Contents 1. Introduction
Renewable integration studies such as [1], [2] have evaluated many challenges associated with deploying large amounts of variable wind and solar generation. Using production cost modeling software, these studies have evaluated the operational impacts associated with variable generation, benefits of improved wind and solar resource forecasting, and trade-offs among institutional changes. For example, the commercially available PLEXOS simulates the commitment and dispatch of the power plant fleet to meet load at least cost while maintaining system reliability. However, these types of studies have not yet considered how markets function by means of the interactions among strategic entities that compete to supply energy to the marketplace. Standard power system software tools are limited in their ability to recognize strategic behavior that might have significant impacts on market outcomes. Generation companies act strategically to maximize their own profits, subject to their real and perceived risks and technical constraints, and they are averse to the risks associated with uncertainty. The current literature on electricity markets has looked at how different market rules can affect price formation [3]–[7] and how bidding behaviors can change based on several conditions [8]–[11]. As the level of renewable energy sources on the electric grid increases, price suppressions coming from the deployment of zero-marginal-cost resources such as wind and solar may have a significant impact on the behavior of generators and decision-makers. This contributes to the discussions among power system industry actors and those who regulate it about how to design future energy markets. Another very important issue that affects energy market participants who invest in generation assets is the lack of monetary stream that can guarantee a recovery from their investments. The same issue also affects incentives to build new generation facilities if the prices do not increase because of administrative actions, such as price caps. This phenomenon is often referred to as the “missing money problem.” The missing money problem is predicted by electricity market theory [12]–[14]. To address this, most North-American independent system operators (ISOs) have established longer-term markets, such as capacity markets (e.g., New York ISO, PJM, Midcontinent ISO, ISO-New England, California ISO). However, a few (e.g., Electric Reliability Council of Texas [ERCOT], the Alberta wholesale market) rely on recovering costs from energy, operating reserves, and not capacity, and they employ a price cap at the value of lost load as a correct scarcity pricing signal to incent new generation.
