| نویسندگان | Mostafa Vahedipour-Dahraie |
| نشریه | Sustainable energy grids and networks |
| شماره صفحات | 1-11 |
| شماره سریال | 33 |
| شماره مجلد | 1 |
| نوع مقاله | Full Paper |
| تاریخ انتشار | 2022 |
| نوع نشریه | چاپی |
| کشور محل چاپ | ایران |
| نمایه نشریه | ISI،JCR،Scopus |
| کلید واژه ها | Demand response Optimal scheduling Stochastic framework Virtual power plant |
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چکیده مقاله
In this paper, a three-stage bi-level stochastic programming approach is proposed for joint energy and
reserve scheduling of a virtual power plant (VPP). In this framework, the VPP can provide demand
response (DR) services and reserve capacity from external DR providers (DRPs) by participating in a
local intraday demand response exchange (IDRX) market and trading with internal load aggregators
(LAs). The VPP tries to reach a proper balance between allocating spinning reserve and DR services to
reduce the penalty cost resulting from the difference between the day-ahead (DA) scheduled power
and the real-time dispatched. To this end, a bi-level problem is formulated, in which at the upper
level the objective of the VPP is to maximize its profit, and in the lower level, the LAs maximize
their social welfare. The interaction between the VPP and the LAs is modelled as a Stackelberg game;
then, by reformulating the lower-level problem using Karush–Kuhn–Tucker optimality conditions, a
mathematical programming with equilibrium constraints (MPEC) is achieved. The intended problem
is converted into a convex mixed-integer quadratic problem (MIQP) by applying the strong duality
theorem. Simulation results demonstrate that providing DR services from the internal LAs and the
local IDRX market noticeably affects the VPP’s decisions improving the profit by more than 7% and
reducing the imposed imbalance penalty in the balancing market by nearly 50%.
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