To gradually building a sustainable energy system, the electricity power system is experiencing its most dramatic transformation to a new vision with high level penetration of renewable generation. The global installed wind capacity reached 591 GW at the end of 2018. Meanwhile, the total installed capacity for PV crossed the 500 GW mark in 2018. Even more, “the increasing competitiveness of solar PV pushes its installed capacity beyond that of wind before 2025, past hydropower around 2030 and past coal before 2040”, said the IEA energy outlook report of 2018 version.
However, wind power and PV, which have remarkable randomness and volatility, bring great challenge to the dispatching of power system, and lead to serious problem of abandoning wind and solar power. Two positive efforts have been made to try to solve the problem. The first way is wind and solar power forecasting technologies. By the power prediction of the next several hours to even several days, the uncertainty characters can be grasped to a great extent and used in operation scheduling in advance. Secondly, the new dispatching mode and technical system which fully consider the characteristics of variable generation such as wind power and PV is established.
To keep track of the latest research in these areas, this special issue investigates the forecasting and scheduling method of wind and solar power generations, focusing on the theories, methods, strategies, platforms and case studies related to these issues. This Special Section solicits original work that is not under consideration for publication in other avenues.
1. Medium-and long-term electricity forecasting of wind /photovoltaic power generation
2. Multiple time scale short-term wind /photovoltaic power prediction
3. Ultra-short-term wind /photovoltaic power forecasting technology considering resource relevance
4. Probabilistic wind /photovoltaic power forecasting method
5. Medium-and long-term scheduling method of power system with high share of variable generation
6. Risk based dispatching decision method considering the uncertainty of renewable power forecasting
7. Optimal allocation of reserve generation for dealing with uncertainty of renewable power forecasting
8. Emergency control method for dealing with uncertainty of renewable power forecasting
This special issue solicits any original work that is not under consideration for publication in other journals and magazines. Authors should refer to https://www.pcmp.springeropen.com or https://www.pcmp.info for information about content and formatting of submissions.
Zongxiang Lu, Tsinghua University, BEIJING, China
Mingjie Li, National Electrical Power Dispatching & Control Center, BEIJING, China