Leigh Tesfatsion

Centrally-managed U.S. wholesale power markets operating over high-voltage AC transmission grids are transitioning from heavy reliance on fossil-fuel based power to greater reliance on renewable power with increasingly diverse suppliers and customers. This study highlights four conceptually-problematic economic presumptions reflected in the legacy core design of these markets that are hindering this transition. The key problematic presumption is the static conceptualization of the basic product as grid-delivered energy (MWh) transacted in short-run (day-ahead and intra-day) markets at competitively determined unit prices ($/MWh), conditional on delivery location and time. This study argues, to the contrary, that the basic product in need of efficient reliable transaction in these markets is reserve (physically-covered insurance) for protection against power imbalance (volumetric grid risk). This reserve is the guaranteed availability of dispatchable nodal power-production capabilities for possible central dispatch during designated future operating periods at designated grid delivery locations to satisfy just-in-time customer power demands and grid reliability requirements. For illustration, a recently proposed Linked Swing-Contract Market Design is briefly reviewed. The latter design permits dispatchable power resources to offer diverse types of reserve into a centrally-managed collection of linked forward bid/offer-based reserve markets via two-part pricing insurance contracts taking a flexible swing form. The swing in these contracts permits efficient planning for real-time reliability, and the two-part pricing form of these contracts permits cleared suppliers to assure their revenue sufficiency. A principled cost allocation rule supports the independence of the fiducial central manager by assuring break-even revenue adequacy for system operations as a whole.

This study establishes that Locational Marginal Pricing (LMP) is conceptually problematic for grid-supported centrally-managed wholesale power markets transitioning to decarbonized grid operations with increasingly diverse participants, hence with increasingly uncertain and volatile net loads. LMP assigns a common per-unit price LMP(b,T) ($/MWh) to each “next” unit (MWh) of grid-delivered energy, conditional on delivery location b and delivery period T. However, this entails a serious many-to-one benefit/cost measurement error: namely, the valuation of this “next” unit by a market participant or system operator will typically depend strongly on the specific dynamic attributes of the path of power injections and/or withdrawals (MW) used to implement the delivery of this “next” unit at b during T. One option is to muddle through, forcing market participants and system operators to express benefit and cost valuations for “next” units of grid-delivered energy (MWh) in per-unit form ($/MWh) without regard for the true benefits and costs of flexible power delivery. Another option, advocated in this study, is to explore conceptually-coherent nodal multi-interval pricing mechanisms permitting grids to function efficiently as flexibility-support insurance mechanisms, i.e., as mechanisms enabling just-in-time nodal power deliveries to meet just-in-time nodal power demands as well as system reliability requirements.

This study develops a consensus-based transactive energy design managed by an Independent Distribution System Operator (IDSO) for an unbalanced distribution network. The network is populated by welfare-maximizing customers with price-sensitive and fixed loads who make multiple successive power decisions during each Operating Period (OP). The IDSO and customers engage in a negotiation process in advance of each OP to determine retail prices for OP that align customer power decisions with network constraints in a manner that preserves customer privacy. Convergence and optimality properties of this proposed design are established for an analytically formulated illustration: an unbalanced radial distribution network, populated by households, that is electrically connected to a relatively large RTO/ISO-managed transmission network. Numerical test cases are reported for a 123-bus unbalanced radial distribution network that demonstrate these properties.

The general objective of our project has been to investigate the ability of Independent Distribution System Operators (IDSOs), functioning as linkage agents for Integrated Transmission and Distribution (ITD) systems, to facilitate the flexible availability and usage of reserve in support of ITD system operations. This general objective is in accordance with Order 2222 of the U.S. Federal Energy Regulatory Commission (FERC), titled “Participation of Distributed Energy Resource Aggregations in Markets Operated by Regional Transmission Organizations and Independent System Operators”. The Final Rule for FERC Order 2222 was issued on September 17, 2020. The primary contribution of our project is that we have formulated an innovative energy management Transactive Energy Design (TES) approach for ITD systems that provides promising support for our project objective. Specifically, we have developed a new type of IDSO-managed TES design for distribution system operations, as well as new types of swing contracts permitting IDSOs to participate in transmission system operations as providers of reserve harnessed from distribution system resources in return for appropriate compensation. Together, these design elements constitute a scalable market-based approach facilitating efficient reserve procurement for ITD system operations from a fuller range of power resources. The efficacy of our approach has been demonstratedmore » by means of detailed conceptual analyses as well as test case simulations. To implement the latter, we have developed the ITD TES Platform V2.0, a computational platform that permits the modeling and software implementation of ITD system operations over time. The Electric Reliability Council of Texas (ERCOT) energy region has been used as the empirical anchor for the development of this platform. Our conceptual and test-case work has been reported in a Wiley/IEEE Press book, two refereed book chapters, and seven refereed journal articles. The key components comprising the ITD TES Platform V2.0 have been released as documented open-source software at online GitHub repositories. « less

This study demonstrates how bid-based transactive energy system designs can be formulated from a customer-centric vantage point to encourage voluntary customer participation. Supportive evidence is provided for distribution systems populated by households with smart electric heating, ventilation and air conditioning systems. The optimal form of a household’s bid function is first derived from dynamic programming principles, based solely on the household’s general thermal dynamic and welfare attributes. The quantitative form of this optimal bid function is then explicitly derived, given quantitative forms for these attributes. A method is also developed for the systematic construction of household types based on these attributes. Bid comparison, peak load reduction, and target load matching test cases conducted for a 123-bus distribution system illustrate the usefulness of these methods for ensuring bid-based transactive energy system designs are able to align system goals and constraints with local customer goals and constraints.

Agent based modeling (ABM) is a standard tool that is useful across many disciplines. Despite widespread and mounting interest in ABM, even broader adoption has been hindered by a set of methodological challenges that run from issues around basic tools to the need for a more complete conceptual foundation for the approach. A er several decades of progress, ABMs remain di icult to develop and use for many students, scholars, and policy makers. This di iculty holds especially true for models designed to represent spatial patterns and processes across a broad range of human, natural, and human-environment systems. In this paper, we describe the methodological challenges facing further development and use of spatial ABM (SABM) and suggest some potential solutions from multiple disciplines. We first define SABM to narrow our object of inquiry, and then explore how spatiality is a source of both advantages and challenges. We examine how time interacts with space in models and delve into issues of model development in general and modeling frameworks and tools specifically. We draw on lessons and insights from fields with a history of ABM contributions, including economics, ecology, geography, ecology, anthropology, and spatial science with the goal of identifying promising ways forward for this powerful means of modeling.