Power System Operational Scenario And Risk Management Based On Stochastic Constraints

The infrastructure of power system is becoming more and more complex along with its development. Some components of it are uncertain, which will lead to stochastic constraints. Such as unplanned outage and repair of generators and transmission lines, the forecast errors and inaccuracies of load demand and the power of intermittent energy, and the possible load fluctuate caused by electrical vehicle in the future smart grid time and V2G technology. These stochastic constraints will bring obstacles to power system operation management, and will influence the safety, reliability and economic of the system as well. This paper discusses the different types of stochastic constraints in power system, analyzes their sources, features, and gives corresponding solutions, especially for the growing penetration of intermittent energy into the power system.After discussing the sources of these stochastic constraints, this paper mainly introduces the following two parts:1. Presents a unit commitment model based on the penetration of intermittent energy, using wind as an example. VaR and Integrated Risk Management (IRM) are adopted to assess the risk of the results obtained respectively;2. Proposed a risk contribution model based on uncertainties in power systems, which can separate different risks caused by different risk factors and calculate corresponding risk contributions, rather than treating them as a whole as in traditional methods.By introducing the two points above, this paper realizes the followings:1. Establishes an operation model for intermittent energy penetrated power system and its corresponding risk management algorithm. System operators can refer to the results obtained by this model and algorithm to make a tradeoff operation plan between economic and risk;2. IRM can be applied to the systems in which there are many sorts of uncertainties and precise and quantitative risk management method should be employed. The corresponding amount of risk management method can be determined by different values of risk;This article is funded by the National High Technology Research and Development Program of China (863) (no: 2007AA05Z458) for completion.