A Stochastic Operational Planning Model for Smart Power Systems
Authors
Abstract:
Smart Grids are result of utilizing novel technologies such as distributed energy resources, and communication technologies in power system to compensate some of its defects. Various power resources provide some benefits for operation domain however, power system operator should use a powerful methodology to manage them. Renewable resources and load add uncertainty to the problem. So, independent system operator should use a stochastic method to manage them. A Stochastic unit commitment is presented in this paper to schedule various power resources such as distributed generation units, conventional thermal generation units, wind and PV farms, and demand response resources. Demand response resources, interruptible loads, distributed generation units, and conventional thermal generation units are used to provide required reserve for compensating stochastic nature of various resources and loads. In the presented model, resources connected to distribution network can participate in wholesale market through aggregators. Moreover, a novel three-program model which can be used by aggregators is presented in this article. Loads and distributed generation can contract with aggregators by these programs. A three-bus test system and the IEEE RTS are used to illustrate usefulness of the presented model. The results show that ISO can manage the system effectively by using this model
similar resources
A Petri-net Model for Operational Cycle in SCADA Systems
Supervisory control and data acquisition (SCADA) system monitors and controls industrial processes in critical infrastructures (CIs) and plays the vital role in maintaining the reliability of CIs such as power, oil, and gas system. In fact, SCADA system refers to the set of control process, which measures and monitors sensors in remote substations from a control center. These sensors usually ha...
full textMedium Term Hydroelectric Production Planning - A Multistage Stochastic Optimization Model
Multistage stochastic programming is a key technology for making decisions over time in an uncertain environment. One of the promising areas in which this technology is implementable, is medium term planning of electricity production and trading where decision makers are typically faced with uncertain parameters (such as future demands and market prices) that can be described by stochastic proc...
full textA Game Theoretic Approach for Sustainable Power Systems Planning in Transition
Intensified industrialization in developing countries has recently resulted in huge electric power demand growth; however, electricity generation in these countries is still heavily reliant on inefficient and traditional non-renewable technologies. In this paper, we develop an integrated game-theoretic model for effective power systems planning thorough balancing between supply and demand for e...
full textA stochastic model for operating room planning under uncertainty and equipment capacity constraints
In the present economic context, the operating theater is considered as a critical activity in health care management. This paper describes a model for operating room (OR) planning under constraint of a unique equipment. At first level we schedule elective surgeries under the uncertainty of using a unique equipment. At the second level we consider emergency surgeries, and at the third le...
full textA Stochastic Model for Water Resources Management
Irrigation water management is crucial for agricultural production and livelihood security in many regions and countries throughout the world. Over the past decades, controversial and conflictladen water-allocation issues among competing municipal, industrial and agricultural interests have raised increasing concerns. Particularly, growing population, varying natural conditions and shrinking wa...
full textMy Resources
Journal title
volume 10 issue 4
pages 293- 303
publication date 2014-12
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023