This paper proposes a stochastic optimization model for the day-ahead scheduling in power systems, which incorporates the hourly demand response (DR) for managing the variability of renewable energy sources (RES). DR considers physical and operating constraints of the hourly demand for economic and reliability responses. The proposed stochastic day-ahead scheduling algorithm considers random ou...

The aim of this paper is to address the challenges regarding safety and economics power system operation after integration a high proportion wind power. In response limitations literature, which often fails simultaneously consider both aspects, we propose solution based on stochastic optimization scheduling model. Firstly, uncertainty day-ahead forecasting errors establish multi-scenario By bal...

Distribution networks are envisaged to host significant number of electric vehicles and potentially many charging stations in the future provide as well vehicle-2-grid services vehicle owners. The main goal this study is develop a comprehensive day-ahead scheduling framework achieve an economically rewarding operation for ecosystem vehicles, retailers using optimal charging/discharging strategy...

In this master thesis, a model is proposed to enable profitable market participation of wind power plants considering the availability of second-party owned energy storage. A novel concept of storage capacity reservations is presented using which the wind power producer hedges against wind outcomes which are unfavourable with respect to its day-ahead market bids. The idea that wind power produc...

One of the most important methods for implementing demand response (DR) schemes is to allocate time-varying prices power by consumers. Indeed, effective implementation DR programs passes from a successful pricing way retail electricity. However, massive influence renewable energy sources with unpredictable generation in today’s systems such as Micro-grids has made any planning encounter serious...

Driven by the improvement of smart grid, active distribution network (ADN) has attracted much attention due to its characteristic management. By making full use electricity price signals for optimal scheduling, total cost ADN can be reduced. However, day-ahead scheduling problem is challenging since future unknown. Moreover, in ADN, some schedulable variables are continuous while discrete, whic...