Low-carbon Power System Research Articles

Balancing the Water-Carbon Trade-Off: Development of a Bi-Level Source-Grid-Load Synergistic Optimization Model for Multi-Regional Electric Power System

This study introduces the Bi-Level Source-Grid-Load Synergistic Optimization (BL_SGLSO) model, which effectively balances the competing objectives of water conservation and carbon emission reduction in the power industry. The model aims to establish a clean and low-carbon electric power system by harmoniously reconciling these two critical goals. Through the application of bi-level programming, the BL_SGLSO model adeptly manages the preferences and conflicts of decision makers at various levels while capturing regional interactions and the intricacies of electricity transmission. Key findings reveal that non-fossil energy conversion technologies are poised to become the dominant force in electricity generation, accounting for an impressive 89.34% share by 2050. To mitigate the spatial mismatch between power load and resource allocation, the development of new transmission pathways and the expansion of the “power transmission from west to east” initiative are paramount. Furthermore, the implementation of a carbon-reducing power system offers significant potential for conserving water resources and alleviating water stress. These insights provide invaluable guidance for decision makers seeking to optimize multi-regional electric power systems for both water efficiency and low-carbon outcomes while simultaneously promoting the adoption of renewable energy sources and fostering synergistic development across regions.

Deep learning power grid project cost prediction under low-carbon background

Abstract Under the background of low-carbon power system developing towards cleaner, more efficient and more economical direction, accurate prediction of power grid project cost is very important for the construction of power grid project. In order to improve the accuracy of power grid project cost prediction, a power grid project cost prediction method based on deep learning is proposed. First, for the complex and nonlinear features of the line engineering cost data, the XGBoost model is used to analyze the line engineering cost data. Feature selection and data dimension reduction are carried out through the importance ordering of the features analyzed. Then, the engineering cost integration model is established based on the XGBoost model and Stacking. The cost analysis of power grid transmission project shows that the integrated model has better generalization performance and higher prediction accuracy, and can accurately predict the line cost level.

Blockchain-Based Renewable Energy Trading Using Information Entropy Theory

Renewable energy sources (RES) and electric vehicles (EVs) are widely recognized as primary ways to reduce carbon emissions and essential components of low-carbon power systems. However, both of them have strong uncertainties which bring great challenges to power transactions and the operation of power grids. This paper defines the uncertainty cost of wind power producer(WPP) in day-ahead(DA) market pricing based on information entropy theory for the first time and proposes a EV charging management strategy with DA contract. The constructed low-carbon emission electricity market(LCEM) quantifies the uncertainty cost and contracts the disordered charging of EVs. It reduces the uncertainty and ensures the balance of power supply and demand. In addition, the transaction between WPP and EVs is described as the Stackelberg game, and its communication network is constructed through a blockchain network to ensure transaction efficiency and privacy security. Experiments show that LCEM can accurately measure the uncertainty of wind power generation, increase the net profit for WPP by more than 2% when the prediction error is greater than 10%, and adopt EV contract charging management in the DA market to minimize charging costs.

Effect of investment cost on technology preference in a flexible, low-carbon Finnish power system

This paper investigates the effects of varying investment costs in a cost-optimal portfolio of electricity-generating technologies to achieve a low-carbon power system to help mitigate climate emissions in Finland. Several different cost scenarios for nuclear, solar, wind, and battery technologies are constructed, considering both single- and multi-stage investment-strategy pathways, with sector coupling of the power system to the heating sector and hydrogen production. Potential new nuclear investments are assumed small modular reactors capable of flexible operation, and optional additional flexibility measures from heating and hydrogen sectors are considered. The scenarios are simulated with hourly resolution using GenX, an openly available capacity expansion optimization tool. Across a wide range of assumed investment costs, the results demonstrate a clear role for flexible nuclear power as a provider of both a solid base generation and flexibility to enhance integration of intermittent wind to the system. Despite optimistic cost assumptions for solar and batteries, their role is observed to remain marginal in the Finnish setting, likely due to large seasonal variation in the local solar availability.

The Market Mechanism and Issues of China's Clean Energy Consumption Policies

Under the dual-carbon goals, since the 18th National Congress of the Communist Party of China, various regions and relevant departments have, based on the new development stage and the implementation of the new development concept, formulated a series of policies and measures related to energy, green, and low-carbon development. These policies include carbon trading, mechanisms to ensure the absorption of renewable energy, and mechanisms for trading green electricity. The focus has been on establishing a clean and low-carbon new power system. Against this backdrop, this article, starting from the national context, meticulously reviews the policy development process and current status of carbon trading, the absorption of renewable energy (green certificates), and green power trading. It also analyzes and introduces the operational mechanisms of clean energy absorption policies from the perspectives of market entities, transaction methods, and supporting measures. The study identifies issues in the development of carbon trading, green certificate trading, and green power trading, as well as the challenges arising from the integration of different clean energy policies. Based on these findings, specific development recommendations are proposed to clarify the operational mechanisms of typical clean energy absorption policies. This is aimed at assisting various entities involved in energy consumption to better fulfill their carbon reduction tasks.

