Power Generation Planning Addressing the Critical Issues in Renewable Energy for Carbon Management: Leading the Transition to a Low Carbon World

Modernizing the U.S. electric power grid has been one of the greatest challenges which can help create a safer, cleaner and more secure world. The power architecture exhibits many characteristics of the supply chain management including prosumer and utilities side. The researchers have applied optimization models and algorithms to a wide range of applications in energy and power systems. On the prosumer side, the keys issues involve the reduction of waste of energy, lower monthly payments, and improvised home appliance control, better access to energy usage information, precise picture of real time response. On the utilities side, the major issues comprise of reduction of power procurement cost, developing decision making methodologies, flexibility by time varying prices, reduction in system-wide peak load. Besides that, the role of renewable sources of energy is becoming significant with an aim to ensure reliable, affordable and clean energy worldwide. Wind, Solar PV, Solar thermal, geothermal and bioenergy are some of the distributed energy sources (DERs) that are shaping the renewable revolution. Broadly guessing, the dependence of weather (wind and sunshine) is very important for renewable generation. Because of the uncertainties present in renewable generation, the energy storage has become another challenging and complex issue for the electrical utilities. Factors like reliability and efficient use of renewable encourage the use of battery reserves. But battery reserves come with a high maintenance cost. To address the critical issues present in energy sector, a combined mathematical model of optimal reserve dispatch having volatility in wind conditions and its corresponding generation has been presented for liberalized electricity markets. Specifically, efficient planning and scheduling of energy resources has become a priority for both energy market players and prosumers. To simulate the volatility, three scenarios have been presented which takes the form of stochastic linear programming model which is solved by GAMS/CPLEX. The optimal values of power generation, reserve dispatch (battery) and corresponding sales to the main stream utility market are calculated. Final computational results indicate that increasing the utilization of wind power output might decrease the over-dependence on conventional thermal sources but still the proposed model cannot make the wind and solar power self-sufficient autonomous model. Then the issues of incorporating price based renewable plans will be incorporated into the power scheduling problem for the residential consumers in a smart grid and as a future work, the values of the optimal scheduling strategies will be calculated. In another model, we study the role of aggregator in prosumer inclusive market. The utility market is continuously evolving, and the electrical power landscape is transforming at a faster rate than ever. The traditional electrical power grid management is characterized by one-directional power flows from producers to consumers. The current electric power landscape is moving towards greater decentralization and multidirectional flows, characterized by greater volatility. These days, the flow of power has become multi-directional and decentralization is taking place for production units at the grid level. Micro grid architecture is playing a significant role in meeting the growing changes. Prosumers are getting more freedom and rights in terms of the energy use. This dissertation throws light and discusses a model for a micro grid architecture incorporating the role of aggregators and renewable sources on the prosumer side, working together to optimize configurations and operations. The final model takes the form of mixed integer linear programming model. This model is solved using the CPLEX solver via GAMS by having a consistent data set. All the models are developed and studied with the aim of carbon management in order to reduce the carbon foot prints at a global level.