Energy transition in resource-constrained regions faces particularly severe challenges. This paper focuses on regions characterized by coal scarcity, lack of oil, limited gas reserves, and constrained renewable energy endowments, constructing a simulation model for regional low-carbon energy transition pathways that considers incoming electricity from imported sources. It also proposes a comprehensive assessment indicator system encompassing multiple dimensions such as energy, emissions, and economy for the transition pathways. Taking a certain resource-constrained province in middle China as a case study, the paper designs representative low-carbon energy transition pathways for the province's unique resource characteristics, conducts simulation exercises and quantitative assessment of these pathways, and carries out sensitivity analyses on parameters like coal price, carbon quota baseline, imported electricity price, and utilization hours of new energy sources. The computational examples demonstrate that the simulation model and indicator system developed herein can provide substantial support for the quantitative assessment of low-carbon energy transition pathways in resource-constrained regions.

Planning the low-carbon transition pathway of the power sector to meet the carbon neutrality goal poses a significant challenge due to the complex interplay of temporal, spatial, and cross-domain factors. A novel framework is proposed, grounded in the cyber-physical-social system in energy (CPSSE) and whole-reductionism thinking (WRT), incorporating a tailored mathematical model and optimization method to formalize the co-optimization of carbon reduction and carbon sequestration in the power sector. Using the carbon peaking and carbon neutrality transition of China as a case study, clustering method is employed to construct a diverse set of strategically distinct carbon trajectories. For each trajectory, the evolution of the generation mix and the deployment pathways of carbon capture and storage (CCS) technologies are analyzed, identifying the optimal transition pathway based on the criterion of minimizing cumulative economic costs. Further, by comparing non-fossil energy substitution and CCS retrofitting in thermal power, the analysis high-lights the potential for co-optimization of carbon reduction and carbon sequestration. The results demonstrate that leveraging the spatiotemporal complementarities between the two can substantially lower the economic cost of achieving carbon neutrality, providing insights for integrated decarbonization strategies in power system planning.

Under the “dual-carbon” targets, the coal power industry faces significant challenges in low-carbon transition, with carbon capture, utilization, and storage (CCUS) technologies as a key solution for emission reduction and energy security. Existing evaluation methods lack comprehensive assessments of technical, economic, and environmental synergies. This study proposes a dynamic three-dimensional framework integrating technical, economic, and emission indicators. By using Monte Carlo simulation and K-means clustering, the framework captures technology degradation and market fluctuations. Results show compression energy consumption averages of 0.37 ± 0.07 GJ/tCO2, with capture rates above 94%, increasing the variability by 35%. Lifecycle costs can be reduced by 24% at carbon prices of 80–100 USD/tCO2 with optimal subsidies. Emission costs peak alongside carbon prices above 430 USD/t, suggesting the need for tiered carbon pricing and CAPEX subsidies. A cluster analysis divides CCUS into high-capture-high-energy, balanced, and low-efficiency types, supporting differentiated policies such as tiered carbon pricing and phased subsidy withdrawal. This research offers actionable insights to balance economic viability and carbon neutrality goals.

The nuclear event risk (NER) is an important and disputed factor that should be reasonably considered when planning the pathway of nuclear power development (NPD) to assess the benefits and risks of developing nuclear power more objectively. This paper aims to explore the impact of nuclear events on NPD pathway planning. The influence of nuclear events is quantified as a monetary risk component, and an optimization model that incorporates the NER in the objective function is proposed. To optimize the pathway of NPD in the low-carbon transition course of power supply structure evolution, a simulation model is built to deduce alternative NPD pathways and corresponding power supply evolution scenarios under the constraint of an exogenously assigned carbon emission pathway (CEP); moreover, a method is proposed to describe the CEP by superimposing the maximum carbon emission space and each carbon emission reduction (CER) component, and various CER components are clustered considering the emission reduction characteristics and resource endowments of different power generation technologies. A case study is conducted to explore the impact of NER and its risk valuation uncertainty on NPD pathway planning. The method presented in this paper allows the impact of nuclear events on NPD pathway planning to be quantified and improves the level of coordinated optimization of benefits and risks.

