system as an example,a multi-objective optimization scheduling strategy considering energy storage participation is proposed.Firstly,the new energy power system model is established,and the PP scenario generation and reduction frame based on the autoregressive moving average model and Kantorovich-distance is proposed.Then,based on the optimization goal of the system operation cost minimization and the PP output power consumption maximization,the multi-objective optimization scheduling model is established.Finally,the simulation results show that introducing energy storage into the system can effectively reduce the system operation cost and improve the utilization efficiency of PP.
基金This work was supported of National Natural Science Foundation of China Fund(No.52306033)State Key Laboratory of Engines Fund(No.SKLE-K2022-07)the Jiangxi Provincial Postgraduate Innovation Special Fund(No.YC2022-s513).
文摘The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.
基金supported by the National Key R&D Program of China (2016YFC0402209)the Major Research Plan of the National Natural Science Foundation of China (No. 91647114)
文摘Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model. This model is aimed at maximizing the total system power generation and the minimum ten-day joint output. To effectively optimize the multi-objective model, a new algorithm named non-dominated sorting culture differential evolution algorithm(NSCDE) is proposed. The feasibility of NSCDE was verified through several well-known benchmark problems. It was then applied to the Jinping Wind-Solar-Hydro complementary power generation system. The results demonstrate that NSCDE can provide decision makers a series of optimized scheduling schemes.
基金Projects(51005115, 51005248) supported by the National Natural Science Foundation of ChinaProject(SKLMT-KFKT-201105)supported by the Visiting Scholar Foundation of State Key Laboratory of Mechanical Transmission in Chongqing University, ChinaProject(QC201101) supported by Visiting Scholar Foundation of the Automobile Engineering Key Laboratory of Jiangsu Province, China
文摘The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-objective genetic algorithm (GA) was designed. Based on the model of system, the quantitative formula of the road feel, sensitivity, and operation stability of the steering were induced. Considering the road feel and sensitivity of steering as optimization objectives, and the operation stability of steering as constraint, the multi-objective GA was proposed and the system parameters were optimized. The simulation results show that the system optimized by multi-objective genetic algorithm has better road feel, steering sensibility and steering stability. The energy of steering road feel after optimization is 1.44 times larger than the one before optimization, and the energy of portability after optimization is 0.4 times larger than the one before optimization. The ground test was conducted in order to verify the feasibility of simulation results, and it is shown that the pure electric bus equipped with the recirculating ball-type EPS system can provide better road feel and better steering portability for the drivers, thus the optimization methods can provide a theoretical basis for the design and optimization of the recirculating ball-type EPS system.
文摘Increasing demand for water from all sectors presents a challenge for policy makers to improve water allocation policies for storage reservoirs. In addition, there are many other organisms and species present in river waters that also require water for their survival. Due to the lack of awareness many times the minimum required quantity and quality of water for river ecosystem is not made available at downstream of storage reservoirs. So, a sustainable approach is required in reservoir operations to maintain the river ecosystem with environmental flow while meeting the other demands. Multi-objective, multi-reservoir operation model developed with Python programming using Fuzzy Linear Programing method incorporating environmental flow requirement of river is presented in this paper. Objective of maximization of irrigation release is considered for first run. In second run maximization of releases for hydropower generation is considered as objective. Further both objectives are fuzzified by incorporating linear membership function and solved to maximize fuzzified objective function simultaneously by maximizing satisfaction level indicator (λ). The optimal reservoir operation policy is presented considering constraints including Irrigation release, Turbine release, Reservoir storage, Environmental flow release and hydrologic continuity. Model applied for multi-reservoir system consists of four reservoirs, i.e., Jayakwadi Stage-I Reservoir (R1), Jayakwadi Stage-II Reservoir (R2), Yeldari Reservoir (R3), Siddheshwar Reservoir (R4) in Godavari River sub-basin from Marathwada region of Maharashtra State, India.
