Semi-markov Chain Based Full-state Model Predictive Energy Management Optimization For PV-FC-BS Hybrid System

The PV-FC-BS hybrid system has been paid more and more attention because of the intermittent and fluctuating problem of PV output power.And it is significant for the application and promotion of PV-FC-BS to accurate predict intermittent randomness of photovoltaic output power,to overcome limitations of each component utilization and to realize efficient power dispatching.It is benefitial for more efficient energy storage component control strategy and optimization of deterministic scheduling.Thus better smoothing the fluctuations of photovoltaic power generation is achieved.According to the working principle and output characteristic of the PV module,the PV output power reference trajectory is determined and the statistical model of PV output power probability is established,which is the mathematical preparation for the semi-Markov discrete stochastic process model.According to the power characteristics of the hybrid system,the output power flow model of PV-FC-BS is established,which constitute the block matrix in the control coefficient matrix of model predictive control.Futhermore,the hybrid system power generation model in different operating modes is established,which constitute the prediction model of the whole state model of the hybrid system to predict the energy management optimization strategy.According to the semi-Markov characteristic of PV output power,the PV output power probability model based on semi-Markov discrete-random process is established.It is more responsive to the sudden change of PV output power and acheived more accurate description.According to the determined PV output power reference trajectory,a correction scheme is proposed for the real-time prediction error to realize the rolling prediction of the PV output power,so as to ensure the accuracy of the PV output power prediction and rapid responce of the PV output mutation.Traditional energy management strategy often creates separated predictionmodels in different switch mode.It is difficult to guarantee the stability in mode switching process.New BS charging-discharging constraints are proposed and full-state multiple-input-multiple-output dynamic power exchange model is built.Therefore such energy management problem is transformed into an optimization problem,reducing the complexity of algorithm and avoiding the impact of mode switching.PV-FC-BS hybrid system energy optimal allocation is realized by designing dynamic prediction model and quick rolling optimization methods.Taking charging or discharging efficiency coefficient of batteries into account,an adaptive estimation algorithm of battery constant charging-discharging parameter is proposed to achieve an accurate scheduling of energy.In the MATLAB environment,the prediction accuracy of PV semi-Markov chain prediction and the optimization strategy of PV-FC-BS hybrid system are simulated.The results show that the proposed prediction method has high accuracy.The results show that the proposed management strategy has the advantages of small computational complexity,accurate energy allocation,strong adaptability to different applications,and cooperative controling and scheduling.The control strategy of energy storage components is more efficient and optimized.Thus scheduling has higher accuracy.