This paper studies the algorithm of the adaptive grid and fuzzy interacting multiple model （AGFIMM） for maneuvering target tracking, while focusing on the problems of the fixed structure multiple model （FSMM） algo...This paper studies the algorithm of the adaptive grid and fuzzy interacting multiple model （AGFIMM） for maneuvering target tracking, while focusing on the problems of the fixed structure multiple model （FSMM） algorithm＇s cost-efficiency ratio being not high and the Markov transition probability of the interacting multiple model （IMM） algorithm being difficult to determine exactly. This algorithm realizes the adaptive model set by adaptive grid adjustment, and obtains each model matching degree in the model set by fuzzy logic inference. The simulation results show that the AGFIMM algorithm can effectively improve the accuracy and cost-efficiency ratio of the multiple model algorithm, and as a result is suitable for enineering apolications.展开更多
With the advancement of energy transition,residential photovoltaic(PV)systems face intermittency challenges that impact grid stability.While battery integration enhances resilience,existing approaches exhibit critical...With the advancement of energy transition,residential photovoltaic(PV)systems face intermittency challenges that impact grid stability.While battery integration enhances resilience,existing approaches exhibit critical gaps:(1)underdeveloped hybrid modeling frameworks balancing physical interpretability and data-driven accuracy;(2)reinforcement learning(RL)strategies prioritizing economic gains over grid stability,risking localized fluctuations;and(3)performance evaluations lacking systematic assessment across varying PV-battery capacities.To bridge these gaps,this study proposes a hybrid framework combining physical energy flow constraints with XGBoost-based machine learning for robust forecasting.Two optimization strategies,proximal policy optimization(PPO)and rule-based control(RBC),are developed for charge-discharge scheduling,explicitly incorporating grid stability metrics.Multi-scenario analysis evaluates performance under varying capacities and initial states of charge(SOC).Results demonstrate the hybrid model’s superiority over physics-based benchmarks,significantly improving prediction accuracy,with R2 increasing from 0.70 to 0.95 for SOC and from 0.83 to 0.98 for grid power.Both PPO and RBC enhance efficiency and stability versus baseline:the energy self-sufficiency rate rises from 10.6%to 79.3%(PPO)and 82.4%(RBC),while grid power fluctuations decrease from 2.6 kWh to 1.66 kWh(PPO)and 1.38 kWh(RBC).Crucially,RBC achieves higher stability and interpretability near boundaries,whereas PPO excels in long-term optimization but exhibits boundary-condition sensitivity.Results further reveal that PV-battery capacity and initial SOC influence strategy performance.This study establishes a structured technical pathway encompassing hybrid forecasting model development,stability-oriented optimization design,and scenario-based performance evaluation,providing an integrated solution to enhance grid resilience and energy autonomy in residential PV-battery systems.展开更多
“Net Zero-Energy Building”has become a popular catchphrase to describe the synergy between energy-efficient building and renewable energy utilisation to achieve a balanced energy budget over an annual cycle.Taking i...“Net Zero-Energy Building”has become a popular catchphrase to describe the synergy between energy-efficient building and renewable energy utilisation to achieve a balanced energy budget over an annual cycle.Taking into account the energy exchange with a grid overcomes the limitations of energy-autonomous buildings with the need for seasonal energy storage on-site.Although the expression,“Net Zero-Energy Building,”appears in many energy policy documents,a harmonised definition or a standardised balancing method is still lacking.This paper reports on the background and the various effects influencing the energy balance approach.After discussing the national energy code framework in Germany,a harmonised terminology and balancing procedure is proposed.The procedure takes not only the energy balance but also energy efficiency and load matching into account.展开更多
基金Foundation item： Supported by the National Nature Science Foundation of China （No. 61074053, 61374114） and the Applied Basic Research Program of Ministry of Transport of China （No. 2011-329-225 -390）.
文摘This paper studies the algorithm of the adaptive grid and fuzzy interacting multiple model （AGFIMM） for maneuvering target tracking, while focusing on the problems of the fixed structure multiple model （FSMM） algorithm＇s cost-efficiency ratio being not high and the Markov transition probability of the interacting multiple model （IMM） algorithm being difficult to determine exactly. This algorithm realizes the adaptive model set by adaptive grid adjustment, and obtains each model matching degree in the model set by fuzzy logic inference. The simulation results show that the AGFIMM algorithm can effectively improve the accuracy and cost-efficiency ratio of the multiple model algorithm, and as a result is suitable for enineering apolications.
文摘With the advancement of energy transition,residential photovoltaic(PV)systems face intermittency challenges that impact grid stability.While battery integration enhances resilience,existing approaches exhibit critical gaps:(1)underdeveloped hybrid modeling frameworks balancing physical interpretability and data-driven accuracy;(2)reinforcement learning(RL)strategies prioritizing economic gains over grid stability,risking localized fluctuations;and(3)performance evaluations lacking systematic assessment across varying PV-battery capacities.To bridge these gaps,this study proposes a hybrid framework combining physical energy flow constraints with XGBoost-based machine learning for robust forecasting.Two optimization strategies,proximal policy optimization(PPO)and rule-based control(RBC),are developed for charge-discharge scheduling,explicitly incorporating grid stability metrics.Multi-scenario analysis evaluates performance under varying capacities and initial states of charge(SOC).Results demonstrate the hybrid model’s superiority over physics-based benchmarks,significantly improving prediction accuracy,with R2 increasing from 0.70 to 0.95 for SOC and from 0.83 to 0.98 for grid power.Both PPO and RBC enhance efficiency and stability versus baseline:the energy self-sufficiency rate rises from 10.6%to 79.3%(PPO)and 82.4%(RBC),while grid power fluctuations decrease from 2.6 kWh to 1.66 kWh(PPO)and 1.38 kWh(RBC).Crucially,RBC achieves higher stability and interpretability near boundaries,whereas PPO excels in long-term optimization but exhibits boundary-condition sensitivity.Results further reveal that PV-battery capacity and initial SOC influence strategy performance.This study establishes a structured technical pathway encompassing hybrid forecasting model development,stability-oriented optimization design,and scenario-based performance evaluation,providing an integrated solution to enhance grid resilience and energy autonomy in residential PV-battery systems.
文摘“Net Zero-Energy Building”has become a popular catchphrase to describe the synergy between energy-efficient building and renewable energy utilisation to achieve a balanced energy budget over an annual cycle.Taking into account the energy exchange with a grid overcomes the limitations of energy-autonomous buildings with the need for seasonal energy storage on-site.Although the expression,“Net Zero-Energy Building,”appears in many energy policy documents,a harmonised definition or a standardised balancing method is still lacking.This paper reports on the background and the various effects influencing the energy balance approach.After discussing the national energy code framework in Germany,a harmonised terminology and balancing procedure is proposed.The procedure takes not only the energy balance but also energy efficiency and load matching into account.