The long-term evolution of coal power installed capacity in the physical dimension is affected by social factors such as coal-related policy mechanisms (carbon pricing and capacity electricity prices) and the decommissioning decision of existing coal power. Under the guidance of the Cyber-Physical-Social system in Energy (CPSSE), a hybrid simulation model covering coal power policy, existing coal power decommissioning decision, and long-term evolution of coal power installed capacity is established. The evolution process of the long-term financial condition and decommissioning time of each coal power plant with different carbon emission costs and capacity price revenue are obtained by the simulation model. And impact of coal power plant decommissioning on the long-term power generation balance of the whole system are analyzed. The results show that high carbon emission costs may have a fatal impact to the financial condition of coal power plants, and the resulting large-scale decommissioning in advance of coal power plants can cause long-term power generation balance risks of the whole system, and a reasonable capacity price can help to address the above risks.

Coal power units combined with carbon capture and storage (CCS) technology can provide indispensable flexible low-carbon power for the reliable operation of new energy-dominated power systems. Besides, they are one of the most important technical ways for low-carbon development of power generation companies under the goal of carbon neutrality. However, due to the high cost of CCS at this stage, corresponding incentive policies must be introduced to promote the development of coal power CCS for power generation companies. Quantitative assessment of the impact of large-scale CCS development on the low-carbon transition path and economic benefit of power generation companies is the key to supporting relevant policy decisions. Based on the technical-economic-emission simulation model of power generation company transition considering CCS, this paper obtains the power, emission, and economic indicators of a power generation company under multiple typical CCS development pathways through simulation, realizes the quantitative evaluation of the low-carbon transition pathway of power generation companies considering CCS, and provides decision-making support for the optimization of CCS development strategy and related policies.

The long-term evolution of new energy power generation capacity in the physical dimension is affected by social factors such as new energy policies and investment behavior of power generation companies (GENCOs). Under the guidance of the Cyber-Physical-Social System in Energy (CPSSE) framework of energy, a hybrid simulation model that can simulate the dynamic interaction between wind power feed-in tariff policies, investment behaviors of GENCOs and long-term evolution pathways of new energy power generation capacity is established, and a sand-table deduction of feed-in tariff policy optimization is carried out using wind power as an example. A feed-in tariff policy optimization method based on the idea of “feedback” is realized, in which the feed-in tariff policy adjustment target is set to make up for the gap between the actual development pathway and the planned pathway of new energy, using the information of new energy power generation cost and GENCOs investment behavior. The results of sand-table deduction verify the effectiveness of the proposed method.

The goal of carbon neutrality poses significant challenges and opportunities to traditional coal production, processing, and utilization enterprises. Carbon capture, utilization, and storage (CCUS) is a critical option to reduce carbon emissions for coal-based enterprises. Based on enterprise data and geological data, this study quantitatively evaluates the techno-economic feature and potential of CCUS in China Energy Group using sys-tematical source-sink matching and carbon reduction contribution methods. With the current technical level and only considering the scenario of CO2-enhanced water recovery (CO2-EWR), an enterprise using CCUS to reduce CO2 is feasible. About 73% of the installed capacity of the enterprise is suitable for CCUS, and the cumulative CO2 emission reduction is more significant than 580 Mt/a with 135 g/kWh of the final CO2 emission intensity. Additionally, the emission reduction contribution of CCUS is predicted to be 10%-29.5% from 2020 to 2060. The cost of full-chain CCUS in the enterprise is controllable. The levelized avoidance cost (LAC) of coal chemical plants with a high concentration of CO2 is less than 23 USD/t, the average LAC of coal-fired power plants is 68.6 USD/t, and the average levelized additional cost of electricity is 52.9 USD/MWh. Taking the local feed-in tariff as a standard, the cost of EWR is more competitive than the cost of wind and solar power generation combined with energy storage technology. Considering technological advances and the CCUS hub, which uses common infra-structure to transport and store CO2, EWR costs for coal-fired power will be drastically reduced. Coal-based enterprises can prioritize deploying low-cost CO2-EWR demonstration projects, research and develop key tech-nologies, and form full-chains integrated systems and the CCUS hub. This study provides a basis for coal-based enterprises to reduce large-scale emissions and develop low-carbon transformation through CCUS technology.

