Low-carbon Energy System Research Articles

A prospect-theoretic game approach to demand response market participation through energy sharing in energy storage systems under uncertainty

The Paris Agreement, which is carried out in a bottom-up manner, is giving great vitality to the transition to low-carbon energy system. Accordingly, as the spread of renewable energy increases, securing flexibility resources is emerging as a keyword in the power system and power market, and many studies on demand response (DR) and energy storage system (ESS) classified as demand-side flexible resources are being conducted. However, most of the studies on DR are on voluntary DR programs that participate through bidding among incentive-based DR or price-based DR programs, and ESS faced difficulties in its distribution due to low economic feasibility. Therefore, in this work, we propose a feasible process for participating in a reliability DR program that guarantees high profitability but involves high uncertainty, and non-cooperative game model is suggested to mitigate the uncertainty through surplus electricity-trading model of ESS. In addition, a subjective decision-making based on prospect theory is proposed to reflect the impact of the uncertainty about the incentive-based program’s engagement. Case study results performed in an environment formed based on actual operation data of the Korean DR market prove that participants’ uncertainty is mitigated when participating in the DR market through power trading of ESS through the proposed model. In addition, a small-scale ESS with an average benefit–cost ratio of 0.78 improves by up to 1.08 (1.04 with a standard scenario).

Operation strategy optimization of combined cooling, heating, and power systems with energy storage and renewable energy based on deep reinforcement learning

Combined cooling, heating, and power (CCHP), coupled with renewable energy generation and energy storage can achieve a low-carbon, multi-energy complementary, and flexible energy system. However, the inclusion of renewable resources and energy storage poses significant challenges to the operational management of such systems. Conventional algorithms are limited when solving nonlinear and uncertain non-convex optimization problems thus, deep reinforcement learning (DRL) is considered the most effective method to solve these issues because of its powerful nonlinear fitting ability, model-free utilization, and capability of solving decision-making problems. This study proposes a novel operation strategy optimization model based on DRL to minimize the operation cost of an energy system, which composes of CCHP, photovoltaic generation and energy storage system. The optimization problem was transformed into a Markov decision process (MDP), and the state space and action space are differently modeling in summer and winter scenarios. Two models of handling action constraints are proposed and testing in terms of performance. Two DRL algorithms, Deep Deterministic policy gradient (DDPG) and Twin Delayed Deep Deterministic policy gradient (TD3), were verified separately via comparison with the conventional algorithms, particle swarm optimization (PSO) and mathematical programming under perfect input conditions. Results show that setting different training environments for summer and winter respectively can get better optimization results, and the model with better performance in handling action constraints was validated from the operation strategy and optimization results. The performance of the TD3 method is comparable to the theoretical benchmark, with an average error of approximately 5%. The computation time for a single-step online decision is only 0.001s and for a 24-step online decision is only 0.006s, it significantly improves operational efficiency, demonstrating the adaptability of DRL methods for optimization and computational performance.

Shale gas production evaluation framework based on data-driven models

Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system. Sharp decline of gas production has been widely observed in shale gas reservoirs. How to forecast shale gas production is still challenging due to complex fracture networks, dynamic fracture properties, frac hits, complicated multiphase flow, and multi-scale flow as well as data quality and uncertainty. This work develops an integrated framework for evaluating shale gas well production based on data-driven models. Firstly, a comprehensive dominated-factor system has been established, including geological, drilling, fracturing, and production factors. Data processing and visualization are required to ensure data quality and determine final data set. A shale gas production evaluation model is developed to evaluate shale gas production levels. Finally, the random forest algorithm is used to forecast shale gas production. The prediction accuracy of shale gas production level is higher than 95% based on the shale gas reservoirs in China. Forty-one wells are randomly selected to predict cumulative gas production using the optimal regression model. The proposed shale gas production evaluation framework overcomes too many assumptions of analytical or semi-analytical models and avoids huge computation cost and poor generalization for numerical modelling.

