Architectural plan generation via pix2pix series algorithms faces dual challenges:the absence of domain-specific evaluation metrics and a lack of systematic insights into the joint impact of training configurations.To...Architectural plan generation via pix2pix series algorithms faces dual challenges:the absence of domain-specific evaluation metrics and a lack of systematic insights into the joint impact of training configurations.To address the limitations of pix2pix-based models adaptation to architectural design,we designed a training regimen involving 12 experiments with varying training set sizes,dataset characteristics,and algorithms.These experiments utilized our self-built,high-quality,large-volume synthetic dataset of architectural-like plans.By saving intermediate models,we obtained 240 generative models for evaluation on a fixed test set.To quantify model performance,we developed a dual-aspect evaluation method that assesses predictions through pixel similarity(principle adherence)and segmentation line continuity(vectorization quality).Analysis revealed algorithm choice and training set size as primary factors,with larger sets enhancing the benefits of high-resolution and enhancedannotation datasets.The optimal model achieved high-quality predictions,demonstrating strict adherence to predefined principles(0.81 similarity)and effective vectorization(0.86 segmentation line continuity).Testing on 7695 samples of varying complexity confirmed the model’s robustness,strong generative capability,and controlled innovation within defined principles,validated through 3D model conversion.This work provides a domain-adapted framework for training and evaluating pix2pix-based architectural generators,bridging generative research and practical applications.展开更多
With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and ...With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.展开更多
Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality.The power sector accounts for approximately 40%of China’s total CO_(2) emissions.Accor...Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality.The power sector accounts for approximately 40%of China’s total CO_(2) emissions.Accordingly,collaborative optimization in power generation expansion planning(GEP)simultaneously considering economic,environmental,and technological concerns as carbon emissions is necessary.This paper proposes a collaborative mixedinteger linear programming optimization approach for GEP.This minimizes the power system’s operating cost to resolve emission concerns considering energy development strategies,flexible generation,and resource limitations constraints.This research further analyzes the advantages and disadvantages of current GEP techniques.Results show that the main determinants of new investment decisions are carbon emissions,reserve margins,resource availability,fuel consumption,and fuel price.The proposed optimization method is simulated and validated based on China’s power system data.Finally,this study provides policy recommendations on the flexible management of traditional power sources,the market-oriented mechanism of new energy sources,and the integration of new technology to support the attainment of carbon-neutral targets in the current energy transition process.展开更多
As renewable energy resources increasingly penetrate the electric grid,the inertia capability of power systems has become a developmental bottleneck.Nevertheless,the importance of primary frequency response(PFR)when m...As renewable energy resources increasingly penetrate the electric grid,the inertia capability of power systems has become a developmental bottleneck.Nevertheless,the importance of primary frequency response(PFR)when making generation-expansion plans has been largely ignored.In this paper,we propose an optimal generation-expansion planning framework for wind and thermal power plants that takes PFR into account.The model is based on the frequency equivalent model.It includes investment,startup/shutdown,and typical operating costs for both thermal and renewable generators.The linearization constraints of PFR are derived theoretically.Case studies based on the modified IEEE 39-bus system demonstrate the efficiency and effectiveness of the proposed method.Compared with methods that ignore PFR,the method proposed in this paper can effectively reduce the cost of the entire planning and operation cycle,improving the accommodation rate of renewable energy.展开更多
Power system equipment outages are one of the most important factors affecting the reliability and economy of power systems.It is crucial to consider the reliability of the planning problems.In this paper,a generation...Power system equipment outages are one of the most important factors affecting the reliability and economy of power systems.It is crucial to consider the reliability of the planning problems.In this paper,a generation expansion planning(GEP)model is proposed,in which the candidate generating units and energy storage systems(ESSs)are simultaneously planned by minimizing the cost incurred on investment,operation,reserve,and reliability.The reliability cost is computed by multiplying the value of lost load(VOLL)with the expected energy not supplied(EENS),and this model makes a compromise between economy and reliability.Because the computation of EENS makes the major computation impediment of the entire model,a new efficient linear EENS formulation is proposed and applied in a multi-step GEP model.By doing so,the computation efficiency is significantly improved,and the solution accuracy is still desirable.The proposed GEP model is illustrated using the IEEE-RTS system to validate the effectiveness and superiority of the new model.展开更多
A generation planning model of six main power grids in China is developed to evaluate the potential of advanced power generation technologies into the Chinese power system as CDM （clean development mechanism）. It is...A generation planning model of six main power grids in China is developed to evaluate the potential of advanced power generation technologies into the Chinese power system as CDM （clean development mechanism）. It is investigated how delivered coal price, on-grid power price, and environmental protection may influence the potential of advanced thermal power generation as CDM projects. One finding from the baseline analysis is that coal price, on-grid power price, and environmental protection policy have only a small significance to the grid-wide specific CO2 emissions of thermal power generation up to the year 2026, while the best thermal generation mix is influenced largely by environmental protection policy. And it is found that not only the price of CER （certified emission reduction） and the length of crediting period but also on-grid power price and the reduction of air pollutants in the baseline have a significant influence on the potential of the CDM activities.展开更多