Multi-Objective Optimal Power Flow Calculation Considering Carbon Emission Intensity

In keeping with China’s dual carbon goals, optimal low-carbon power system dispatch has become a necessary component of the greening of the power system. However, typically, research considers only the economics of such efforts. Based on our power flow analysis of the power grid and the correlation properties of carbon emission flow, an optimal power flow calculation model targeting the total carbon emission rate of the power system’s power generation cost, active network loss, and load and network loss was constructed. Next, the NSGA-III algorithm was used to solve the model, and the decision was to coordinate and optimize the output schemes of various types of power plants, such as wind, water, and thermal. The modified IEEE39 node simulation system was built with Matlab software (MATLAB R2020b). The results of the calculation showed that, compared to the traditional method of determining the optimal power flow, the proposed method reduced the system carbon emissions by 20% while the power generation cost increased by less than 2%, which proves the effectiveness and practicability of the proposed method.

Editorial: Advances in flexibility exploration and utilization for low carbon power systems

Editorial: Advances in flexibility exploration and utilization for low carbon power systems

Distributional labour challenges and opportunities for decarbonizing the US power system

The transition towards a low-carbon power system presents challenges and opportunities for the workforce with important implications for just transitions. Studies of these distributional labour impacts could benefit from tighter linkages between energy and employment modelling. Here, we couple a power-sector optimization model, an employment impact model and demographic databases to understand state-level job characteristics and the societal implications of low-carbon transitions in the US. Although decarbonization brings consistent job growth, it heightens the need for investment in human capital and supply chain restructuring. Major fossil fuel-producing states need to prepare for fewer mining jobs under the US Long-Term Strategy, so other opportunities should be created or seized. The lowest-skilled workers will experience more uncertain employment outcomes. Expanding renewable energy could improve opportunities for women in fossil fuel-dependent states, but not enough to disrupt the national gender status quo. This work provides a new quantitative perspective to inform proactive just transition policies.

Research of the system-on-chip-based relay protection technology

The relay protection device is the core equipment that ensures the safe and stable operation of a power grid. With the open access of a large number of distributed generation, DC transmission and electric vehicles, a new deep low-carbon power system dominated by power electronic devices has gradually been formed. It is difficult for the traditional control and protection architecture, methods, and technology to meet the business characteristics and functional requirements of a diversified interaction, agile response, safety, and credibility of the power grid in the future. This paper presents a chip-based relay protection technology based on system-on-chip (SoC), which is described from four aspects, namely, the architectural design of the relay protection SoC, software and hardware cooperative relay protection based on the SoC IP core, experimental verification, and engineering application. The results show that the relay protection SoC proposed in this paper has significantly improved the performance of high-speed data acquisition and interaction through hardware algorithm engine acceleration and software and hardware collaborative computing, which is helpful to realize the local equipment operation and the integration of primary and secondary equipment, shorten the protection action time, and improve the speed, reliability, and stability of relay protection devices.

Economic modelling of flexible carbon capture and storage in a decarbonised electricity system

This research provides new techno-economic insights into integrating flexible combined-cycle gas turbines with post-combustion carbon capture and storage (CCGT-CCS) for low-carbon power systems. This study developed a versatile unit-commitment optimisation model of CCGT-CCS. This research highlights the model’s adaptability, accommodating diverse techno-economic configurations, feed gases (e.g., biomethane or fossil natural gas), carbon capture rates, and policy instruments. This generalisation empowers seamless application in various policy and market contexts, making the model a potent tool for researchers and policymakers. While the case study focuses on the UK, the findings are relevant for most low-carbon power systems with variable renewable supplies. Analysing the UK’s net-zero scenarios from 2030 to 2050, the economic viability of flexible CCGT-CCS was highlighted. Intertemporal flexibility proves highly valuable with greater electricity price volatility, with a total ROI range of 81–246 %, surpassing the CCGT-CCS plant’s ROI (7–64 %). A flexible solvent storage solution should be seen in the context of the overall system ‘flexibility’ requirements of a low-carbon power system. On a cost basis, solvent storage represents just a fraction of the capital costs of more “mainstream” energy storage technologies, such as lithium-ion batteries or hydro-pumped storage, while CCGT-CCS offers firm power. Overall, while seen as a rather technical solution, if abated fossil fuel generation is to be part of a future low-carbon power system, having this flexibility adds economic benefits not just to operators but also improves overall system security and complements high shares of variable renewables on the grid.