Designing residential energy systems considering prospective costs and life cycle GHG emissions

Novel energy technologies are typically associated with large investments and environmental impacts generated in the construction phase. In this work, we present a systematic approach to optimally design residential energy systems, considering (prospective) costs and life cycle greenhouse gas (GHG) emissions of a large set of low-carbon energy technologies and sources. To achieve this, an optimization problem has been formulated and is tested on several scenarios considering climate-specific heat and electricity demand as well as scenario-specific conditions, such as the flexibility of grid electricity tariffs and associated GHG intensities. With GHG-intensive grid electricity supply and flexible energy tariffs, we recommend to implement policy measures to encourage the investment in residential solar PV-coupled batteries and heat pumps, especially in the near future. The inclusion of environmental impacts generated from the production of energy technologies cannot be neglected; they should be considered during the design phase of residential energy systems. Current high electricity and natural gas prices result in the installation of low-carbon energy system components. This implies that battery systems are already an effective option to reduce the reliance on carbon-intensive and expensive energy supply. And lastly, the large-scale deployment of residential lithium-ion batteries might be limited by global lithium production. This implies that energy system designers should consider alternative electricity storage technologies in their energy technology portfolio.

Implementation of a Just Green Transition: Notions and Risks

The paper discusses opportunities and risks in making just green transitions. Existing notions of justice and results of studies of established unfavorable processes in different countries, such as insufficient support of affected groups, mechanisms of rent extraction and corrupt practices, are analyzed. The review outlines serious challenges to the necessary transitions to low carbon energy systems. On this basis, the study argues for the need to build public capacity through a preliminary and consistent framework that clearly outlines pro-development notions of justice, meaningful alignment of social and environmental goals, and honest monitoring of potential problems, along with solutions to overcome them.

Side Effects of Wind Energy: Review of Three Topics—Status and Open Questions

Wind energy is considered a pillar of the low-carbon energy system of the future. Whereas the side effects and social costs of fossil energy sources (coal, oil and gas), as well as those of nuclear energy, are well-documented and quantified, understanding of the analogous questions with respect to wind energy is far less advanced. However, such understanding is crucial in order to minimize the influence of wind energy on the environment and to compare its social costs with those of conventional energy sources. Here, we summarize the state of knowledge of three side effects of wind energy that have not been convincingly evaluated to date. We focus our analysis on three topics, namely (1) the impact of wind energy on insects; (2) the impact of wind energy on the spatiotemporal distribution of air velocity, temperature, moisture and precipitation in the vicinity of wind parks; and (3) the impact of wind energy on humans through noise emission. For each topic, we formulate open research questions that should be addressed by responsible policy incentives in order to comprehensively assess the social costs of wind energy and to develop wind farms with minimal impact on their environment.

Framing climate strategy of the oil industry of China: A tailored approach to ecological modernization

China has announced its ambitious targets of attaining a carbon peak before 2030 and achieving carbon neutrality by 2060. Although China is a developing country, its oil sector plays a key role in carbon emissions and thus has a responsibility toward climate change. It is very important to understand the role of the oil industry of China in climate governance. This raises the following question: how have oil companies in China framed and tailored their climate strategies? By employing the concept of ecological modernization as a theoretical framework, this study observes the driving forces of climate policies, low-carbon energy, advanced technologies, and market mechanisms by collecting and analyzing reports published by three oil companies. The main findings are that state-owned oil companies in China have adopted the ideas and institutions of national climate strategies, low-carbon energy systems, and emerging financial and market tools. The analysis of the reports reveals that the main motives for the climate strategies of the companies are China’s administrative system, international climate cooperation, the transformation of the energy mix, and emerging market mechanisms.

