Search

The paper analyses the impact of uncertainty in power system on congestion management and minimization of operation cost under overloading condition. In the recent development, Demand Response Programs play a vital role in a smart grid environment. It is an economical and flexible attempt towards the maintenance of system security and reliability. But it has a limited capability, as it totally depends on the effective participation of customers from time to time. The consumer often fails to reduce their load due to some external factors. Thus it is necessary to consider the uncertainty of the responsive loads. For this probabilistic load model is developed on the basis of normal distribution function, in accordance with the historical load data available. Further Monte-Carlo simulation is used and samples are extracted which corresponds to the most probable event. To make the condition more realistic, operational condition during a day (24 hours) is considered. In the end, the multi-stage market clearing procedure is followed and analysis is done for different scenarios: Deterministic as well as Probabilistic. Demand Response Program considered is Time of Use.

This paper proposes the use of Demand Response programs for congestion management. Two DR programs are implemented: Time-of-Use (TOU) and Emergency Demand Response Program (EDRP).A combination of single period modeling and multi-period modeling on the basis of elasticity concept is used to model the DR programs. The model that has been put forward is implemented on load data varying on the hourly basis. Further to analyze the effect of DR program on congestion management an interactive process between GENCOs and ISO is taken into consideration. A two-stage process is followed. First ISO clears the market based on base case generation, after this congestion in transmission lines is checked. If it occurs ISO clears the market using DR programs. Transmission flow violations are again checked and in the case of violations Gencos and demand reschedule their bids.

Traffic congestion and tidal flow management are two major problems in modern urban areas which lead to road accident and loss of life. To implement this, we introduce Automatic Ambulance Rescue System (AARS). The main idea behind this scheme is ambulance can reach smoothly to hospital in time, by mechanically controlling traffic lights in path. The ambulance is controlled by control unit which gives the shortest path for reaching hospital and controls traffic lights. The sensor senses the spot and the nearest ambulance reaches the accident spot. The traffic lights in the path of the ambulance are controlled. The ambulance is guided to hospital by server through shortest route. The vehicle unit installed in vehicle senses the accident and sends the location of the accident to the main server in the ambulance section. The main server finds the ambulance, nearest to the accident spot and also shortest path between ambulance, accident spot and nearest hospital.