With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,...With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,methods for quantifying and assessing carbon emissions and operational risks are lacking.It results in excessive carbon emissions and frequent load-shedding on some days,although meeting annual carbon emission reduction targets.First,in response to the above problems,carbon emission and power balance risk assessment indicators and assessment methods,were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios,considering power supply regulation and renewable energy fluctuation characteristics.Secondly,building on traditional two-tier models for low-carbon power planning,including investment decisions and operational simulations,considering carbon emissions and power balance risks in lower-tier operational simulations,a two-tier rolling model for thermal power retrofit and generation expansion planning was established.The model includes an investment tier and operation assessment tier and makes year-by-year decisions on the number of thermal power units to be retrofitted and the type and capacity of units to be commissioned.Finally,the rationality and validity of the model were verified through an example analysis,a small-scale power supply system in a certain region is taken as an example.The model can significantly reduce the number of days of carbon emissions risk and ensure that the power balance risk is within the safe limit.展开更多
The generation expansion planning is one of complex mixed-integer optimization problems, which involves a large number of continuous or discrete decision variables and constraints. In this paper, an interior point wit...The generation expansion planning is one of complex mixed-integer optimization problems, which involves a large number of continuous or discrete decision variables and constraints. In this paper, an interior point with cutting plane （IP/CP） method is proposed to solve the mixed-integer optimization problem of the electrical power generation expansion planning. The IP/CP method could improve the overall efficiency of the solution and reduce the computational time. Proposed method is combined with the Bender＇s decomposition technique in order to decompose the generation expansion problem into a master investment problem and a slave operational problem. The numerical example is presented to compare with the effectiveness of the proposed algorithm.展开更多
This paper develops a high time-resolution optimal power generation mix model in its time resolution of 10 minutes on 365 days by linear programming technique. The model allows us to analyse the massive deployment of ...This paper develops a high time-resolution optimal power generation mix model in its time resolution of 10 minutes on 365 days by linear programming technique. The model allows us to analyse the massive deployment of photovoltaic system and wind power generation in power system explicitly considering those short-term output variation. PV （photovoltaic） and wind output are estimated, employing meteorological database. Simulation results reveal that variable fluctuation derived from a high penetration level of those renewables is controlled by quick load following operation of natural gas combined cycle power plant, pumped-storage hydro power, stationary NAS （sodium and sulfur） battery and the output suppression control of PV and wind. It additionally turns out that the operational configuration of those technologies for the renewable variability differs significantly depending on those renewable output variations in each season and solving the seasonal electricity imbalance as well as the daily imbalance is important if variable renewables are massively deployed.展开更多
Residential energy use accounts for a substantial portion of global consumption,making its reduction critical for sustainable architectural design.However,existing generative models for residential layouts often overl...Residential energy use accounts for a substantial portion of global consumption,making its reduction critical for sustainable architectural design.However,existing generative models for residential layouts often overlook energy performance,resulting in inefficient designs and costly revisions.To address this,we propose an AI-based framework that integrates generative model,energy prediction,and evolutionary optimization.Our framework comprises three components:(1)Energy prediction:a deep learning model trained on energy simulations of 71,125 floor plans from the RPLAN dataset predicts monthly energy consumption across five categories with over 99%accuracy.(2)Generative model:a diffusion-based layout generator uses room blocks and residential contours to create diverse,high-quality floor plans under spatial constraints.(3)Optimization:a genetic algorithm iteratively refines floor plans by selecting low-energy solutions and regenerating new options,guided by the predictive model.Experiments show that our method reduces energy consumption by 17.5%compared to the best baseline model under identical conditions,demonstrating its effectiveness in reducing residential energy use.Our key contributions include the use of room blocks as chromosomes for layout evolution,and the integration of AI-based prediction and generation for energy-aware residential design.展开更多
Large-scale renewable energy integration decreases the system inertia and restricts frequency regulation. To maintain the frequency stability, allocating adequate frequency-support sources poses a critical challenge t...Large-scale renewable energy integration decreases the system inertia and restricts frequency regulation. To maintain the frequency stability, allocating adequate frequency-support sources poses a critical challenge to planners. In this context, we propose a frequency-constrained coordination planning model of thermal units, wind farms, and battery energy storage systems (BESSs) to provide satisfactory frequency supports. Firstly, a modified multi-machine system frequency response (MSFR) model that accounts for the dynamic responses from both synchronous generators and grid-connected inverters is constructed with preset power-headroom. Secondly, the rate-of-change-of-frequency (ROCOF) and frequency response power are deduced to construct frequency constraints. A data-driven piecewise linearization (DDPWL) method based on hyperplane fitting and data classification is applied to linearize the highly nonlinear frequency response power. Thirdly, frequency constraints are inserted into our planning model, while the unit commitment based on the coordinated operation of the thermal-hydro-wind-BESS hybrid system is implemented. At last, the proposed model is applied to the IEEE RTS-79 test system. The results demonstrate the effectiveness of our co-planning model to keep the frequency stability.展开更多
