Should Natural Gas Be Shipped or Stored to Supply Power Plants?

Following a series of winters featuring extreme cold episodes in the Northeastern U.S., power grid operators have engaged in exercises focused on assessing fuel deliverability to power plants, particularly natural gas. These studies have raised important issues and identified possible scenarios that could contribute to reliability problems during winter peaks, but have not evaluated the economics of specific solutions to winter-time fuel deliverability. This paper describes an expansion to a new modeling framework for gas and electric power transmission planning problems (the Combined Electricity and Gas Expansion, or CEGE model) that allows centralized or distributed natural gas storage to be evaluated alongside traditional planning alternatives such as transmission network expansion. Using a test system based on the gas and electric transmission topology in New England, we develop a a simple two-period gas storage model and use this model to evaluate economically valuable locations for distributed natural gas storage and compare the economic merits of increasing storage within New England versus expanding pipeline infrastructure to increase fuel deliverability to New England power plants within our test system. Initial simulations using this storage model suggest that the optimal placement for gas storage may be co-located with power plants to relieve binding pressure constraints in areas of the gas network close to gas-fired generation. Moreover, the economic consequences of extreme winter peak scenarios may be ameliorated at a lower cost with a mix of gas storage and pipeline expansions rather than via pipeline expansion alone

Joint Planning of Natural Gas and Electric Power Transmission with Spatially Correlated Failures

We develop and illustrate a method for the joint planning of natural gas and electric power systems that are subject to spatially correlated failures of the kind that would be expected to occur in the case of extreme weather events. Our approach utilizes a two-stage stochastic planning and operations framework for a jointly planned and operated gas and electric power transmission system. Computational tractability is achieved through convex relaxations of the natural gas flow equations and the use of a machine learning algorithm to reduce the set of possible contingencies. We illustrate the method using a small test system used previously in the literature to evaluate computational performance of joint gas-grid models. We find that planning for geographically correlated failures rather than just random failures reduces the level of unserved energy relative to planning for random (spatially uncorrelated failures). Planning for geographically correlated failures, however, does not eliminate the susceptability of the joint gas-grid system to spatially uncorrelated failures

RTO Governance Structures Can Affect Capacity Market Outcomes

Regional Transmission Organizations (RTOs), which coordinate delivery for over two-thirds of the electricity consumed in the U.S., are required by the FERC to employ stakeholder-driven mechanisms to establish market and operational rules. These “governance structures” set up a quasi-political process for determining which market rules are adopted and which are not. This study shows how governance systems are not simply administrative constructs but have real impacts – the details of how the market rules are made will ultimately affect market outcomes. Using the capacity market in the PJM Interconnection as a case study, we model the preferences of individual stakeholders over different capacity market designs, under different decision rules for which capacity market design is implemented. We compare capacity market design choices under PJM’s current decision system, which requires a super-majority in a sector-weighted voting context to implement a new market rule, with the decision systems used in the New York ISO and also under systems of preferential voting. This voting model is integrated with a model of capacity market clearing which allows us to demonstrate how different decision systems matter in terms of installed capacity and capacity market outcomes

A Cooperative Game Framework for the Joint Operation of Natural Gas Storage and Electric Power Generation

We develop a cooperative game-theoretic framework for analyzing the impact of natural gas storage on interconnected gas and electricity markets. While increased utilization of gas storage has been proposed as a policy solution to fuel-security concerns in the electric power grid, the mode of interaction between gas storage units and electric power markets has not been investigated and some potential for cross-market manipulation exists. We investigate the potential for collusive behavior between gas storage units and power plants, whereby joint profits in the electricity and gas markets are increased by a strategy that involves the cooperative agents taking a loss in one market to the benefit of the other market. In a static game context, we find that such a strategy increases joint profits in scenarios when peak demand natural gas prices are high and the power plant(s) involved in the cooperative arrangement have relatively low marginal costs. The value of cooperation is not affected by whether gas storage units are physically connected to gas-fired power plants or if gas storage units inject gas into existing pipeline systems. While additional research into the nature of these competitive effects is needed, particularly in a repeated game context, our results point to the need to carefully consider the competitive effects of fuel security measures. A mechanism for monitoring of interactions between gas storage and power plants is likely warranted

When are Decentralized Infrastructure Networks Preferable to Centralized Ones?

Many infrastructure networks, such as power, water, and natural gas systems, have similar properties governing flows. However, these systems have distinctly different sizes and topological structures. This paper seeks to understand how these different features can emerge from relatively simple design principles. Specifically, we work to understand the conditions under which it is optimal to build small decentralized network infrastructures, such as a microgrid, rather than centralized ones, such as a large high-voltage power system. While our method is simple it is useful in explaining why sometimes, but not always, it is economical to build large, interconnected networks and in other cases it is preferable to use smaller, distributed systems. The results indicate that there is not a single set of infrastructure cost conditions that cause a transition from centralized networks being optimal, to decentralized architectures. Instead, as capital costs increase network sizes decrease gradually, according to a power-law. And, as the value of reliability increases, network sizes increase abruptly---there is a threshold at which large, highly interconnected networks are preferable to decentralized ones

The Evolution of Participatory Policy-Making for Regional Power Grids

In the United States, Regional Transmission Organizations (RTOs) are critical for maintaining electric reliability and facilitating the shift toward more efficient and sustainable electric power systems. RTOs are voluntary member-driven organizations that engage hundreds of stakeholders in policy decisions affecting planning, markets, and operations. RTOs have evolved into highly complex and interdependent systems with internal feedback among and within RTO functions, and external feedback from emerging technologies and federal and state clean energy policies. In the PJM Interconnection, the expanded scope of responsibilities, complexity, and member body size has created tensions within the stakeholder processes that has led some to question the efficacy of existing decision-making structures. We develop a case study of recent tensions within the PJM stakeholder process and argue that the source of many of these tensions is a fundamental change in the organizational nature of PJM and other RTOs

Reliability Model of Joint Electricity and Natural Gas System Considering Electric Compressor Failures under Different Network Topologies

We formulate a steady-state operational model for natural gas and electric transmission that is capable of considering bi-directional interdependence. The electric transmission system depends on the gas transmission system to provide fuel to power plants for reliable operations. The gas transmission system depends on the electric transmission system to provide power for some compressors, which ensure sufficient gas deliverability. We illustrate our formulation using a gas-grid test system with realistic properties, that is based on the topology of these networks in the northeastern part of the United States and Canada. Subjecting this test system to failures involving both natural gas and electric transmission demonstrates that having a larger fraction of electric-driven gas compressors (which rely on the power grid) worsens the impact of contingencies, relative to having compressors that use natural gas and on-site engines to run. The extent of this impact is sensitive to both the spatial pattern of gas-fired generation in the power grid, and the spatial distribution of electrified compressors in the gas transmission grid