China's hydrogen development strategy in the context of double carbon targets

As a clean, low-carbon, efficient and renewable energy source, hydrogen has gradually become an important energy carrier to combat climate change and achieve sustainable development in the world. China is now facing the stress of realizing the carbon peak and carbon neutrality goals, where hydrogen will play a significant role. Against this backdrop, to develop China's hydrogen strategy under the carbon peak and carbon neutrality goals, this paper explores the hydrogen resource endowment in China, presents the concepts such as Hydrogen Ethics and the Hu's Hydrogen Line, and discusses the status quo and existing advantages in hydrogen production, storage, transport and utilization in China. Six major obstacles and challenges that China's hydrogen energy industry is facing are pointed out, i.e. cost problem, inadequate hydrogen infrastructures, low energy efficiency mismatching the development progress of renewable energy, insufficient market demand, shortcomings in technology, and imperfect policy system. Finally, five policy suggestions for the future development of China's hydrogen energy industry are proposed as follows: (1) make an action plan as a response to the national hydrogen development plan; (2) build an international and domestic double-cycle hydrogen economic system; (3) incorporate hydrogen into the establishment of a clean, low-carbon, safe and efficient energy system; (4) accelerate the technological innovation to form advanced hydrogen technologies; and (5) construct hydrogen-oriented industrial clusters/parks to expand the hydrogen utilization market. It is concluded that for meeting the carbon peak and carbon neutrality goals, China should leverage the dual advantages of hydrogen as an energy carrier and an industrial raw material, allowing the hydrogen industry to play a synergistic role in ensuring the country's energy security, promoting the socio-economic transformation and upgrading, and protecting the ecological environment, thereby providing a technical option and support for China to achieve the ultimate goal of carbon neutrality.

Design Optimization and Carbon Footprint Analysis of an Electrodeionization System with Flexible Load Regulation

Thermal power plants will function as a flexible load regulation in a low-carbon grid, which requires operation adaption for the whole system. Energy transition in the electricity sector is the core to realizing carbon neutrality. The power grid will be gradually dominated by renewable energy, such as wind power and photovoltaic solar power. However, renewable energy has problems such as insufficient power supply and output fluctuation; thermal power will be required to regulate the peak load flexibly to meet demand. Therefore, the supply of boiler make-up water prepared by electrodeionization (EDI) in thermal power plants should also be flexibly changed. This study focused on the ultrapure water preparation system by EDI with variable flow rates. For an EDI system with a maximum ultrapure water capacity of 20 m3/h, the power consumption, annual cost, and carbon footprint of different designs are compared. The operation parameters were optimized based on the optimal cost design when the temporal demand of boiler make-up water is reduced to 75%, 50%, and 25%, respectively, considering thermal power as peak load regulation technology. The results showed that the optimized system could significantly reduce power consumption and carbon footprint by up to 30.21% and 30.30%, respectively. The proposed strategy is expected to be widely applied for design and operation optimization when considering the low-carbon but unstable energy system dominated by renewable energy. The carbon footprint could be a feasible optimization object to balance the greenhouse gas emissions from the module manufacturing and operation consumption.

Offshore wind power in China: A potential solution to electricity transformation and carbon neutrality

China is likely to lead global offshore wind power development, in the hope of transforming the coal-based electricity system and reducing greenhouse gas emissions. However, the potential of power generation and emissions mitigation is largely unknown, and the contribution of offshore wind utilization to regional carbon neutrality needs to be further clarified. Here, we reveal that offshore wind energy resources are abundant in China, with an estimated power generation potential of about 17.5 PWh, more than doubling the current power consumption nationwide. Although current utilization of offshore wind energy in China accounts for 21% of global overall capacity, the total share is still limited, supplying just 0.4% of national electricity needs (2019). With the increasing use of offshore wind, by 2050, the planned installation along China coast would be nearly five times as much as current (2019) global capacity, or 25 times of current national offshore wind power generation. The total CO2 emissions reduction in 2050 due to the decrease in coal use is projected to be 294.3 Tg CO2-eq yr–1, equivalent to 20% of current emissions from coal-fired power in the coastal region. The size of reduced emissions is higher than current CO2 emissions in about 90% of countries. Our results highlight the important role of offshore wind power in upgrading the energy system and achieving carbon neutrality. Future studies are encouraged to further explore technological, economic and institutional challenges facing offshore wind energy deployment and low-carbon energy system development.

