Flexible Production Simulation And Evaluation For Power System With Uncertain Energy

The introduction of renewable energy in the power system plays a vitaland positive role in relieving the pressure of energy shortage, adjusting theenergy structure and solving the environmental problems. However, thoserenewable energy resources are well known for the characteristics ofrandomness, fluctuation and inconsistence, which affect generationexpansion planning and threat the security and stability of the power systemas a whole. As a result, a novel flexible production simulation andevaluation method, which is based on probabilistic theory, is proposed. Themajor innovations and contents are as follows:1) A thorough survey is conducted with respect to the current researchof power system uncertainties, including the potential effects brought bythe integration of uncertain energy. Besides, the concept and procedure offlexible production simulation and evaluation are described in detail.2) Based on the chronological load curve, sequence operation andfrequency function method (SOFF) is proposed to conduct the study ofpower system probabilistic production simulation with uncertain energy.The output forecasting method of uncertain energy is also discussed, basedon which a comprehensive resource planning method considering economyand reliability is put forward. The proposed method takes the uncertaintiesof load, energy source and transmission unit into consideration. The effectsof large scale uncertain energy integration are further explored by adoptingthe equivalent load frequency curve.3) A generation maintenance scheduling model is built with the consideration of power system reserve rate and risk. A multi-objectiveoptimization of system reserve rate fluctuation and average risk is appliedin the unit maintenance scheduling optimization process. By adoptingnondominated sorting genetic simulated-annealing algorithm (NSGSA)，the generation maintenance scheduling optimization result is presentedwith Pareto front set.4) The uncertain energy multi-generator aggregate modeling methodbased on improved genetic K-means clustering algorithm (improved GKA)is put forward. During the aggregation process, a model concerning wakeeffects is built based on the wind speed. The initial cluster number andpoly class center are determined by hierarchical clustering method andfurther optimized by the improved GKA.5) A computation model for abandoned uncertain energy power isdeveloped and utilized in the power system equipped with uncertain energy.The abandoned uncertain energy power is evaluated from both the aspectsof peak-load regulation and the frequency adjustment. From the aspect ofpeak-load regulation, the corresponding abandoned uncertain energypower amount is given based on the peak-load regulation demand andpeak-load regulation capacity of power system. From the aspect offrequency adjustment, the corresponding abandoned uncertain energy iscalculated through multi-scenario analysis theory.Finally, the effectiveness and validity of proposed flexible productionsimulation and evaluation method for power system with uncertain energyare illustrated by a series of test systems.