Abstract

Ensuring access to affordable energy and water resources is essential for achieving the United Nations Sustainable Development Goals. Urban energy and water systems exhibit strong interconnectivity and interdependence. We adopt a bottom-up, two-tier, multi-stage multi-agent game combined with multi-objective optimization to quantify intra-city energy–water interaction dynamics and determine optimal resource-dominance allocations across the urban cluster. Our results show significant spatial disparities among cities such as Ordos and Yulin, which exhibit energy carbon footprints of approximately 2.46 t COâ‚‚ / tce and water footprints of about 1.52 billion m³ — exceeding the regional averages by 39.3% and 21.7%, respectively. Under a shifting resource dominance paradigm, as exemplified by Ordos, the energy-dominant Stackelberg scenario achieves economic benefits 28.5% and 19.7% higher than those of water-dominant and cooperative scenarios. The formation of a coal–coal power to coal-to-chemicals industrial chain that strategic resource coupling can enhance systemic resilience. We also provide recommendations for promoting sustainable urban transitions in resource-constrained regions by strengthening system-level coordination between energy and water subsystems.

Abstract

Integrated energy systems (IES) synergize electricity, gas, and heat networks to enhance renewable integration and utilization efficiency, where carbon emissions are intrinsically coupled with multi-energy flows. Precise carbon allocation mechanisms are critical for carbon-aware operations. This paper proposes a unified carbon emission flow (CEF) framework for IES, defining core physical quantities under conservation principles. Explicit CEF models are established for different energy networks. The energy hub formulation integrates these via coupling matrices to map carbon redistribution through converters. Based on the theoretical foundation, a CEF calculation procedure is demonstrated through an integrated electricity-gas-heat case study, to validate the effectiveness of the proposed method. This framework enables precise carbon accounting and decarbonization-oriented IES planning.

Abstract

Traditional gas-fired combined heat and power (CHP) plants are plagued by high transmission loss to off-site heat users and irreversible loss when driving absorption chillers (heat source ≤200℃). To alleviate these challenges, this study proposes a novel hydrogen-cooling-heating-power poly-generation energy system driven by industrial steam waste heat. This innovative system utilizes methanol as feedstock, whose reforming temperature (200-300°C) aligns closely with industrial steam temperatures. It is integrated with gas-steam combined cycle power generation and the thermochemical process of methanol reforming. The waste heat from 300°C industrial steam is utilized to drive hydrogen production through methanol reforming, achieving cascade energy utilization. The industrial steam is split for material and energy coupling with the methanol reforming unit. One stream is mixed with methanol as a reactant and enters the reformer, while the other provides the heat for the endothermic reforming reaction. The industrial steam waste heat is further recovered through absorption refrigeration for cascaded utilization. The overall utilization efficiency of industrial steam is enhanced. Under the designed operating conditions, the energy efficiency and exergy efficiency of the system reach 73.60% and 61.37%, respectively. Electricity, hydrogen, cooling, and heat are simultaneously generated by the integrated design, minimizing energy waste and alleviating thermal mismatch. This study provides an innovative solution for the efficient utilization of industrial steam in power plants.

Abstract

Local multi-energy systems can accommodate renewable energy while meeting the multi-energy demands of urban end-users. However, a seasonal imbalance exists between renewable energy supply and multi-energy demand. Seasonal thermal energy storage (STES) can efficiently address the seasonal imbalance, but whether or how much to install costly STES remains a question. To this end, this paper conducts a techno-economic analysis of STES. Three Chinese cities in different climate regions are selected for our analysis to find out in what situations STES is cost-effective and to understand why STES performs differently across cities. The result shows that STES is more economical in high-latitude cities with an intense seasonal heating difference. Exceedingly, alteration in STES capacity is attributed to the influence of the heat and cooling load ratio and carbon price.

Abstract

Moisture-conducting fibers have the potential to be used as an evaporative medium in evaporative cooling systems. The performance of indirect evaporative coolers depends on the evaporation of the water film in the wet channel, while traditional core materials face issues such as poor wetting (low wetting rate, uneven water film, etc.). This study experimentally investigated the evaporation performance of a novel wet surface material (moisture-conducting fibers) when applied to an indirect evaporative cooler, constructing a single-channel evaporative cooling test bench equipped with a micro-pressure water distribution system. Under different inlet air temperatures (25°C–35°C), relative humidity (40%–80%), and air velocity (2 m/s–4 m/s) conditions, the surface dynamic wetting characteristics, including changes in moisture content and evaporation rate, were investigated. A sensitivity analysis was conducted using Pearson correlation analysis to assess the importance of the three influencing factors. The effects of various factors on the performance of the evaporative cooler were analyzed, providing guidance for the development, design, and efficient operation of moisture-conducting fiber-type evaporative coolers.