Drivers of electricity GHG emissions and the role of natural gas in mexican energy transition

In the last three decades, the high growth of natural gas as an energy source for Mexican electricity production was the most significant change in the sector. Natural gas went from being the source of 7% of electricity in 1990 to 62.3% in 2020. A co-dependence of electricity and natural gas systems has been established and is increasing. Is this fact consistent with the objective of decarbonizing the electricity sector? We study this question through a decomposition analysis of electricity Greenhouse Gas (GHG) emissions in Mexico between 1990 and 2015. We use a Logarithmic Mean Divisia Index (LMDI) to quantify the changes of electricity GHG emissions related to activity, carbon coefficient, structure, and energy intensity effects. Activity effect was the most significant driver of GHG emissions growth, structure and energy intensity effects contributed to limiting that growth, while the carbon coefficient effect had a small contribution to mitigating GHG emissions. From these results, we raise concerns about the role of natural gas, which crowd-out renewable energy and could lead to carbon lock-in and stranded assets in the long term. In addition, Mexico's energy system relies heavily on U.S. natural gas. In light of these concerns, we concluded that an energy policy aiming towards a low-carbon energy system should consider the composition “natural gas + renewable energies + energy efficiency”.

Capacity planning of carbon-free microgrid with hydrogen storage considering robust short-term off-grid operation

Carbon-free microgrids (CFMs) composed of renewable energy and hydrogen energy storage systems (HESS) are a promising solution for low-carbon energy systems. However, when CFMs are off-grid, their reliability is frequently questioned, especially when renewable energy (RE) outputs are extremely low. To reduce the total cost and improve the off-grid reliability, this paper proposes a two-stage robust planning model for CFM with renewable energy and HESS that considers both grid-connected (GC) and short-term (several days) off-grid (OG) statuses. In the GC status, the target is to minimize the system expenses; while in the OG status, the optimization goal is not to lose the important loads in a short period of time considering the worst realization of days. The Nested-C&CG algorithm is employed to solve the robust planning model of CFM. Additionally, a new uncertainty set that takes terrible days into account for RE and loads is presented to make the decision robust. Finally, the numerical analysis based on the case studies shows that the HESS in CFM has the ability to support loads in OG status for a week. And the total cost of the CFM using HESS and batteries can be reduced by 11.83% compared with that using only batteries. In addition, the planning results with robust optimization can guarantee that all the important loads are satisfied.

Power Generation Scheduling for a Hydro-Wind-Solar Hybrid System: A Systematic Survey and Prospect

In the past two decades, clean energy such as hydro, wind, and solar power has achieved significant development under the “green recovery” global goal, and it may become the key method for countries to realize a low-carbon energy system. Here, the development of renewable energy power generation, the typical hydro-wind-photovoltaic complementary practical project, is summarized, and some key problems in complementary systems such as the description and prediction of the power generation law in large-scale stations, risk management, and coordinated operation are analyzed. In terms of these problems, this paper systematically summarizes the research methods and characteristics of a hydro-wind-solar hybrid system and expounds upon the technical realization process from the prediction and description of wind and solar power station cluster output, the risks brought about by large-scale renewable energy grid-connected operation, and the long-term and short-term coordination modeling and resolution thoughts on the hydro-wind-solar hybrid system in cluster mode. Finally, based on the aforementioned analysis, the existing research gaps are discussed from the standpoints of generation forecast, risk management, and cluster scheduling, and the future work outlook is presented accordingly. A hybrid system that combines hydro, wind, and solar energy is emerging as a way to make up for each other’s shortcomings and will be a fruitful area of study in the future.

The PRISMI Plus Toolkit Application to a Grid-Connected Mediterranean Island

Islands are a constrained environment due to their geographical peculiarities and their land use accounting for, especially in the touristic locations, strong variability during the year. Consequently, the variation of energy demand to be met by variable renewable energy leads to a complex issue. This study aims at investigating the PRISMI Plus approach applied to the Island of Procida to drive the transition towards low-carbon and high-renewable energy system. The toolkit involves the analysis of local renewable energy potential, their potential matching of the energy demand, and the prioritization of the technological solutions to achieve the decarbonization targets set by the energy planning strategies. Three scenarios are designed for 2030 considering low, middle, and high penetration of renewable energy in the systems, results indicate that the amount of power production in low, middle, and high penetration of renewable energy scenarios are 0.18, 14.5, 34.57 GWh/year, respectively. The environmental and landscape constraints lead to a restricted set of available solutions. The decarbonization of the electricity supply is foreseen thanks to the available local solar resources plus the electrification of other sectors, i.e. heating by using Heat Pumps and transport by using Electric Vehicles.