文摘This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal allocation and sizing of multiple PV-DG units to minimize power losses using a probabilistic PV model and time-series power flow analysis. Addressing the uncertainties in PV output due to weather variability and diurnal cycles is critical. A probabilistic assessment offers a more robust analysis of DG integration’s impact on the grid, potentially leading to more reliable system planning. The presented approach employs a genetic algorithm (GA) and a determined PV output profile and probabilistic PV generation profile based on experimental measurements for one year of solar radiation in Cairo, Egypt. The proposed algorithms are validated using a co-simulation framework that integrates MATLAB and OpenDSS, enabling analysis on a 33-bus test system. This framework can act as a guideline for creating other co-simulation algorithms to enhance computing platforms for contemporary modern distribution systems within smart grids concept. The paper presents comparisons with previous research studies and various interesting findings such as the considered hours for developing the probabilistic model presents different results.
文摘Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constrained Optimal Power Flow(SCOPF)using the Line Outage Distribution Factor(LODF)to enhance resilience in a renewable energy-integrated microgrid.The research examines a 30-bus system with 14 generators and an 8669 MW load demand,optimizing both single-objective and multi-objective scenarios.The single-objective opti-mization achieves a total generation cost of$47,738,while the multi-objective approach reduces costs to$47,614 and minimizes battery power output to 165.02 kW.Under contingency conditions,failures in transmission lines 1,22,and 35 lead to complete power loss in those lines,requiring a redistribution strategy.Implementing SCOPF mitigates these disruptions by adjusting power flows,ensuring no line exceeds its capacity.Specifically,in contingency 1,power in channel 4 is reduced from 59 to 32 kW,while overall load shedding is minimized to 0.278 MW.These results demonstrate the effectiveness of SCOPF in maintaining stability and reducing economic losses.Unlike prior studies,this work integrates LODF into SCOPF for large-scale microgrid applications,offering a computationally efficient contingency management framework that enhances grid resilience and supports renewable energy adoption.
文摘Due to the climate-dependent nature of renewable energy sources(RESs),solving the optimal power flow(OPF)problem in power systems that integrate RESs,such as photovoltaic(PV)units and wind turbines(WTs),remains a significant challenge.To address this problem,this study presents an effective framework that incorporates solar and wind power generation.To manage the nonconvex and nonlinear characteristics of the OPF problem,a modified physics-inspired algorithm termed the Enhanced Coulomb’s and Franklin’s laws Algorithm(ECFA),is deployed.In the proposed OPF model,the power generated from RESs is considered a dependent variable,while voltages at buses equipped with RESs serve as decision variables.Real-time data on solar irradiation and wind speed are used to model the power outputs of PV units and WTs,respectively.Although the Coulomb’s and Franklin’s law algorithm(CFA)offers some advantages,it underperforms on complex optimization tasks compared to SSA,BA,SCA,ABC,and CFA.The enhanced version of the CFA improves the search process across the feasible space by incorporating diverse interaction methods and enhancing exploitation capabilities.The performance of the proposed ECFA is assessed through comprehensive comparisons with state-of-the-art methods for solving the OPF problem.
基金supported in part by the Department of Navy award N00014-24-1-2287 and N00014-23-1-2124。
文摘Modern shipboard microgrids(SMGs)incorporating distributed energy resources(DERs)enhance energy resilience and reduce carbon emissions.However,the hierarchical control schemes of DERs bring challenges to the traditional power flow methods.This paper devises a generalized three-phase power flow approach for SMGs that integrate hierarchically controlled DERs.The main contributions include:(1)a droop-controlled three-phase Newton power flow algorithm that automatically incorporates the droop characteristics of DERs;(2)a secondary-controlled three-phase power flow method for power sharing and voltage regulation;and(3)modified Jacobian matrices to incorporate various hierarchical control modes.Numerical results demonstrate the effectiveness of the devised approach in both balanced and unbalanced three-phase hierarchically controlled SMG systems with arbitrary config-urations.
基金Supported by the National Key R&D Program of China project (2017YFC0805309)the National Natural Science Foundation of China (60602020)。
文摘To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and environmental issues of ships,this study aims to improve the transportation efficiency of ships by providing a ship route induction method.Ship data from a certain bay during a defined period are collected,and an improved backpropagation neural network algorithm is used to forecast ship traffic.On the basis of the forecasted data and ship route induction objectives,dynamic programming of ship routes is performed.Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55%compared with statically induced routes.This method has promising engineering applications in improving ship navigation efficiency,promoting energy conservation,and reducing emissions.
