Abstract
This paper introduces the “Energy-Environmental Efficiency” concept of building a low-carbon dispatch model of wind-incorporated power systems from the perspective of environmental protection and low-carbon dispatch promotion based on the existing economic environmental dispatch. A rolling auto-regressive and moving-average model is adopted to forecast wind speeds for the next 24 h and reduce the disadvantages brought about to the power system dispatch by wind speed fluctuations. A fuzzy satisfaction-maximizing approach is employed to convert the multi-objective decision-making problem in the low-carbon dispatch model into a single nonlinear one. Particle swarm optimization with a simulated annealing algorithm hybrid is used for better solutions. Simulation results show that the energy-environmental efficiency concept benefits the optimization of the proposed power system dispatch, and the proposed low-carbon dispatch model is reasonable and practical.
Highlights
The global energy security and environment situation has become increasingly serious in recent years, leading to a mounting social appeal for environmental protection and sustainable development [1].One of the most promising nonpolluting renewable energy sources, wind power, has been given more consideration by policies because of its difference from conventional energy sources [2]
The energy-environmental efficiency concept is introduced into the optimal dispatch of wind-incorporated power systems, for which a low-carbon dispatch model considering unit commitment is built based on wind speed prediction
This paper introduces wind speed prediction technique and energy-environmental efficiency concept into the optimization dispatch problem of a wind-incorporated power system
Summary
The global energy security and environment situation has become increasingly serious in recent years, leading to a mounting social appeal for environmental protection and sustainable development [1]. The intermittent and unpredictable nature of wind power generation can influence generation schedule and frequency control For this reason, the main method currently used to deal with problems of grid-connected wind power generation is to integrate wind speed forecasting into dispatch operation. Auto-regressive and moving-average (ARMA), artificial neural network, Kalman filter algorithm, fuzzy logic, and wavelet analysis are the most commonly used methods in wind speed forecasting These methods mainly aim at very short-term forecasting, without considering the time sequence of wind speed data. The premise of large-scale wind power integration, optimization scheduling can effectively reduce CO2 emissions, promote low carbon for power production, and promote sustainable development in the power industry. The energy-environmental efficiency concept is introduced into the optimal dispatch of wind-incorporated power systems, for which a low-carbon dispatch model considering unit commitment is built based on wind speed prediction.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