Reducing energy and environmental challenges by modeling clean electricity generation in oil-rich regions

Reducing greenhouse gas (GHG) emissions induced environmental hazards is one of the most important goals of future research the energy economy and the environment. This challenge is becoming more important in developing countries, including Iran, with high energy intensity and is one of the leading countries in GHG emissions. This study aims to visualize emissions from electricity generation in Khuzestan province, southern Iran. Khuzestan is the largest producer of electricity and the country's energy capital. Khuzestan's electricity supply and demand system was simulated and examined under green scenarios till 2050 by assessing the existing situation and choosing a suitable low-carbon energy system for the future. One of the results of this research is to reduce emissions in terms of energy management strategies in the short term and the ineffectiveness of development strategies regardless of consumption management strategies. Electricity supply optimization scenarios are attractive in the long term, which indicates the costly implementation of development strategies. Combining solutions to balance the energy economy and environment is more effective. The OKEP scenario as a combination of consumption management and development strategies showed that it would maintain its positive impact in the short and long term and successfully reduce emissions. In this scenario, the net present value (NPV) attractiveness is over $ 6706 million and saves the emission of 179 MtCO2e. Compared to the business as usual (BAU) scenario, more than 90 Bm3NGe savings and a 3.62% increase in renewables share are other benefits of this scenario.

Energy requirements and carbon emissions for a low-carbon energy transition

Achieving the Paris Agreement will require massive deployment of low-carbon energy. However, constructing, operating, and maintaining a low-carbon energy system will itself require energy, with much of it derived from fossil fuels. This raises the concern that the transition may consume much of the energy available to society, and be a source of considerable emissions. Here we calculate the energy requirements and emissions associated with the global energy system in fourteen mitigation pathways compatible with 1.5 °C of warming. We find that the initial push for a transition is likely to cause a 10–34% decline in net energy available to society. Moreover, we find that the carbon emissions associated with the transition to a low-carbon energy system are substantial, ranging from 70 to 395 GtCO2 (with a cross-scenario average of 195 GtCO2). The share of carbon emissions for the energy system will increase from 10% today to 27% in 2050, and in some cases may take up all remaining emissions available to society under 1.5 °C pathways.

Wind-photovoltaic co-generation prediction and energy scheduling of low-carbon complex regional integrated energy system with hydrogen industry chain based on copula-MILP

The application of hydrogen is promising for achieving carbon neutrality. To promote hydrogen utilization and carbon emission reduction, this paper attempts to integrate the hydrogen industry chain, carbon capture and storage (CCS) into a regional integrated energy system (forming a complex regional integrated energy system (CRIES)) and proposes an energy scheduling model for optimizing CRIES operation considering wind and photovoltaic co-generation (WT-PV) uncertainties. Firstly, to measure the uncertainties of WT-PV, the Wasserstein distance with better geometric properties is introduced to select the best Copula to model the correlation between wind and photovoltaic generation and to generate a typical scenario of WT-PV for each season. Secondly, based on MILP, the system is modularly modeled considering the pressure difference of various gases, the time interval of carbon capture and natural gas synthesis, and the energy coupling relationship. Finally, based on the above WT-PV prediction and modeling, the energy dispatch status in each season is investigated, and the economics of the proposed system is verified in the minimum hydrogen demand variation of hydrogen metallurgy plant, hydrogen blending ratio, and uncertainties of electric vehicles and hydrogen vehicles loads. Results show that 1) hydrogen-rich natural gas improves system’s energy use efficiency, CCS weakens system’s dependence on the upstream natural gas network, and the multi-energy coupling improves system’s arbitrage ability under different prices; 2) hydrogen is richest in the summer, causing system’s revenue to be 8.54%–32.17% and 29.29%–244.21% higher than in the transition season and winter. 3) zero-carbon energy interaction with the outside world and fully accommodating WT-PV are achieved by integrating the hydrogen industry chain; 4) the proposed CRIES operates reliably and economically under multiple uncertainties.

