CS19: Energy System Modeling and Innovation

p.p1 {margin: 0.0px 0.0px 12.0px 0.0px; font: 12.0px Times; color: #000000}
Global energy firms are increasingly reallocating capital beyond traditional upstream and downstream activities in response to decarbonization pressures and rapid technological change. While existing research has focused primarily on financial flows into renewable energy sectors, less attention has been paid to how energy corporations allocate capital across industries and how such cross-industry allocation contributes to structural transformation within the energy economy.
This study analyzes cross-industry capital allocation by global energy firms between 2005 and 2024. It distinguishes between industrial relatedness and technological proximity as alternative drivers of investment flows and examines how repeated cross-sectoral allocations accumulate to alter the structure of the energy industry. By integrating industry-distance measures with text-based technological similarity metrics, the analysis identifies whether capital reallocation follows existing sectoral boundaries or reflects capability-based expansion across structurally distant industries.
Industry relatedness is measured using NAICS-based industry distance, and technological proximity is estimated through text-based similarity measures. The results reveal a systematic shift of capital toward technology-intensive sectors such as digital infrastructure, advanced manufacturing, and electrical equipment. Although many investments target industries that are structurally distant from traditional energy sectors, they exhibit high technological similarity, indicating capability-aligned capital reallocation rather than unrelated diversification. Network analysis further shows rising centrality of digital and manufacturing clusters, suggesting an ongoing reconfiguration of sectoral boundaries and industrial structure within the global energy economy.

This paper examines the impact of regulatory announcements on methane emissions and evaluates the economic potential for methane abatement in US oil and gas basins. We first conduct an event study analysis of an adopted but not yet implemented US regulation that would impose substantial fees on methane super-emitters. The results suggest that the implicit tax signal embedded in the regulation announcement far exceeds the marginal abatement cost for a substantial share of installations, although this estimate reflects only a single average point on the cost curve. To capture the full distribution of costs, we then construct marginal abatement cost curves for the Permian, Appalachian and Anadarko U.S basins. This expanded analysis reveals sizeable "missed-money" opportunities: approximately 8% of methane emissions could be abated at zero net cost and nearly 50% could be avoided for less than 1.5 USD/t CO2e. These cost estimates are significantly lower than recent estimates, revealing considerable untapped potential for cost-effective methane mitigation.

Exceptional renewable resources, recent system-wide blackouts, and electricity tariffs that have doubled in recent years create a strong incentive for investment in distributed energy resources (DER) in Chile. This study evaluates the profitability and self-sufficiency of optimally designed DER under Chile's evolving net billing context. The analysis covers multiple geographical locations across Chile, reflecting the country's wide diversity of renewable resources and electricity tariffs. We model the joint optimal sizing and energy management of the DER investments by minimizing total customer electricity costs. A mixed-integer linear programming (MILP) model is developed to perform the simulations. The investments may include on-site solar PV, wind generation, and battery energy storage systems (BESS). 


We found significant levels of self-sufficiency driven by optimally sized solar and wind investments across the country. Solar investments dominate in northern Chile, whereas wind investments are more competitive in the south. The assessed business models exhibit strong financial returns and short payback periods, highlighting DER as attractive investments for residential, commercial, industrial, and aggregated customers. Finally, we analyze how the economic value of DER for customers aligns with its broader system-level value, with particular attention to the ongoing electricity distribution regulation reform in Chile.


We conclude by recommending the promotion of new aggregated energy arrangements. Policy efforts are required to streamline grid-connection administrative processes and enhance the remuneration of DER exports to the grid. Currently, exported DER energy is charged grid tolls associated with the entire transmission and distribution infrastructure. However, in most cases these exports predominantly utilize only the local low-voltage grid. Revising these grid charges, together with the introduction of appropriately designed peak-demand charges for aggregated customers, could significantly accelerate DER deployment in Chile.

Suriname with its 600 thousand inhabitant at the northern cost of South America, has presented its Nationally Determined Contributions (NDC) to attend the Paris Agreement of the United Nations Framework Convention on Climate Change, where it has stated his contribution to embody efforts to reduce national emissions and adapt to the impacts of climate change. Suriname's Second Nationally Determined Contribution (NDC) places the electricity sector at the center of its climate–development agenda, committing to sustain and expand renewable generation capacity to 35% by 2030 while safeguarding affordability, reliability, and macroeconomic stability. Achieving this ambition requires moving beyond headline targets toward a system-wide assessment of capacity expansion, infrastructure readiness, investment sequencing, and institutional feasibility under uncertainty. This study develops a policy-relevant gap analysis of Suriname's NDC trajectory within an integrated energy-economics framework anchored in Open Source Energy Modeling System (OSeMOSYS). This framework determines through Linear Programming the most cost-effective option, considering economic, environmental and other user defined constraints. The OSeMOSYS model covers the actual and planned generating capacity, transmission and distribution network, and consumer expansion expectation based on three scenarios: (i) Business-as-Usual (BaU), reflecting continuation of current pipelines; (ii) High-Demand (HD), stress-testing adequacy under accelerated load growth as expected to occur due to offshore oil and gas exploration in the Guiana basin; and (iii) High-Demand/Emission-Constrained (HD/EC), examining implications of tighter decarbonization requirements for technology choice, system configuration, and cost structures. By integrating least-cost optimization with scenario-based stress testing, the analysis strengthens alignment between national climate commitments and electricity-sector planning. OSeMOSYS shows the gap in proposed targets and scenarios outcomes and provides data driven decision support for government, utilities, financiers, and development partners to operationalize Suriname's renewable-energy commitments toward 2030.

Electric vehicles (EVs) can become a distributed source of electricity storage through Vehicle-to-Grid (V2G), a socio-technical arrangement that enables EVs to modulate charging and discharge electricity back to the grid. While the theoretical benefits of V2G for flexibility provision and decarbonization have been widely acknowledged, the economic relationship between EV owners and the intermediaries providing V2G services remains under-theorized. Much of the existing literature adopts ad hoc assumptions regarding compensation schemes, risk allocation, and participation incentives. This gap limits our understanding of recently emerging V2G business models, many of which diverge substantially from stylized theoretical designs. In this paper, we develop a formal framework grounded in mechanism design theory to analyze how different combinations of business model dimensions allocate value and risk between EV owners and service providers. We model the interaction as a principal–agent problem with participation and incentive compatibility constraints, allowing us to characterize which configurations are viable under asymmetric information and uncertainty. We then implement a simulation calibrated with empirical data to compare existing V2G business models in terms of expected value creation and risk sharing. Our results show that current business models differ significantly in how they distribute market and operational risks. Importantly, those models that explicitly remunerate EV owners for electricity discharged to the grid exhibit greater potential to align private incentives with system-level decarbonization objectives. Our findings contribute to the economic design of V2G markets and provide guidance for firms and policymakers seeking to scale V2G deployment.