Electric vehicles(EV)are proposed as a measure to reduce greenhouse gas emissions in transport and support increased wind power penetration across modern power systems.Optimal benefits can only be achieved,if EVs are ...Electric vehicles(EV)are proposed as a measure to reduce greenhouse gas emissions in transport and support increased wind power penetration across modern power systems.Optimal benefits can only be achieved,if EVs are deployed effectively,so that the exhaust emissions are not substituted by additional emissions in the electricity sector,which can be implemented using Smart Grid controls.This research presents the results of an EV roll-out in the all island grid(AIG)in Ireland using the long term generation expansion planning model called the Wien Automatic System Planning IV(WASP-IV)tool to measure carbon dioxide emissions and changes in total energy.The model incorporates all generators and operational requirements while meeting environmental emissions,fuel availability and generator operational and maintenance constraints to optimize economic dispatch and unit commitment power dispatch.In the study three distinct scenarios are investigated base case,peak and off-peak charging to simulate the impacts of EV’s in the AIG up to 2025.展开更多
Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reli...Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reliability value of a photovoltaic(PV)energy system with a battery storage system(BSS)by considering the probability of grid outages causing household blackouts.Considering this reliability value,which is the economic profit and capital cost of PV+BSS,a simple formula is derived to calculate the optimal planning strategy.This strategy can provide household-level customers with a simple and straightforward expression for invested PV+BSS capacity.Case studies on 600 households located in eight zones of the US for the period of 2006 to 2015 demonstrate that adding the reliability value to economic profit allows households to invest in a larger PV+BSS and avoid loss of load caused by blackouts.Owing to the differences in blackout hours,households from the 8 zones express distinct willingness to install PV+BSS.The greater the probability of blackout,the greater revenue that household can get from the PV+BSS.The simulation example shows that the planning strategy obtained by proposed model has good economy in the actual operation and able to reduce the economic risk of power failure of the household users.This model can provide household with an easy and straightforward investment strategy of PV+BSS capacity.展开更多
To address the planning issue of offshore oil-field power systems, an integrated generation-transmission expansion planning model is proposed. The outage cost is considered and the genetic Tabu hybrid algorithm(GTHA)i...To address the planning issue of offshore oil-field power systems, an integrated generation-transmission expansion planning model is proposed. The outage cost is considered and the genetic Tabu hybrid algorithm(GTHA)is developed to find the optimal solution. With the proposed integrated model, the planning of generators and transmission lines can be worked out simultaneously,which outweighs the disadvantages of separate planning,for instance, unable to consider the influence of power grid during the planning of generation, or insufficient to plan the transmission system without enough information of generation. The integrated planning model takes into account both the outage cost and the shipping cost, which makes the model more practical for offshore oilfield power systems. The planning problem formulated based on the proposed model is a mixed integer nonlinear programming problem of very high computational complexity, which is difficult to solve by regular mathematical methods. A comprehensive optimization method based on GTHA is also developed to search the best solution efficiently.Finally, a case study on the planning of a 50-bus offshore oilfield power system is conducted, and the obtained results fully demonstrate the effectiveness of the presented model and method.展开更多
Demand response is becoming a promising field of study in operation and planning of restructured power systems. More attention has recently been paid to demand response programs. Customers can contribute to the operat...Demand response is becoming a promising field of study in operation and planning of restructured power systems. More attention has recently been paid to demand response programs. Customers can contribute to the operation of power systems by deployment demand response. The growth of customers' participation in such programs may affect the planning of power systems. Therefore, it seems necessary to consider the effects of demand response in planning approaches. In this paper, the impact of demand responsiveness on decision making in generation expansion planning is modeled. Avoidance or deferment in installation of new generating units is comprehensively investigated and evaluated by introducing a new simple index. The effects of demand responsiveness are studied from the points of view of both customers and generation companies. The proposed model has been applied to a modified IEEE 30-bus system and the results of the study are discussed. Simulation results show that reducing just 3% of the customers' demand(due to price elasticity) may result in a benefit of about 10% for customers in the long term.展开更多
An electricity generation planning model of the six major Chinese power grids was developed based on the General Algebraic Modeling System to evaluate and analyze the CDM （clean development mechanism）, including con...An electricity generation planning model of the six major Chinese power grids was developed based on the General Algebraic Modeling System to evaluate and analyze the CDM （clean development mechanism）, including consideration of the environmental co-benefits of reductions in air pollutants （SO~, NO~ and particulate matter） achieved by advanced electricity generation technologies incorporating CCS （carbon capture and storage）. An objective function was developed that included revenue from sales of electric power, total system cost, the cost of CO2 transport and storage, and emissions reduction co-benefits for SOx, NO~, and particulate matter. The objective function was minimized using an optimization model. We also developed a method for evaluating and analyzing the potential for transferring advanced power generation technologies into the Chinese power system through the CDM. We found that： （1） thermal power generation is predominant in the Chinese electricity system and will remain so for a long time; （2） advanced thermal plants are being installed as a result of the CDM, which contribute to decreasing emissions of CO2 and other air pollutants; and （3） CCS projects have significant potential to reduce substantial and sustained CO2 emissions from the Chinese power and industrial sectors.展开更多
