Tham khảo tài liệu 'wind power impact on power system dynamic part 14', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 438 Wind Power probabilistic in its very nature and thus it may be appropriately treated by applying stochastic modelling techniques. Only with the advent of more powerful computing hardware the problem of optimizing the spinning reserve has attracted the interest of researchers and its solution is currently deemed practicable. This chapter proposes a novel method for determining the optimal amount of spinning reserve that should be carried in autonomous hybrid wind-diesel generation systems. The optimal spinning reserve is determined by comparing the cost of its provision with the economic benefits it delivers in terms of supply reliability. The proposed approach is still general and can be applied in straightforward manner to establish the optimal reserve level in large interconnected systems. The presented methodology considers with accuracy the probabilistic features of the load and the wind generation as well as the random outages of the conventional generating units. By applying high-resolution chronological simulation techniques the stochastic features of the integrated operation of the diesel units and the wind turbine can be detailed replicated. The mathematical model appropriately considers all relevant characteristics and operational constraints of the generating units . non-linear heat rate curve maximum and minimum output startup and synchronization time minimum down and uptime ramping etc. Massive stochastic simulation methods allow assessing the system reliability and valuing the economic costs of loss load events. Global search methods like particle swarm optimization PSO are proposed for finding the optimal scheduling policy and spinning reserve requirement that minimizes the sum of the expected operation costs and the expected costs of the energy not served. The remaining of this chapter is organized as follows. Section 2 is devoted to revisit the conventional Unit Commitment problem and presents a new stochastic formulation for coping with .