Nuclear power development is a complex issue spanning cyber, physical, and social systems that is essential to achieving energy security and climate goals. With the ongoing worldwide trend towards carbon neutrality, the positioning of nuclear power in energy mix should be reconsidered. This paper aims to present a systematic review of current research on optimization of nuclear power development. The concept of cyber - physical - social system in energy (CPSSE) is adopted, which provides a suitable perspective and enables the review of relevant studies to achieve some novel insights. Based on the CPSSE, firstly, a research framework is established and the main research elements in optimization are identified, followed by a proposed conceptual risk-based optimization model. Secondly, current studies are analyzed and classified into four categories according to the research boundary. The status quo and limitations are discussed. It is found that the research results of nuclear-specific issues have not been well integrated into the optimization of nuclear power. As a relatively reliable power supply, nuclear power is capable of maintaining power and electricity adequacy of the whole system, especially in the case of power shortage caused by long-period low output of renewable energy or extreme external disasters. This superiority should not be ignored in the optimization. Other critical factors that should be further considered include disruptive technologies, nuclear safety, energy policies, and stakeholder behaviors. Finally, suggestions are given for future research.

信息-物理-社会系统(CPSS)是在信息物理系统(CPS)的基础上,加入政策、行为等社会元素,将广义物理系统视作一个整体,并消除不同领域之间的壁垒.相关的研究和应用都离不开仿真工具的支持.为此,在近20年探索能源的信息-物理-社会系统(CPSSE)过程中研发了统一的仿真平台(Sim-CPSS).Sim-CPSS支撑了异构仿真应用的互通、互动、互用,并显著降低了复杂系统仿真研究的难度,提高了分析效率.文中介绍了Sim-CPSS的研发思路、架构、功能和原创技术.通过能源领域的众多工程应用验证了其对多领域、多尺度,以及行为多种表达方式的适应能力.Sim-CPSS为CPSS提供了基础工具的强大支撑.

Endogenous learning curve (endogenous method) and set value exogenously (exogenous method) are two widely used methods for non-fossil energy cost experience curve in energy transition research based on quantitative model. The difference between endogenous method and exogenous method on total energy investment cost are compared, and the effect of key factors such as the learning rate of endogenous curve, cumulative installation capacity of the electricity supply technology, growth pathway of the electricity supply technology are analyzed. Recommendation for pay more attention to the effects of different cost experience curves on results of quantitative models are made for better decision-making support.

The incentive policies for non-fossil energy are important factors affecting the investment behavior of generation companies (GENCOs). However, the investment behavior of different types of GENCOs in the system could be quite different, so the implementation of the policy must consider how to achieve incentive compatibility with the investment behavior of GENCOs. This article constructs a power transition simulation model that considers the investment behavior of GENCOs. Taking the wind power feed-in tariff policy as an example, it analyzes the impact of policy on the whole system’s low carbon transition pathway of the power structure and the evolution trajectory of system carbon emissions under different behavior scenarios.

Carbon Capture, Utilization and Storage (CCUS) is one of the key technologies for realizing large-scale low-carbon utilization of coal-fired power plants in service. How to evaluate its economics is crucial to the decision-making of traditional coal-fired power enterprises. This paper analyzes the changes in the physical, emission and economic parameters of in-service coal-fired power plants without and with the CCUS retrofit. A method for evaluating the economic feasibility of coal-fired power plants retrofitting based on net cash flow is proposed, which compares the impact of CCUS retrofit on the net present value of the remaining life cycle of the power plant. The impact of uncertain parameters such as carbon dioxide sales unit price, carbon capture device operating cost, free carbon quota, and carbon emission right price on the evaluation results are analyzed.

The quantitative analysis of the low-carbon energy transition is crucial for providing decision-support for energy planning and policy-making. This study presented an approach for quantitative analysis of energy transition, involving dynamic simulation model, mathematical methods of describing the energy transition targets and pathways, boundary condition, and evaluation indicators. The transition targets of Baseline scenario were set following the Energy Production and Consumption Revolution Strategy (2016-2030) (hereinafter referred to as the Energy Strategy) promulgated by the Chinese government. Four comparative scenarios were generated by adjusting the targets of the total primary energy consumption and the proportion of power generation. The carbon emissions and economic costs were calculated based on the quantitative dynamic simulation model. In the study, an attempt was made to explain whether China's cumulative carbon emissions following the Energy Strategy match the emission quotas under the global 2 degrees C temperature rise target. Furthermore, the future research direction for low-carbon transition was also analyzed.