Variable renewable energy(VRE)integrated via non-synchronous inverters exhibits low inertia and fluctuating output,posing substantial frequency security challenges for future power systems.When frequency security cons...Variable renewable energy(VRE)integrated via non-synchronous inverters exhibits low inertia and fluctuating output,posing substantial frequency security challenges for future power systems.When frequency security constraints are omitted from generation planning,the resulting low-inertia generation portfolios often fail to meet critical frequency requirements.To address this issue,this paper proposes a novel frequency security constrained generation planning(FSCGP)model that leverages the frequency support potential of diverse power sources,including conventional thermal generators(CTGs),VRE units,concentrating solar power(CSP)units,and energy storage systems(ESSs).A physics-data hybrid-driven method is introduced to formulate frequency security constraints,enabling accurate representation of diverse frequency regulation characteristics,particularly the fast frequency support capabilities of inverter-based generators(IBGs).To further enhance the computational efficiency,several acceleration techniques are incorporated into the proposed FSCGP model.Case studies based on a modified IEEE RTS-79 system validate the effectiveness of the proposed FSCGP model.The numerical results identify the primary contributors to frequency security under different renewable energy penetration(REP)levels and demonstrate the cost-effectiveness of coordinating various frequency support sources,especially CSP units and IBGs,in mitigating challenges in low-inertia grids.展开更多
This paper proposes a new method for the planning of stand-alone microgrids.By means of clustering techniques,possible operating scenarios are obtained considering the daily patterns of wind and load profiles.Then,an ...This paper proposes a new method for the planning of stand-alone microgrids.By means of clustering techniques,possible operating scenarios are obtained considering the daily patterns of wind and load profiles.Then,an approximate analytical model for reliability evaluation of battery energy storage system is developed in terms of the diverse scenarios,along with multistate models for wind energy system and diesel generating system.An optimal planning model is further illustrated based on the scenarios and the reliability models,with the objective of minimizing the present values of the costs occurring within the project lifetime,and with the constraints of system operation and reliability.Finally,a typical stand-alone microgrid is studied to verify the efficiency of the proposed method.展开更多
With an increasing integration of intermittent distributed energy resources(DERs),the consequent voltage excursion and thermal overloading issues limit the self-sufficiency of distribution networks(DNs).The concept of...With an increasing integration of intermittent distributed energy resources(DERs),the consequent voltage excursion and thermal overloading issues limit the self-sufficiency of distribution networks(DNs).The concept of soft open point(SOP)has been proposed as a promising solution to improve the hosting capacity of DNs.In this paper,considering the ability of building thermal storage(BTS)to increase the penetration of renewable energy in DNs,we provide an optimal planning framework for SOP and DER.The optimal planning model is aimed at minimizing the investment and operational costs while respecting various constraints,including the self-sufficiency requirement of the DN,SOP,building thermal storage capacity and DER operations,etc.A steady-state SOP model is formulated and linearized to be incorporated into the planning framework.To make full use of the BTS flexibility provided by ubiquitous buildings,a differential equation model for building thermal dynamics is formulated.A hybrid stochastic/robust optimization approach is adopted to depict the uncertainties in renewable energy and market prices.IEEE 33-bus feeder and a realistic DN in the metropolitan area of Caracas are tested to validate the effectiveness of the proposed framework and method.Case studies show that SOP/BTS plays a complementary and coordinated coupling role in the thermo-electric system,thereby effectively improving the hosting capacity and self-sufficiency of DNs.展开更多
Concerning the integration of large-scale wind power,an integrated model of generation and transmission expansion planning is proposed based on the assessment of the value of steady state and dynamic security.In the a...Concerning the integration of large-scale wind power,an integrated model of generation and transmission expansion planning is proposed based on the assessment of the value of steady state and dynamic security.In the assessment of security value,the unit commitment simulation based on the predicted hourly load and wind power output data in the planning horizon is used to evaluate the costs of preventive control,emergency control and social losses due to the uncertainty of load and wind power.The cost of preventive control consists of the fuel cost of power generation,the environmental cost and the load shedding cost.This not only provides a systematic method of security assessment of power system expansion planning schemes,but also broadens the perspective of power system planning from the technology and economic assessment to the measure of the whole social value.In the assessment process,the preventive control and emergency control of cascading failures are also presented,which provides a convincing tool for cascading failure analysis of planning schemes and makes the security assessment more comprehensive and reasonable.The proposed model and method have been demonstrated by the assessment of two power system planning schemes on the New England 10-genarator 39-bus System.The importance of considering the value of security and simulating hourly system operation for the planning horizon,in expansion planning of power system with integration of large-scale wind power,has been confirmed.展开更多
文摘Architectural plan generation via pix2pix series algorithms faces dual challenges:the absence of domain-specific evaluation metrics and a lack of systematic insights into the joint impact of training configurations.To address the limitations of pix2pix-based models adaptation to architectural design,we designed a training regimen involving 12 experiments with varying training set sizes,dataset characteristics,and algorithms.These experiments utilized our self-built,high-quality,large-volume synthetic dataset of architectural-like plans.By saving intermediate models,we obtained 240 generative models for evaluation on a fixed test set.To quantify model performance,we developed a dual-aspect evaluation method that assesses predictions through pixel similarity(principle adherence)and segmentation line continuity(vectorization quality).Analysis revealed algorithm choice and training set size as primary factors,with larger sets enhancing the benefits of high-resolution and enhancedannotation datasets.The optimal model achieved high-quality predictions,demonstrating strict adherence to predefined principles(0.81 similarity)and effective vectorization(0.86 segmentation line continuity).Testing on 7695 samples of varying complexity confirmed the model’s robustness,strong generative capability,and controlled innovation within defined principles,validated through 3D model conversion.This work provides a domain-adapted framework for training and evaluating pix2pix-based architectural generators,bridging generative research and practical applications.