Optimal home energy management strategy: A reinforcement learning method with actor-critic using Kronecker-factored trust region

The global development trend of building decentralized and low-carbon energy systems has given rise to challenges in the demand side energy management. With the overwhelming increase in the domestic electricity demand and distributed energy penetration, scheduling residential energy consumption has become essential for decreasing environmental impact. To this end, the paper proposes an energy scheduling strategy optimization framework for a home energy management system devised with photovoltaic and storage to realize the optimal scheduling of household appliances. Uncertainties in energy usage behaviour and real-time electricity prices were considered and described using a Markov decision process model. Subsequently, to search for the optimal appliance scheduling policy in a complex and changing environment, a model-free energy scheduling approach was proposed based on actor-critic using the Kronecker-Factored Trust Region (ACKTR). Unlike conventional deep reinforcement learning methods, the proposed ACKTR-based approach has high sampling efficiency and can deal with both discrete and continuous control actions to jointly optimize the scheduling strategies of various types of appliances. Finally, the numerical results of case studies validate the effectiveness and demonstrate that the proposed approach can significantly reduce costs while maintaining satisfaction, with a remarkable 25.37% cost saving on a typical test day.

Barriers identification, analysis and solutions to rural clean energy infrastructures development in China: Government perspective

Under the carbon neutrality target, it is significant to build a clean, low-carbon, efficient and safe energy system in the whole society. As farmers and agriculture remain an important social and industrial component of China, good development of rural clean energy infrastructures (RCEIs) has great meaning for reducing carbon emissions. However, limited by various objective conditions, the current status of RCEIs is lagging behind, and existing studies do not change this situation very well. This research establishes a comprehensive barrier analysis system and gives specific recommendations for the government's reference. Firstly, a complete barrier list is identified according to the literature surveys, industry reports and expert consultations, which consists of 15 barriers. Then, the decision-making trial and evaluation laboratory (DEMATEL) is extended to the interval trapezoidal type-II fuzzy number (IT2TrFN) to convey more decision-making information, and the K-means clustering algorithm is utilized to optimize the objectivity of the threshold value. The results show that Insufficient government funding is the most important barrier, Energy consumption patterns, Lack of other infrastructure and Inadequate administration are all critical barriers for RCEIs project. At last, corresponding strategies are formulated from three aspects including Subsidy policy, Technology and talents, Administration system for the government's theoretical support and reference.

Research on new energy Marketing innovation

On September 22, 2021, the Party Central Committee, with General Secretary Xi as the core, made a major decision to achieve carbon peaking and carbon neutrality, with the following main objectives. By 2025, an economic system of green, low-carbon and cyclic development will take initial shape, laying a solid foundation for achieving carbon peaking and carbon neutrality. By 2030, the comprehensive green transformation of economic and social development has achieved significant results, and the energy utilization efficiency of key energy-consuming industries has reached the international advanced level. By 2060, a green low-carbon cycle development of the economic system and a clean, low-carbon, safe and efficient energy system will be fully established, carbon neutral goals will be successfully achieved, fruitful results will be achieved in the construction of ecological civilization, and a new realm of harmonious coexistence between man and nature will be created. In order to achieve the goal, "on the complete and accurate implementation of the new development concept to do a good job of carbon peak carbon neutral views" clearly mentioned, accelerate the construction of low-carbon transportation system, the promotion of energy-saving low-carbon transport, this advocacy brings opportunities for the development of new energy vehicles, new energy vehicles refers to is the use of non-conventional automotive fuel as a power source, integrated vehicle power control and drive aspects of the Advanced technology, formed with new technology, new structure, advanced technical principles of the vehicle. However, under the role of the market and external environment, although the sales of new energy vehicles are developing in an upward trend, a series of problems exist in them leading to a bottleneck to be broken through. This paper provides an in-depth analysis of this phenomenon and provides innovative points for the development of the new energy vehicle industry from the marketing perspective to promote the development of the new energy vehicle industry.