Abstract
The proliferation of deregulated energy markets in the United States has been steadily increasing over the years, as more service areas have been migrating from the vertically integrated utility model to that of a deregulated energy market. These deregulated energy markets have been increasing due to the fact that they foster access to competitive pricing for electricity to consumers, thus decreasing the price for energy. These economic benefits have been observed across several states that have implemented and facilitated a deregulated energy market structure. Although these markets have overall provided access to reduced electricity prices through competition, the market designs implemented through several aspects specific to the bulk electric system reliability have caused electricity prices to increase under certain real-time operating conditions. The intent of integrating reliability into the market design is to ensure that reliable electricity is provided to consumers, as electricity has become an essential service critical to all aspects of daily life. While the integration of reliability is an important feature of market design, and can provide significant insight in areas specific to a deregulated energy market requiring additional investment through observable increased pricing; they also require significant risk management strategies for market participants to protect themselves from price exposure which in turn provides consumer reduced energy costs. These Risk management strategies are often devised through the use of historical data and financial models and do not take into account the physical grid. This project will show that the physical grid, and associated aspects of market design, such as security-constraints, have a significant effect on Locational Marginal Prices. This project will present the core concepts of a de-regulated energy market. An overview of market design will be presented consisting of an introduction to Real-Time Energy Markets (RTM), Locational Marginal Pricing (LMP), and the concept of Security Constraints in the Bulk Electric System. The IEEE 14 Bus System will be modeled as a combined Power-Market Model in PowerWorld Simulator 21 and two set of price data will be calculated. The first data set arising from an Optimal Power Flow (OPF) method, and the second from a Security-Constrained Optimal Power Flow (SCOPF) method. Prices from both methods will then be compared with the intent of highlighting the significant economic impact security-constraints have on electricity prices in a de-regulated energy market.