基金supported partly by the National Key R&D Program of China(2018YFA0702200)the Science and Technology Project of State Grid Shandong Electric Power Company(520604190002)。
文摘With the development of carbon electricity,achieving a low-carbon economy has become a prevailing and inevitable trend.Improving low-carbon expansion generation planning is critical for carbon emission mitigation and a lowcarbon economy.In this paper,a two-layer low-carbon expansion generation planning approach considering the uncertainty of renewable energy at multiple time scales is proposed.First,renewable energy sequences considering the uncertainty in multiple time scales are generated based on the Copula function and the probability distribution of renewable energy.Second,a two-layer generation planning model considering carbon trading and carbon capture technology is established.Specifically,the upper layer model optimizes the investment decision considering the uncertainty at a monthly scale,and the lower layer one optimizes the scheduling considering the peak shaving at an hourly scale and the flexibility at a 15-minute scale.Finally,the results of different influence factors on low-carbon generation expansion planning are compared in a provincial power grid,which demonstrate the effectiveness of the proposed model.
基金supported by the Natural Science Foundation of Shandong Province (No.ZR2019MEE078)Education and Teaching Reform Research Project of Shandong University (“Development of an experiment platform to support the intelligent energy courses”)。
文摘Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality.The power sector accounts for approximately 40%of China’s total CO_(2) emissions.Accordingly,collaborative optimization in power generation expansion planning(GEP)simultaneously considering economic,environmental,and technological concerns as carbon emissions is necessary.This paper proposes a collaborative mixedinteger linear programming optimization approach for GEP.This minimizes the power system’s operating cost to resolve emission concerns considering energy development strategies,flexible generation,and resource limitations constraints.This research further analyzes the advantages and disadvantages of current GEP techniques.Results show that the main determinants of new investment decisions are carbon emissions,reserve margins,resource availability,fuel consumption,and fuel price.The proposed optimization method is simulated and validated based on China’s power system data.Finally,this study provides policy recommendations on the flexible management of traditional power sources,the market-oriented mechanism of new energy sources,and the integration of new technology to support the attainment of carbon-neutral targets in the current energy transition process.
基金supported in part by the National Natural Science Foundation of China(No.U1966204,51907064).
文摘As renewable energy resources increasingly penetrate the electric grid,the inertia capability of power systems has become a developmental bottleneck.Nevertheless,the importance of primary frequency response(PFR)when making generation-expansion plans has been largely ignored.In this paper,we propose an optimal generation-expansion planning framework for wind and thermal power plants that takes PFR into account.The model is based on the frequency equivalent model.It includes investment,startup/shutdown,and typical operating costs for both thermal and renewable generators.The linearization constraints of PFR are derived theoretically.Case studies based on the modified IEEE 39-bus system demonstrate the efficiency and effectiveness of the proposed method.Compared with methods that ignore PFR,the method proposed in this paper can effectively reduce the cost of the entire planning and operation cycle,improving the accommodation rate of renewable energy.
基金supported by project of State Grid Shandong Electric Power Company(52062520000Q)the National Key Research and Development Program of China(2019YFE0118400)。
文摘Power system equipment outages are one of the most important factors affecting the reliability and economy of power systems.It is crucial to consider the reliability of the planning problems.In this paper,a generation expansion planning(GEP)model is proposed,in which the candidate generating units and energy storage systems(ESSs)are simultaneously planned by minimizing the cost incurred on investment,operation,reserve,and reliability.The reliability cost is computed by multiplying the value of lost load(VOLL)with the expected energy not supplied(EENS),and this model makes a compromise between economy and reliability.Because the computation of EENS makes the major computation impediment of the entire model,a new efficient linear EENS formulation is proposed and applied in a multi-step GEP model.By doing so,the computation efficiency is significantly improved,and the solution accuracy is still desirable.The proposed GEP model is illustrated using the IEEE-RTS system to validate the effectiveness and superiority of the new model.
文摘A generation planning model of six main power grids in China is developed to evaluate the potential of advanced power generation technologies into the Chinese power system as CDM （clean development mechanism）. It is investigated how delivered coal price, on-grid power price, and environmental protection may influence the potential of advanced thermal power generation as CDM projects. One finding from the baseline analysis is that coal price, on-grid power price, and environmental protection policy have only a small significance to the grid-wide specific CO2 emissions of thermal power generation up to the year 2026, while the best thermal generation mix is influenced largely by environmental protection policy. And it is found that not only the price of CER （certified emission reduction） and the length of crediting period but also on-grid power price and the reduction of air pollutants in the baseline have a significant influence on the potential of the CDM activities.
