RESEARCH ARTICLE Risk‐based optimal energy management of virtual power plant with uncertainties considering responsive loads Ali Shayegan Rad 1 | Ali Badri 2 | Ali Zangeneh 2 | Marin Kaltschmitt 3 1 MAPNA Electric and Control, Engineering and Manufacturing Co. (MECO), MAPNA Group, Alborz, Iran 2 Faculty of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran 3 Institute of Environmental Technology and Energy Economics (IUE), Hamburg University of Technology (TUHH), Hamburg, Germany Correspondence Ali Badri, Faculty of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran. Iran. Email: ali.badri@sru.ac.ir Summary This paper proposes a stochastic scheduling model to determine optimal oper- ation of generation and storage units of a virtual power plant (VPP) for partic- ipating in a joint energy and regulation service (RS) market under uncertainty. Beside electricity, the VPP provides required RSs according to the probability of delivery request in the electricity market. A new model for providing RS is introduced in which the dispatchable generation units are financially compen- sated with their readiness declarations and will be charged/paid for their real‐ time down/up regulations. Besides, the VPP sets up incentive price‐quantity curves to benefit from the potential of demand side management in both energy and RS market. Within the model presented here, the VPP consists of two types of generation units: wind turbine and standby diesel generator; the latter is modeled by considering CO 2 ‐emission penalty costs. The given uncertainties are divided into two parts. Firstly, the uncertainties from the energy market price are simulated using information gap decision theory to evaluate the risk‐based resource scheduling for both risk‐taker and risk‐averse VPP. Other uncertainties affecting decision making such as wind turbine generation, load, regulation up/down calling probabilities, and regulation market prices are modeled via scenario trees. Three typical case studies are implemented to vali- date the performance and effectiveness of the proposed scheduling approach. KEYWORDS demand response, energy, information gap decision theory, regulation market, scheduling, virtual power plant 1 | INTRODUCTION Due to the extensive increase of electricity demand and growing awareness related to environmental issues, dis- tributed energy resources (DERs) such as renewable sources of energy are more and more used on a global scale due to significant price drops in recent years. Thus, most likely these technologies will play an increasingly important role within sustainable electricity systems of the future. 1,2 However, the stochastic nature of the wind power and solar radiation is a main challenge of an increased use of these energy resources. 3 One possible way to overcome such obstacles is to aggregate various DERs within a so‐called virtual power plant (VPP). Such a VPP is defined as an integration of very diverse generation units that may be located at different points of the distribution system and operated in a coordinated way. Within such a VPP, the coordinated operated decen- tralized energy resources have the same controllability, visibility, and market functionality as existing large‐scale Received: 6 July 2018 Revised: 25 December 2018 Accepted: 26 December 2018 DOI: 10.1002/er.4418 Int J Energy Res. 2019;1–16. © 2019 John Wiley & Sons, Ltd. wileyonlinelibrary.com/journal/er 1