A5101400819- Electric Power System Optimization
- Smart Grid Energy Management
- Power Systems and Renewable Energy
- Energy Load and Power Forecasting
- Building Energy and Comfort Optimization
- Smart Grid and Power Systems
- Adsorption and Cooling Systems
- Microgrid Control and Optimization
- Integrated Energy Systems Optimization
- Power Systems and Technologies
- Refrigeration and Air Conditioning Technologies
- Optimal Power Flow Distribution
- Power System Reliability and Maintenance
- Thermodynamic and Exergetic Analyses of Power and Cooling Systems
- Solar Energy Systems and Technologies
- Advanced Computational Techniques and Applications
- Phase Change Materials Research
- Market Dynamics and Volatility
- Wind and Air Flow Studies
- Thermal Analysis in Power Transmission
- High-Voltage Power Transmission Systems
- Consumer Market Behavior and Pricing
- Advanced Algorithms and Applications
- Image and Object Detection Techniques
- Energy Efficiency and Management
Shanghai University
2013-2024
Hunan University
2021-2023
Shanghai University of Electric Power
2018-2020
China Southern Power Grid (China)
2013
Shaoxing University
2010
Minzu University of China
2010
Jiangnan University
2004-2008
This paper reviews recent research on the demand flexibility of residential buildings in regard to definitions, flexible loads, and quantification methods. A systematic distinction terminology is made, including flexibility, operation energy buildings. comprehensive definition building proposed based an analysis existing definitions. Moreover, capabilities characteristics main loads are summarized compared. Models evaluation indicators quantify these reviewed summarized. Current gaps...
Because of the existences market power and economies scale, there have been various pricing methods proposed for pool-based electricity market, example, uniform clearing method (UCP), pay as bid (PAB) value equivalent (EVE) method. An agent-based simulation model is developed in this paper to compare characteristics under different methods. In generators learn bidding strategy using reinforced learning algorithm repeated game seek their maximum profits. Simulation result presented based on...
Real-Time Pricing (RTP) is proposed as an effective Demand-Side Management (DSM) to adjust the load curve in order achieve peak shifting.At same time, RTP mechanism can also raise revenue of supply-side and reduce electricity expenses consumers a win-win situation.In this paper, real-time pricing algorithm based on price elasticity theory analyze energy consumption response smart grid structure.We consider equipped with meters two-way communication system.By using real data simulate model,...
This paper summarizes the typical operation strategy for CCHP, and problem is modeled as nonlinear programming in which relationship between generating heating efficiency change with power are considered constraints. The KKT condition of optimal model investigated strategy, that obtained. A CCHP simulation algorithm based on presented this paper. numerical results demonstrated cost reduces significantly comparison traditional strategy.
In the deregulated electricity market, accurate knowledge of price trend helps maximize profit participants in market. But with increasing proportion clean energy, it brings new challenges to forecast. This paper mainly studies how forecast more accurately power market which has large wind power. A feature called load ratio is introduced, not only used as a candidate input predicted model, but also an important indicator distinguish day and night. The model established according selected...
In this paper, a calculation methodology of the power system production simulation is proposed. On one hand, wind conversion simulated as doing in sequential Monte Carlo simulation. other probability distribution function convention units' available capacity employed during The developed paper used chronological load model, which could take account intermittency generation. presented method has important characteristics wherein correlation speeds and abandonment generation, caused by...
In the deregulated electricity market, accurate knowledge of price tend helps maximize profitability participants in so forecasting becomes extremely important. On basis not considering situation market itself and many factors affecting price, historical load are used as inputs to predict from perspective data driven. The Lasso, Random Forest, Support Vector Machine BP Neural Network methods establish a single algorithmic model respectively, then linear Lasso nonlinear neural network make...
In this paper, the cross-border electricity price difference data in Nordic power market is modeled with standard generalized autoregressive conditional heteroscedasticity model, GJR model and Markov-switching GARCH model. These models are estimated normal, skewed normal student-t-t distributions. Studies show that not only a "spike" higher than data, jumping more obvious, but also "volatility cluster" strongly regime-dependent. The example analysis shows MS-GARCH distribution has better...
In the bilateral power market with an open transmission grid, how to allocate loss reasonably and fairly is important problem faced by market. Based on original method, this paper applies method allocation of transactions. The proposed in as follows: complex flow tracing which based circuit theory, allocated load side source respectively, then responsibility obtained averaging both side. IEEE-5 bus system analyzed calculated, compared transaction incremental traditional verify rationality method.
The participants utility of the peak regulation market is analyzed in this paper. And then a trading model proposed which employed marginal generating cost as decision variables. Using model, characteristics are revealed that total costs reduced after peaking transaction. bidding, clearing and settlement rules given based on model. A case study illuminates theory results.