基金supported by Science and Technology Project of State Grid Anhui Electric Power Co.,Ltd. (No.B6120922000A).
文摘With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,methods for quantifying and assessing carbon emissions and operational risks are lacking.It results in excessive carbon emissions and frequent load-shedding on some days,although meeting annual carbon emission reduction targets.First,in response to the above problems,carbon emission and power balance risk assessment indicators and assessment methods,were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios,considering power supply regulation and renewable energy fluctuation characteristics.Secondly,building on traditional two-tier models for low-carbon power planning,including investment decisions and operational simulations,considering carbon emissions and power balance risks in lower-tier operational simulations,a two-tier rolling model for thermal power retrofit and generation expansion planning was established.The model includes an investment tier and operation assessment tier and makes year-by-year decisions on the number of thermal power units to be retrofitted and the type and capacity of units to be commissioned.Finally,the rationality and validity of the model were verified through an example analysis,a small-scale power supply system in a certain region is taken as an example.The model can significantly reduce the number of days of carbon emissions risk and ensure that the power balance risk is within the safe limit.
文摘The generation expansion planning is one of complex mixed-integer optimization problems, which involves a large number of continuous or discrete decision variables and constraints. In this paper, an interior point with cutting plane （IP/CP） method is proposed to solve the mixed-integer optimization problem of the electrical power generation expansion planning. The IP/CP method could improve the overall efficiency of the solution and reduce the computational time. Proposed method is combined with the Bender＇s decomposition technique in order to decompose the generation expansion problem into a master investment problem and a slave operational problem. The numerical example is presented to compare with the effectiveness of the proposed algorithm.
文摘This paper develops a high time-resolution optimal power generation mix model in its time resolution of 10 minutes on 365 days by linear programming technique. The model allows us to analyse the massive deployment of photovoltaic system and wind power generation in power system explicitly considering those short-term output variation. PV （photovoltaic） and wind output are estimated, employing meteorological database. Simulation results reveal that variable fluctuation derived from a high penetration level of those renewables is controlled by quick load following operation of natural gas combined cycle power plant, pumped-storage hydro power, stationary NAS （sodium and sulfur） battery and the output suppression control of PV and wind. It additionally turns out that the operational configuration of those technologies for the renewable variability differs significantly depending on those renewable output variations in each season and solving the seasonal electricity imbalance as well as the daily imbalance is important if variable renewables are massively deployed.
基金supported by the Guangdong Basic and Applied Basic Research Foundation(2024A1515012595)Department of Education of Guangdong Province(2023ZDZX4078)Shenzhen Science and Technology Innovation Committee(WDZC20231129201240001).
文摘Residential energy use accounts for a substantial portion of global consumption,making its reduction critical for sustainable architectural design.However,existing generative models for residential layouts often overlook energy performance,resulting in inefficient designs and costly revisions.To address this,we propose an AI-based framework that integrates generative model,energy prediction,and evolutionary optimization.Our framework comprises three components:(1)Energy prediction:a deep learning model trained on energy simulations of 71,125 floor plans from the RPLAN dataset predicts monthly energy consumption across five categories with over 99%accuracy.(2)Generative model:a diffusion-based layout generator uses room blocks and residential contours to create diverse,high-quality floor plans under spatial constraints.(3)Optimization:a genetic algorithm iteratively refines floor plans by selecting low-energy solutions and regenerating new options,guided by the predictive model.Experiments show that our method reduces energy consumption by 17.5%compared to the best baseline model under identical conditions,demonstrating its effectiveness in reducing residential energy use.Our key contributions include the use of room blocks as chromosomes for layout evolution,and the integration of AI-based prediction and generation for energy-aware residential design.
基金This work was supported by the National Key R&D Program of China (No. 2016YFB0900100)the National Natural Science Foundation of China (No. 51807116).
文摘Large-scale renewable energy integration decreases the system inertia and restricts frequency regulation. To maintain the frequency stability, allocating adequate frequency-support sources poses a critical challenge to planners. In this context, we propose a frequency-constrained coordination planning model of thermal units, wind farms, and battery energy storage systems (BESSs) to provide satisfactory frequency supports. Firstly, a modified multi-machine system frequency response (MSFR) model that accounts for the dynamic responses from both synchronous generators and grid-connected inverters is constructed with preset power-headroom. Secondly, the rate-of-change-of-frequency (ROCOF) and frequency response power are deduced to construct frequency constraints. A data-driven piecewise linearization (DDPWL) method based on hyperplane fitting and data classification is applied to linearize the highly nonlinear frequency response power. Thirdly, frequency constraints are inserted into our planning model, while the unit commitment based on the coordinated operation of the thermal-hydro-wind-BESS hybrid system is implemented. At last, the proposed model is applied to the IEEE RTS-79 test system. The results demonstrate the effectiveness of our co-planning model to keep the frequency stability.