Scheduling optimization of wind-thermal interconnected low-carbon power system integrated with hydrogen storage.

To improve the consumption of wind energy and reduce carbon emission, this paper proposes a wind-thermal interconnected low-carbon power system integrated with hydrogen storage. An energy scheduling optimization model aiming at minimizing the daily operation cost of the system is constructed considering environmental operation cost quantification, and whale optimization algorithm is used to optimize multiple variables. Finally, in simulation example, various scenarios are set considering the application way of hydrogen and the scenarios with and without the carbon capture and storage (CCS) are optimized, respectively. The horizontal comparison results show that the system with hydrogen production (S2) and the system with hydrogen fuel cell (S3) have higher economic operation cost than that of wind-thermal interconnected power system only (S1), but the environmental cost is reduced; the system's daily operating costs are reduced. The wind curtailment rate decreases from 11.0% (S1) to 3.8% (S2 and S3) without CCS, and from 9.0% (S1) to 2.1% (S2 and S3) with CCS. The longitudinal comparison shows that the thermal power output is reduced and the wind power consumption is improved with CCS. The addition of CCS increases total operating costs but significantly reduces environmental costs. Configuring hydrogen storage system in the wind-thermal interconnected power system can effectively promote the consumption of wind energy and reduce the system operation cost; however, the utilization of CCS is economic unfriendly at present.

Continental-scale assessment of micro-pumped hydro energy storage using agricultural reservoirs

The transition to low-carbon power systems necessitates cost-effective energy storage solutions. This study provides the first continental-scale assessment of micro-pumped hydro energy storage and proposes using agricultural reservoirs (farm dams) to significantly reduce construction costs. The continent of Australia is used as a representative case study for other arid and temperate regions internationally. From a new survey of its 1.7 million farm dams, we identified 30,295 promising pumped hydro sites in dam-to-dam and dam-to-river reservoir configurations. The average site had nearby reservoirs (132 m) with a high head height (32 m) and substantial discharge capacity (52 kWh). We then benchmarked a representative micro-pumped hydro site to a commercially available lithium-ion battery for a solar-powered irrigation system. Despite a low discharge efficiency (68%), pumped hydro storage was 30% less expensive (0.215 USD/kWh) for larger single-cycle loads (∼41 kWh/day) due to its high storage capacity. By capitalising on existing farm dams, micro-pumped hydro energy storage may support the uptake of reliable, low-carbon power systems in agricultural communities.

Enhancing the resilience of the power system to accommodate the construction of the new power system: key technologies and challenges

The increasingly frequent extreme events pose a serious threat to the resilience of the power system. At the same time, the power grid is transforming into a new type of clean and low-carbon power system due to severe environmental issues. The system shows strong randomness with a high proportion of renewable energy, which has increased the difficulty of maintaining the safe and stable operation of the power system. Therefore, it is urgent to improve the resilience of the new power system. This paper first elaborates on the concept of power system resilience, listing the characteristics of new power systems and their impact on grid resilience. Secondly, the evaluation methods for resilient power grids are classified into two categories, and measures to improve the resilience of the new power system are reviewed from various stages of disasters. Then, the critical technologies for improving the resilience of the new power system are summarized. Finally, the prospective research directions for new power system resilience enhancement are expounded.

Editorial for the Special Issue on Emerging Technology and Advanced Application of Energy Storage in Low-Carbon Power Systems

Editorial for the Special Issue on Emerging Technology and Advanced Application of Energy Storage in Low-Carbon Power Systems

Multi-objective investment evaluation for low-carbon power system evolution based on system dynamics

The energy transition development path towards low carbon power systems requires considered investments for system design. A multi-objective investment evaluation method for power system evolution towards low-carbon is established based on multiple development goals including energy security, ecological protection, economic development and technology advancement. The four aspects are modeled based on system dynamics and provide collaborative quantitative evaluation for power system evaluation. Different evolution paths are simulated and analyzed with different policy scenarios, which verify the effectiveness of the proposed model. The results of several indices show that with strong enough policies, it is expected to achieve the CO2 peak around 2030. And accelerating the construction of electricity market reform can provide greater investment space. The ecological protection index has the largest weight in the multi-objective investment, requiring power system to deepen the low-carbon transition.

