Optimum scheduling of micro grid connected wind-pumped storage hydro plant in a frequency based pricing environment

Abstract

This paper presents a new formulation to maximize the operational profit of a micro grid connected hybrid system having wind farm and pumped storage unit for a day ahead electricity market in a frequency based pricing environment. Under frequency based pricing mechanism in India, the pricing for energy exchange is adaptive as per Availability Based Tariff (ABT) rate structure and the payment for deviation from schedule, i.e. Unscheduled Interchange (UI) charge is inversely proportional to the prevailing grid frequency. In this work, a small power system is considered as micro grid and it is expected that the hybrid system connected with the micro grid has a role to play to maintain the micro grid frequency. The pump storage hydro plant is operated to serve the dual role of minimizing the UI flow and maximizing the system economy by participating in frequency control based on energy price. The uncertainties in wind power prediction and loads are considered. The optimum operating schedule of PSH unit in coordination with wind farm is investigated. The optimization is performed by utilizing the water storage availability of pump storage hydro unit. An optimization algorithm is proposed and solved using Artificial Bee Colony algorithm. The solution of the proposed approach gives the strategies to be followed by the hybrid system to operate its pump storage unit. The effect of the initial storage water volume on the performance of the hybrid system has also been investigated. It reveals that the PSH units would not operate simply to compensate for the short fall or the surplus generation of the wind units in a frequency based pricing system. Rather, the pump storage units should take the advantage of the low price periods to maximize the profit of the hybrid system. The hourly energy management scenarios of the hybrid system with the micro grid are reported and the numerical case studies on PSH plant scheduling demonstrate the effectiveness of the proposed approach.