基金Dr Aoife FOLEY would like to thank UK Engineering and Physical Sciences Research Council(EPSRC)under grant EP/L001063/1the National Natural Science Foundation of China under grants 51361130153 and 61273040 and the Shanghai Rising Star programme 12QA1401100 for financial supporting this research.Dr Aoife FOLEY and Dr Brian O´GALLACHO´IR would also like to thank the Irish Environmental Protection Agency(EPA)Climate Change Research Programme under grant CCRP-09-FS-7-2.Dr FOLEY also acknowledges Dr Jianhui WANG,Vladimir KORITAROV,Dr Aidun BOTTERUD,Guenter CONZELMANN at Argonne National Energy Laboratory,Illinois,USA.
文摘Electric vehicles(EV)are proposed as a measure to reduce greenhouse gas emissions in transport and support increased wind power penetration across modern power systems.Optimal benefits can only be achieved,if EVs are deployed effectively,so that the exhaust emissions are not substituted by additional emissions in the electricity sector,which can be implemented using Smart Grid controls.This research presents the results of an EV roll-out in the all island grid(AIG)in Ireland using the long term generation expansion planning model called the Wien Automatic System Planning IV(WASP-IV)tool to measure carbon dioxide emissions and changes in total energy.The model incorporates all generators and operational requirements while meeting environmental emissions,fuel availability and generator operational and maintenance constraints to optimize economic dispatch and unit commitment power dispatch.In the study three distinct scenarios are investigated base case,peak and off-peak charging to simulate the impacts of EV’s in the AIG up to 2025.
基金supported by National Natural Science Foundation of China(Project 51907064)in part by China State Key Lab.of Power System(SKLD19KM09)in part by State Grid Corporation of China(1400202024222A-0-0-00)
文摘Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reliability value of a photovoltaic(PV)energy system with a battery storage system(BSS)by considering the probability of grid outages causing household blackouts.Considering this reliability value,which is the economic profit and capital cost of PV+BSS,a simple formula is derived to calculate the optimal planning strategy.This strategy can provide household-level customers with a simple and straightforward expression for invested PV+BSS capacity.Case studies on 600 households located in eight zones of the US for the period of 2006 to 2015 demonstrate that adding the reliability value to economic profit allows households to invest in a larger PV+BSS and avoid loss of load caused by blackouts.Owing to the differences in blackout hours,households from the 8 zones express distinct willingness to install PV+BSS.The greater the probability of blackout,the greater revenue that household can get from the PV+BSS.The simulation example shows that the planning strategy obtained by proposed model has good economy in the actual operation and able to reduce the economic risk of power failure of the household users.This model can provide household with an easy and straightforward investment strategy of PV+BSS capacity.
基金supported by National Natural Science Foundation of China (No. 51322701)National High Technology Research and Development Program of China (863 Program) (No. 2012AA050216)
文摘To address the planning issue of offshore oil-field power systems, an integrated generation-transmission expansion planning model is proposed. The outage cost is considered and the genetic Tabu hybrid algorithm(GTHA)is developed to find the optimal solution. With the proposed integrated model, the planning of generators and transmission lines can be worked out simultaneously,which outweighs the disadvantages of separate planning,for instance, unable to consider the influence of power grid during the planning of generation, or insufficient to plan the transmission system without enough information of generation. The integrated planning model takes into account both the outage cost and the shipping cost, which makes the model more practical for offshore oilfield power systems. The planning problem formulated based on the proposed model is a mixed integer nonlinear programming problem of very high computational complexity, which is difficult to solve by regular mathematical methods. A comprehensive optimization method based on GTHA is also developed to search the best solution efficiently.Finally, a case study on the planning of a 50-bus offshore oilfield power system is conducted, and the obtained results fully demonstrate the effectiveness of the presented model and method.
文摘Demand response is becoming a promising field of study in operation and planning of restructured power systems. More attention has recently been paid to demand response programs. Customers can contribute to the operation of power systems by deployment demand response. The growth of customers' participation in such programs may affect the planning of power systems. Therefore, it seems necessary to consider the effects of demand response in planning approaches. In this paper, the impact of demand responsiveness on decision making in generation expansion planning is modeled. Avoidance or deferment in installation of new generating units is comprehensively investigated and evaluated by introducing a new simple index. The effects of demand responsiveness are studied from the points of view of both customers and generation companies. The proposed model has been applied to a modified IEEE 30-bus system and the results of the study are discussed. Simulation results show that reducing just 3% of the customers' demand(due to price elasticity) may result in a benefit of about 10% for customers in the long term.
