This paper outlines the fundamental features of the PJM day-ahead energy market and real-time energy market. The Day-ahead market is based on a voluntary least-cost security constrained unit commitment and dispatch with several fundamental design features that ensure the market is robust and competitive. This market offers market participants the option to lock in energy and transportation char...

Building the Family Nest: Pre-Marital Investments, Marriage Markets and Spousal Allocations We develop a model of the household in which spousal incomes are determined by premarital investments, the marriage market is characterized by assortative matching, and endogenously-determined sharing rules form the basis of intra-household allocations. By incorporating pre-marital investments and spousa...

In a stock market, numerous stock prices move under a high level of randomness and some regularity. Some stocks exhibit strong correlation to other stocks. A strong correlation among eminent stocks should result in a visible global pattern. However, the networks of such correlation are unstable and the patterns are only temporal. In such a condition, a detailed description of the network may no...

The uncertainty and volatility of renewable energy generation lead to large amounts abandoned electricity. electricity-hydrogen coupling microgrid (EHCM) consists the proton exchange membrane electrolytic cell (PEMEC), liquid organic hydrogen carrier (LOHC) storage, fuel (PEMFC). structure helps increase utilization wind photovoltaic power. scheduling an EHCM is very challenging. This paper pro...

In this paper, we assess the dynamic impact of U.S. monetary policy announcements on oil market futures returns and volatility. We use intra-day data for West Texas Intermediate (WTI) together with a time-varying modeling approach to study nature impact. addition, also control macroeconomic news shocks separately response good bad realized Evidence suggests that there is significant time variat...

In this study, the Market Clearing Price (MCP) is forecasted with Artificial Neural Networks and modeling success examined for different preprocessing strategies. The purpose of study to obtain optimum model a significant estimation provide best price prediction. hour-based electricity generation data diverse production items are assigned as inputs resulting MCP modeled. raw first cleaned from ...