A case study of the Stockholm Royal Seaport project is analysed to demonstrate how to apply the simulation model to assess a DR program by simulating consumers' behaviour change in response to the DR signals.
In the third case, the MG planning is studied without DR program in order to investigate its effects on the expected profit of MG by hybrid prediction method of WT-ANN-ICA.
Industrial consumers have traditionally provided flexibility for power systems through various Demand Response (DR) programs in different regions of the world, but below their real potential.
Nowadays, electricity markets in many countries have incorporated DR programs, such as the emergency response service and economic DR programs in PJM market [9, 10], and load resources participation in fast responding regulation service in ERCOT [11], etc.
This paper focuses on the review of HEMSs and enabled demand response (DR) programs in various scenarios as well as incorporates various DR architectures and models employed in the smart grid.
Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations.
In this study, the optimal scheduling of MG including WFs, PV, TST, FC, CHP units, boiler, and ESDs is examined with the 24-hour time horizon as well as considering uncertainties and DR programs in order to maximize the expected profit.
A specific DR program for these industries is necessary in the long term.
An algorithm is proposed for programming generation and unit commitment of an MG including three WFs, PV, TST, FC, two CHP units, boiler, and ESDs with and without considering DR program shown in Fig. 1.
Interruptible load management (ILM), as an important incentive-based demand response (DR) program, plays a critical role in power system operation.