文摘An electricity generation planning model of the six major Chinese power grids was developed based on the General Algebraic Modeling System to evaluate and analyze the CDM （clean development mechanism）, including consideration of the environmental co-benefits of reductions in air pollutants （SO~, NO~ and particulate matter） achieved by advanced electricity generation technologies incorporating CCS （carbon capture and storage）. An objective function was developed that included revenue from sales of electric power, total system cost, the cost of CO2 transport and storage, and emissions reduction co-benefits for SOx, NO~, and particulate matter. The objective function was minimized using an optimization model. We also developed a method for evaluating and analyzing the potential for transferring advanced power generation technologies into the Chinese power system through the CDM. We found that： （1） thermal power generation is predominant in the Chinese electricity system and will remain so for a long time; （2） advanced thermal plants are being installed as a result of the CDM, which contribute to decreasing emissions of CO2 and other air pollutants; and （3） CCS projects have significant potential to reduce substantial and sustained CO2 emissions from the Chinese power and industrial sectors.
基金supported in part by Carbon Neutrality and Energy System Transformation Projectby National Natural Science Foundation of China(No.52177093)by Organized Research Support Program,Department of Electrical Engineering,Tsinghua University.
文摘Variable renewable energy(VRE)integrated via non-synchronous inverters exhibits low inertia and fluctuating output,posing substantial frequency security challenges for future power systems.When frequency security constraints are omitted from generation planning,the resulting low-inertia generation portfolios often fail to meet critical frequency requirements.To address this issue,this paper proposes a novel frequency security constrained generation planning(FSCGP)model that leverages the frequency support potential of diverse power sources,including conventional thermal generators(CTGs),VRE units,concentrating solar power(CSP)units,and energy storage systems(ESSs).A physics-data hybrid-driven method is introduced to formulate frequency security constraints,enabling accurate representation of diverse frequency regulation characteristics,particularly the fast frequency support capabilities of inverter-based generators(IBGs).To further enhance the computational efficiency,several acceleration techniques are incorporated into the proposed FSCGP model.Case studies based on a modified IEEE RTS-79 system validate the effectiveness of the proposed FSCGP model.The numerical results identify the primary contributors to frequency security under different renewable energy penetration(REP)levels and demonstrate the cost-effectiveness of coordinating various frequency support sources,especially CSP units and IBGs,in mitigating challenges in low-inertia grids.
基金This work was supported by the National High Technology Research and Development Program of China(863 Program)(No.2011AA05A107)the National Natural Science Foundation of China(No.51207099,No.51261130473)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20120032130008).
文摘This paper proposes a new method for the planning of stand-alone microgrids.By means of clustering techniques,possible operating scenarios are obtained considering the daily patterns of wind and load profiles.Then,an approximate analytical model for reliability evaluation of battery energy storage system is developed in terms of the diverse scenarios,along with multistate models for wind energy system and diesel generating system.An optimal planning model is further illustrated based on the scenarios and the reliability models,with the objective of minimizing the present values of the costs occurring within the project lifetime,and with the constraints of system operation and reliability.Finally,a typical stand-alone microgrid is studied to verify the efficiency of the proposed method.
基金This work was supported in part by the Smart Grid Joint Foundation Program of National Science Foundation of China and State Grid Corporation of China(No.U1966204)in part by National Natural Science Foundation of China(No.51907064)。
文摘With an increasing integration of intermittent distributed energy resources(DERs),the consequent voltage excursion and thermal overloading issues limit the self-sufficiency of distribution networks(DNs).The concept of soft open point(SOP)has been proposed as a promising solution to improve the hosting capacity of DNs.In this paper,considering the ability of building thermal storage(BTS)to increase the penetration of renewable energy in DNs,we provide an optimal planning framework for SOP and DER.The optimal planning model is aimed at minimizing the investment and operational costs while respecting various constraints,including the self-sufficiency requirement of the DN,SOP,building thermal storage capacity and DER operations,etc.A steady-state SOP model is formulated and linearized to be incorporated into the planning framework.To make full use of the BTS flexibility provided by ubiquitous buildings,a differential equation model for building thermal dynamics is formulated.A hybrid stochastic/robust optimization approach is adopted to depict the uncertainties in renewable energy and market prices.IEEE 33-bus feeder and a realistic DN in the metropolitan area of Caracas are tested to validate the effectiveness of the proposed framework and method.Case studies show that SOP/BTS plays a complementary and coordinated coupling role in the thermo-electric system,thereby effectively improving the hosting capacity and self-sufficiency of DNs.
文摘Concerning the integration of large-scale wind power,an integrated model of generation and transmission expansion planning is proposed based on the assessment of the value of steady state and dynamic security.In the assessment of security value,the unit commitment simulation based on the predicted hourly load and wind power output data in the planning horizon is used to evaluate the costs of preventive control,emergency control and social losses due to the uncertainty of load and wind power.The cost of preventive control consists of the fuel cost of power generation,the environmental cost and the load shedding cost.This not only provides a systematic method of security assessment of power system expansion planning schemes,but also broadens the perspective of power system planning from the technology and economic assessment to the measure of the whole social value.In the assessment process,the preventive control and emergency control of cascading failures are also presented,which provides a convincing tool for cascading failure analysis of planning schemes and makes the security assessment more comprehensive and reasonable.The proposed model and method have been demonstrated by the assessment of two power system planning schemes on the New England 10-genarator 39-bus System.The importance of considering the value of security and simulating hourly system operation for the planning horizon,in expansion planning of power system with integration of large-scale wind power,has been confirmed.