Abstract

Experiments on CO2 displacement were conducted using cylindrical rock cores under various voltages, electric field modification times, and different injection-production parameters. The dynamic characteristics and contributing factors of direct current (DC) electric field-assisted CO2 displacement on enhanced oil recovery were analyzed. The study shows that DC electric field-assisted CO2 displacement development can be divided into four phases: high-speed oil and gas production induced by DC electric fields, oil-carrying gas production, DC electric-assisted dissolved gas drive, and low-speed oil production. Voltage and electric field modification time are the primary factors affecting the effectiveness of DC electric field-assisted CO2 displacement development, followed by the CO2 injection volume and extraction speed, with the CO2 injection rate having the least impact. An optimal voltage exists that maximizes recovery efficiency; the longer the electric field modification time, the higher the recovery rate, although the rate of increase gradually slows. High volumes of CO2 injection and slow extraction can enhance recovery rates. The stability of bottom-hole pressure in injection-production wells can serve as an indicator of the completion of electric field modification. The main contributors to the recovery rate in DC electric field-assisted CO2 displacement development are the effects of the DC electric field on CO2 dissolution and electroosmosis, followed by diffusion and CO2 flow propagation.

Abstract

The rapid growth of electric vehicles (EVs) presents challenges to power system stability. This study investigates six core business districts in Shenzhen, using a 500-meter spatial grid and proposing a fine-grained “vehicle-building-grid” coordinated optimization framework to enhance urban energy resilience. Commercial building energy profiles are modeled using prototype buildings, while EV load data are generated via Monte Carlo simulations. Incorporating time-of-use electricity pricing and regional energy patterns, the study regulates unordered EV charging behavior to quantify EV flexibility and emergency power potential. Results show that optimized charging reduces energy costs by an average of 2.68% at the district level and by 0.81%–3.59% at the spatial grid level. When minimizing the peak-valley load gap, average reductions reach 37.7%, with spatial grid-level reductions ranging from 17.18% to 42.63%. The study provides both theoretical and empirical support for planning distributed urban energy storage systems.

Abstract

With the transformation of the energy structure and the rising penetration of electric vehicles (EVs), the planning and optimization of regional integrated energy systems (RIES) face new challenges. Using an industrial park in Hangzhou as a case study, this paper first optimizes the traditional high-carbon energy system by introducing electric chillers, ice storage, air source heat pumps, and battery storage, achieving significant reductions of approximately 48% in annual operating costs and 66% in carbon emissions. When EV charging loads are further incorporated into system planning, it is found that the demands for electricity, energy storage, and charging infrastructure increase significantly, resulting in higher total system costs and carbon emissions. To mitigate peak load pressures caused by EV charging, this study compares uncoordinated and coordinated charging strategies. The results show that coordinated charging not only reduces peak load by about 30%, but also decreases the required numbers of charging piles and energy storage capacity by 31% and 18%, respectively, while further lowering steam consumption, system costs, and carbon emissions, thus significantly improving system economy and flexibility. The findings suggest that fully tapping into the flexibility of EV loads and implementing smart coordinated charging are key to achieving low-carbon and efficient operation of RIES in future industrial parks.

Abstract

This study proposes a seasonal multi-objective optimization framework for building performance, addressing the balance between carbon emissions and indoor discomfort in traditional dwellings. Using a typical residential building in Huzhou, China, simulations were conducted for spring, summer, autumn, and winter using DesignBuilder and MATLAB. The results reveal significant seasonal differences: winter and summer exhibit the highest emissions and discomfort, while spring and autumn offer better energy-comfort balance. A genetic algorithm was employed to generate Pareto-optimal solutions, and sensitivity analysis identified key design parameters—such as heating/cooling setpoints and window-to-wall ratio—as dominant factors. The findings provide practical guidance for adaptive, season-specific building energy strategies.

Abstract

Aiming at the low operational efficiency and equipment redundancy of the energy system in an industrial park in a hot summer and warm winter zone of China, this paper firstly assesses the current state of the energy system, then based on the assessment results and the actual situation of the park, the energy system is optimized by using the typical day optimization, and finally, the operating benefits under the year-round scenario are verified. The results show that the optimized photovoltaic capacity is increased to the upper limit, the capacity of the energy storage equipment is increased accordingly, the capacity of the cooling equipment is reduced by 22.8%, and the dynamic payback period is 3.6 years, which can effectively reduce the redundancy of the equipment, improve the operational efficiency, and enhance the economy. However, under the year-round scenario validation, the typical day optimization does not consider enough the extreme cold load and PV output fluctuation, resulting in 2.9% of the cold load not being satisfied in the whole year. The dynamic payback period is extended to 7.1 years, with a significant decrease in the stability and economy of the system. This study provides a theoretical basis for the comprehensive energy system planning of industrial parks in hot summer and warm winter areas.