Transmission planning has historically been driven by reliability, economics, and land avoidance-based policy – meaning planners exclude vast geographical areas from the planning process. However, a growing body of evidence suggests that there are a multitude of landscape-based benefits associated with electric transmission. The purpose of this work is to help planners, policy makers, and researchers better understand how landscape benefits might be included in transmission planning. The fundamental question this work seeks to answer is “what are the opportunities and challenges associated with including landscape benefits in transmission planning?”. Recent research shows that transmission rights-of-way have the potential to provide a broad range of benefits beyond those commonly recognized today such as reliability and economics. These additional benefits include habitat and pollinator support, recreation, wildfire risk reduction, stormwater and heat mitigation, and local economic opportunities. Recent policy changes, such as the Federal Energy Regulatory Committee’s Order 1920 that requires transmission planners to maximize the benefit of transmission projects, provide an opening to integrating non-traditional benefit accounting in formal transmission planning processes. This work identifies a broad range of potential landscape benefits in existing academic and industry literature. Furthermore, it initiates the process of developing conceptual frameworks for determining 1) how difficult specific landscape benefits are to measure with existing tools, data, and techniques, 2) what techniques are most appropriate for measuring landscape benefits, and 3) how landscape benefits might be combined with traditional metrics in industry-grade transmission planning tools.
We assess whether current public support mechanisms for CO2transport infrastructure align with the economics and maturity of the emerging carbon capture and storage (CCS) industry, and identify more effective policy design principles. The investment risk associated with transport storage (T S) infrastructure is a main barrier to scaling CO2 transport networks, yet dominant policy instruments (volumetric subsidies for capture) do not address this constraint. State-led approaches can enable final investment decisions but may create long-term subsidy dependence, while purely regulatory frameworks can provide long-term certainty without overcoming the initial chicken-and-egg problem. Drawing on the economics of CO2 networks, evidence from CCS governance, and lessons from offshore wind and long-duration energy storage, we argue that effective CCS policy should prioritize de-risking T S investment at early stages, in particular through socialization of network costs, before transitioning toward performance-based instruments as the market matures.
The goal of the paper is to analyse the Iberian blackout and determine its direct and underlying causes. We ask the questions: Are renewables to blame? Are other systems with high renewable penetration in danger of a blackout? There are few publications analysing the blackout. Only one discusses lessons for modern power systems and policy implications. The direct cause of the Iberian blackout was an unexpected interaction between oscillations and voltage stability compounded by inadequate voltage control arrangements in Spain. However, the underlying cause is that Spain has concentrated in recent years on increasing the share of renewables but seems to have paid less attention to adapting power system operation and control to the changing needs. The rapidly increasing share of renewables in many power systems causes a profound change in the way power systems behave, which we do not yet fully understand. Hence a significant interdisciplinary effort of academia and industry is required to overcome the challenges and prevent future blackouts.
Given the impact of climate change on electricity supply and demand, nations need to adapt their power sectors to enhance system resilience and manage demand. Although the importance of such adaptation is increasingly recognized, relatively few studies have explicitly used energy system optimization to identify adaptation strategies, particularly in the Global South despite high exposure to climate hazards, and no comprehensive review has examined how such quantitative, optimization-based assessments have been conducted across different regions. This paper reviews studies that quantify the impacts of climate change on electricity generation and demand and use these assessments in energy models to optimize adaptation strategies and determine the optimal power supply mix under climate change. This review addresses three key questions: (1) Which regions have identified adaptation strategies under different climate change scenarios, and where do evidence gaps remain for planning? (2) What are the main similarities and differences in the proposed power supply mix across regions, and what factors explain these patterns? (3) For the same region, have different optimization models produced different power supply mixes, and what drives these differences? Our review shows that a technology may retain a share in the power mix of a region even when negatively affected by climate change, that model and tool choice can strongly influence adaptation outcomes, and that multi-model comparison is important for better capturing uncertainty. This study underlines the value of local leadership and research in supporting adaptation planning, shows that forward-looking modeling can reveal outcomes beyond current expectations. Overall, the review provides transferable insights for regions where adaptation modeling remains limited. Future research should expand regional coverage and incorporate broader adaptation options and multi-model approaches to better capture uncertainty.
Driven by the global transition toward carbon neutrality, power systems with high penetration of variable renewable energy are confronted with dual challenges: hourly power imbalance induced by short-term renewable fluctuations, and seasonal energy mismatch caused by inter-month and inter-annual climatic variations. This paper systematically reviews the state-of-the-art multi-timescale risk-aware planning methods, and this review systematically identifies three critical research gaps in current studies. On this basis, it develops an integrated analytical framework embedded with Conditional Value at Risk (CVaR) for quantitative comparative verification. This work aims to elucidate the risk hedging effect of dual-timescale coordination, and provide methodological reference for flexible resource allocation in high-renewable power systems. Existing studies have made substantial advances in single-timescale risk measurement and stochastic planning, and the hybrid-resolution modeling scheme that couples hourly operational simulation with multi-scenario monthly energy balance has been widely acknowledged as an effective approach to strike a balance between simulation fidelity and computational tractability. As a coherent risk measure, CVaR has been extensively applied in short-term dispatch and long-term planning respectively, but systematic research on its nested deployment across dual timescales within a unified optimization framework remains absent. This paper embeds CVaR into both hourly operational constraints and monthly energy balance constraints, realizing the coordinated quantification of short-term load-shedding risk and long-term energy shortage risk. Comparative case studies on the Garver-6 and Modified 14-bus TEP benchmark system validate that the proposed dual-timescale risk planning scheme can effectively optimize the trade-off between system economy and tail risk, significantly improve renewable energy consumption rate, and enhance power supply reliability, with a slight and reasonable increase in levelized cost of electricity.