4E analysis of a novel proton exchange membrane fuel cell/engine based cogeneration system with methanol fuel for ship application

Cleaner fuels and more efficient systems are important for achieving green, low-carbon ships. In this paper, a novel proton exchange membrane fuel cell/engine based cogeneration system with methanol fuel (MPEC system) for ship application is proposed. By the online catalytic reforming process of methanol, the obtained hydrogen through reforming can provide sufficient high heating value fuel to the MPEC system. The energy efficiency, exergy efficiency, economy and environment (4 E) analysis method is adopted for the comprehensive performance analysis of the MPEC system. The results show that the proposed MPEC system can achieve cogeneration efficiency and power generation efficiency as high as 81.84% and 50.46%, respectively, which performs that the generation efficiency is improved by 19.55% compared to the single engine, and the biggest exergy loss process occurs at the engine. The total life cycle carbon emission and levelized cost of energy of the MPEC system are 344.938 g/kWh and 0.1411 $/kWh, separately. Moreover, the effects of various parameters on the MPEC system performance are analyzed, mainly including steam carbon ratio, current density, etc. Overall, a low-carbon power system with high efficiency and good load performance is achieved by combining high-efficiency fuel cell with a powerful engine.

Complementary potential of wind-solar-hydro power in Chinese provinces: Based on a high temporal resolution multi-objective optimization model

In the context of carbon neutrality, renewable energy, especially wind power, solar PV and hydropower, will become the most important power sources in the future low-carbon power system. Since wind power and solar PV are specifically intermittent and space-heterogeneity, an assessment of renewable energy potential considering the variability of wind power and solar PV with high temporal resolution in different regions will facilitate more accurate identification of the decarbonization pathway of power system. In this paper, the complementary output potential of wind-solar-hydro power every 15 min in 31 Chinese provinces is evaluated by developing a multi-objective optimization model based on Nondominated Sorting Genetic Algorithm II. The results show that the total annual complementary power generation potential in China is 17.57 PWh, of which the three components account for 47.8%, 25.3% and 26.9%, respectively. Inner Mongolia and Tibet are the major renewable energy source provinces with annual complementary power generation potential of 5330 TWh and 3907 TWh, accounting for 30.3% and 13.7% of the total power generation potential, respectively. The temporal potential of wind-solar-hydro power varies greatly, with daily potential is more volatile than monthly. Seasonal and spatial heterogeneity of the complemental renewable potential makes some provinces suffer power shortage during long-hours period especially in winter. Our findings will encourage a higher penetration of renewable energy, the promotion of multi-energy complementarity, and the development of inter-provincial power transmission and energy storage infrastructure in China's future power sector.

A renewable power system for an off-grid sustainable telescope fueled by solar power, batteries and green hydrogen

A large portion of astronomy’s carbon footprint stems from fossil fuels supplying the power demand of astronomical observatories. Here, we explore various isolated low-carbon power system setups for the newly planned Atacama Large Aperture Submillimeter Telescope, and compare them to a business-as-usual diesel power generated system. Technologies included in the designed systems are photovoltaics, concentrated solar power, diesel generators, batteries, and hydrogen storage. We adapt the electricity system optimization model highRES to this case study and feed it with the telescope’s projected energy demand, cost assumptions for the year 2030 and site-specific capacity factors. Our results show that the lowest-cost system with LCOEs of $116/MWh majorly uses photovoltaics paired with batteries and fuel cells running on imported and on-site produced green hydrogen. Some diesel generators run for backup. This solution would reduce the telescope’s power-side carbon footprint by 95% compared to the business-as-usual case.

Multipath retrofit planning approach for coal-fired power plants in low-carbon power system transitions: Shanxi Province case in China

Multipath retrofit planning approach for coal-fired power plants in low-carbon power system transitions: Shanxi Province case in China

Evaluating the cost impacts to meet China’s renewable electricity portfolio standard target in 2030

ABSTRACT The power sector plays a pivotal role in China’s carbon peak and carbon neutrality targets. To build a low-carbon power system, it is important to develop wind and solar. This study aims to evaluate the economic impacts of the newly launched renewable portfolio standard in 2030 in China using a cost minimization model and an input-output model. The results show that to accomplish the renewable electricity portfolio standard in 2030, the installed wind and solar capacity will have to reach 1451.9 gigawatts (GW) in 2030. The Northeast, Northwest, and North regions will deploy the most installed capacity, and Inner Mongolia will take on the most renewable energy generation tasks. The annual cost of wind and solar development is expected to be 506.6 billion CNY in 2030, 94.7% of which are new construction costs and storage costs. Renewable energy growth will result in a national average electricity price increase of 5.4 CNY¢/kWh compared to 2019, and Heilongjiang, Gansu, and Shanxi are the most affected. The rapid development of renewable electricity in the next decade will increase the Consumer Price Index (CPI) by 0.4%, Producer Price Index (PPI) by 0.9%, and Gross Domestic Product (GDP) deflator by 0.5% in 2030. Based on the results, we propose to improve the electricity market mechanisms, enhance the electricity transmission stability, and develop policies appropriate to local conditions.