journal article·2019-04-27Open access

Flexibility Based Day-Ahead Generation–Reserve Bilevel Decision Model

Yan Li, Ming Zhou

Applied Sciences· Volume 9· Issue 9

Abstract

With the increasing penetration rate of renewable energy like fluctuating wind and solar energy, the power system has to equip itself with a more reasonable reserve capacity. Therefore, how to quantify the reserve capacity needed for dealing with the uncertainty and fluctuation has turned out to be a new problem faced by the power system integrated with large-scale renewable energy. This paper proposes a flexibility based day-ahead generation–reserve bilevel decision model. In the upper level, the day-ahead unit commitment model is constrained by flexibility reserve, which is calculated in the lower level. In the lower level, taking into account various factors of uncertainty and fluctuation, e.g., wind power ramping, load ramping and random failure of conventional units, the ramping probability distribution of an equivalent system is obtained by the universal generating function method, then the quantified relationship between operating reserve and flexibility is established ultimately. If the unit commitment scheme gained from the upper level could not provide sufficient reserve, a feedback for the correction of the upper level is needed. The rationality and validity of the proposed model are verified through the simulation of a modified IEEE-118 bus system.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Electric Power System Optimization · Integrated Energy Systems Optimization · Smart Grid Energy Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China

Funding

National Natural Science Foundation of China · National Key Research and Development Program of China

References (31)

Show source-provided references
1. (2017, April 22). Data: China Is Wasting Lots of Renewable Energy. Available online: http://energydesk.greenpeace.org/2017/04/19/chinawind-solar-renewable-curtailment-energy-wasted/.
2. Increasing the Flexibility of Combined Heat and Power for Wind Power Integration in China: Modeling and Implications10.1109/TPWRS.2014.2356723 ↗
3. National Development of Reform Commission and National Energy Administration (2018, April 04). Guidance on Enhance the Power System Regulation Capability, Available online: http://www.nea.gov.cn/2018-03/23/c_137059994.htm.
4. Integration of wind and solar power in Europe: Assessment of flexibility requirements10.1016/j.energy.2014.02.109 ↗
5. Reducing curtailment of wind electricity in China by employing electric boilers for heat and pumped hydro for energy storage10.1016/j.apenergy.2015.10.147 ↗
6. Northeast China Energy Regulatory Bureau of National Energy Administration (2017, January 12). Pilot Work on the Special Reform of the Northeast Power Auxiliary Service Market Officially Launched, Available online: http://dbj.nea.gov.cn/nyjg/hyjg/201611/t20161124_2580781.html.
7. Short-term Operation Service Mechanism of Ancillary Service in the UK Electricity Market and Its Enlightenment
8. A Two-Stage Stochastic Dynamic Economic Dispatch Model Considering Wind Uncertainty10.1109/TSTE.2015.2498614 ↗
9. Multi-area generation-reserve joint dispatch approach considering wind power cross-regional accommodation10.17775/CSEEJPES.2017.0010 ↗
10. Power-Capacity and Ramp-Capability Reserves for Wind Integration in Power-Based UC10.1109/TSTE.2015.2498399 ↗
11. Reserve constrained dynamic economic dispatch with valve-point effect: A two-stage mixed integer linear programming approach10.17775/CSEEJPES.2017.0025 ↗
12. Energy and reserve co-optimisation—Reserve availability, lost opportunity and uplift compensation cost10.1049/iet-gtd.2018.5480 ↗
13. A Multi-Objective Optimization Approach to Risk-Constrained Energy and Reserve Procurement Using Demand Response10.1109/TPWRS.2017.2785266 ↗
14. Adams, J.M., O’Malley, M., Bagen, B., Milligan, M., Connolly, K., Coste, W.H., Crews, W.C., Hanson, K., Jacobson, D., and Jefferies, K. (2010). Flexibility Requirements and Potential Metrics for Variable Generation: Implications for System Planning Studies, NERC.
15. Investigation of real-time flexibility of combined heat and power plants in district heating applications10.1016/j.apenergy.2019.01.017 ↗
16. Reconstructing Operating Reserve: Flexibility for Sustainable Power Systems10.1109/TSTE.2015.2462318 ↗
17. Probabilistic Flexibility Evaluation for Power System Planning Considering Its Association with Renewable Power Curtailment10.1109/TPWRS.2018.2810091 ↗
18. Flexibility Envelopes for Power System Operational Planning10.1109/TSTE.2015.2410760 ↗
19. International Energy Agency (2014). The Power of Transformation: Wind, Sun and the Economics of Flexible Power Systems, International Energy Agency.
20. Assessment on operational flexibility of power grid with grid-connected large-scale wind farms
21. Mazidi, P., Baltas, G.N., Eliassi, M., and Rodríguez, P. (2018, January 14–17). A model for flexibility analysis of RESS with electric energy storage and reserve. Proceedings of the 7th International Conference on Renewable Energy Research and Applications, Paris, France.10.1109/ICRERA.2018.8566992 ↗
22. Pham, H. (2005). Basic Tools and Techniques. The Universal Generating Function in Reliability Analysis and Optimization, Springer.
23. Minimizing Bypass Transportation Expenses in Linear Multistate Consecutively-Connected Systems10.1109/TR.2014.2299156 ↗
24. Reliability Evaluation of Large Scale Battery Energy Storage Systems10.1109/TSG.2016.2536688 ↗
25. Universal generating function based probabilistic production simulation for wind power integrated power systems10.1007/s40565-015-0114-2 ↗
26. Uncertainty Importance Measure of Individual Components in Multi-State Systems10.1109/TR.2014.2364575 ↗
27. Load Modeling For Power System Requirement and Capability Assessment10.1109/TPWRS.2014.2348531 ↗
28. Quantifying Spinning Reserve in Systems with Significant Wind Power Penetration10.1109/TPWRS.2012.2207465 ↗
29. (2014, May 04). Yalmip: Getting Started. Available online: https://yalmip.github.io/tutorial/basics/.
30. (2014, May 04). IBM ILOG CPLEX Optimization Studio CPLEX User’s Manual, Version 12 Release 6. Available online: https://www.ibm.com/support/knowledgecenter/SSSA5P_12.6.1/ilog.odms.studio.help/pdf/usrcplex.pdf?view=kc.
31. Power System Test Archive (2014, May 13). (Illinois Institute of Technology). Available online: http://motor.ece.iit.edu/data/SCUC_118test.xls.