The optimization of trans-regional electricity transmission scale of China’s Western renewable energy base is crucial to drive China's energy revolution. Currently, the regional power planning or optimization is aimed at minimizing the total economic cost, without taking the cost and benefit of transregional electricity transmission into account. In this paper, a regional planning model considering the cost and benefit of trans-regional electricity transmission was proposed, and the target of trans-regional electricity transmission scale by 2050 was optimized. This study analysed the influence of carbon price, fossil fuel scarcity value, accommodation cost for renewable power on the optimized result of trans-regional electricity transmission scale. Furthermore, the policy implication of the research was also analysed.

The clean transition of GenCo is affected by various uncertainties such as strategies of other participants, power grid development, policies, and power demand, among which, being the most direct stakeholders in electricity market, other participants’ generation investment is crucial. This paper simulates the dynamic trajectories of installed capacity, power generation, as well as annual average coal consumption rate of China’s power supply structure from 1985 to 2015, and the dynamic transition process of a traditional coal-dominated GenCo from 2016 to 2030. Based on simulation, this paper comprehensively evaluates the impact of other participants’ generation investment on clean transition of GenCo, and quantitatively analyzes the robustness of a given clean transition strategy in different scenarios. The results achieved by quantitative analysis of simulation can provide decision support for GenCos’ decision makers.

The clean transition of traditional coal-dominated GenCos plays critical role in national energy transition. However, the formulation of strategy is dominated by qualitative analysis, which lacks the ability to quantify key operation indicators in a complex transition process. This paper develops a computer simulation tool for the study of medium and long-term transition of GenCo to simulate the dynamic process of its clean transition. Under the background of clean transition in China’s power sector, it quantitatively analyzes the dynamic performance such as business structure, profit, and carbon emission of a traditional GenCo according to its 2020 and 2030 clean development strategic targets, and compares the differences between different pathways under the same strategic targets. And then, this paper analyzes the impact of uncertainties such as coal prices and renewable energy subsidies.

This paper extracts the elements of energy transition issue,emphasizing that the behaviors of stakeholders such as policy makers,and energy suppliers can impact the energy transition dynamic significantly.The main aims(explanation, prediction,projection,and optimization),contents,and challenges of energy transition researches are presented,and the state-of-the-art research paradigms for energy transition and their limitations on addressing the challenges introduced by human behaviors are reviewed.Finally,this paper suggests a new research paradigm,hybrid simulation of technology-economic-behavior model with human participants,in which the energy transition target and pathway is optimized by repeatedly carrying out experimental economic simulation.The subsequent paper will discuss the uncertainties and analysis approaches in the energy transition researches.

The low-carbon transition of the power system plays critical role in energy system transition. In 2016, the Chinese government proposed an ambitious low-carbon energy transition strategy by 2030. However, relevant researches remain at the level of qualitative analysis. This paper proposes a quantitative analysis approach for assessing China’s power sector transition strategy based on a dynamic simulation model. This appraisal method translates the transition target of non-fossil energy generation in 2030 into a series of plausible pathways. Through the dynamic simulation model, the economic costs and carbon emissions of each transition pathway are evaluated. The simulation results give a range of the total system costs and carbon emissions of China’s transition to a low-carbon power system during the transition period of 2016 to 2030.

Uncertainties,especially the uncertainties of human behavior,introduce great challenges to energy transition analysis.This paper discusses the nature of uncertainty in terms of randomness and vagueness;analyzes the sources of uncer-tainty in terms of model and parameters,operation conditions,disturbances(failures),viewpoints of stakeholders,and human behaviors;and classifies the uncertainty into different categories based on cognitive level.The-state-of-the-art of uncertainty analysis approaches for energy transition and their limitations are reviewed.Aiming to address the chal-lenges introduced by large amount of uncertainties with various characteristics,a comprehensive analysis framework that integrates multiple approaches is proposed to give consideration to both the rapidity and accuracy of the uncer-tainty analysis simultaneously.