Search Results (625)

The photovoltaic–energy storage–direct current–flexibility (PEDF) system provides an integrated pathway for low-carbon and intelligent building energy management by combining on-site PV generation, electrical storage, DC distribution, and flexible load control. This paper reviews recent advances in these four modules and synthesizes quantified benefits reported in real-world deployments. Building-scale systems typically integrate 20–150 kW PV and achieve ~10–18% energy-efficiency gains enabled by DC distribution. Industrial-park deployments scale to 500 kW–5 MW, with renewable self-consumption often exceeding 50% and CO₂ emissions reductions of ~40–50%. Community-level setups commonly report 10–15% efficiency gains and annual CO₂ reductions on the order of tens to hundreds of tons. Key barriers to large-scale adoption are also discussed, including multi-energy coordination complexity, high upfront costs and uncertain business models, limited user engagement, and gaps in interoperability standards and supportive policies. Finally, we outline research and deployment priorities toward open and interoperable PEDF architectures that support cross-sector integration and accelerate the transition toward carbon-neutral (and potentially carbon-negative) built environments. Full article

Frequent extreme-weather events pose severe challenges to the secure and economical operation of power systems with high renewable energy penetration. To strengthen grid resilience against such low-probability, high-impact events while maintaining good performance under normal conditions, this paper proposes an optimal energy storage allocation method for power systems with high-wind-power penetration. We first identify two representative extreme wind power events and develop a risk assessment model that jointly quantifies load-shedding volume and transmission-line security margins. On this basis, a multi-scenario joint siting-and-sizing optimization model is formulated over typical-day and extreme-day scenarios to minimize total system cost, including annualized investment cost, operating cost, and risk cost. To solve the model efficiently, a two-stage hierarchical solution strategy is designed: the first stage determines an investment upper bound from typical-day scenarios, and the second stage optimizes storage allocation under superimposed extreme-day scenarios within this bound, thereby balancing operating economy and extreme-weather resilience. Simulation results show that the proposed method reduces loss-of-load under extreme-weather scenarios by 32.46% while increasing storage investment cost by only 0.18%, significantly enhancing system resilience and transmission-line security margins at a moderate additional cost. Full article

Façade systems in hot, high-insolation climates are required to simultaneously mitigate cooling loads, ensure high-quality daylight, and, where feasible, harvest on-site electricity demands that are often in tension. This study assesses and compares two efficient façade strategies for a fully glazed office prototype in Hail, Saudi Arabia: semi-transparent photovoltaic glazing (STPV10–30%VLT) and parametrically tuned split louvers (18 depth–spacing–tilt configurations). Using a unified parametric workflow (Rhino/Grasshopper), Radiance/honeybee for daylight metrics, ASHRAE-55 heat-balance metrics for thermal comfort, and EnergyPlus for end-use and PV yield, to evaluate annual and solstice performance across cardinal orientations. Optimized split louvers maintained UDI_300–1000lx and effectively suppress glare, but incur substantial lighting-energy penalties. In contrast, STPV with 10–20% VLT broadly meets daylight targets while strongly reducing cooling and lighting demand, delivering whole-façade energy savings of up to 50–94% depending on orientation, but could be net-neutral to slightly adverse north 3% when daylight penalties dominate. Thermal comfort responses mirrored these trends: summer PMV was near 0 to +0.5 for both systems, with winter under-heating evident when solar gains are strongly suppressed. Overall, in hot-arid, highly glazed offices, STPV of 10–20%VLT provides the most balanced triad of daylight quality, cooling reduction, and net energy benefit, while optimized louvers excel where glare control is paramount but require careful daylight-control integration. Full article

To address the challenge of the synergistic optimization of carbon reduction and economic operation in the integrated energy systems (IES) of industrial parks, this paper proposes an optimization scheduling model that incorporates carbon trading and supply–demand response (SDR) coordination mechanisms. This model is based on an IES coupling power-to-gas (P2G) and carbon capture and storage (CCS) technologies. First, the K-means clustering algorithm identifies three typical daily scenarios—transitional season, summer, and winter—from annual operation data. Then, we construct a synergistic optimization model that integrates a carbon trading mechanism, tiered carbon quota allocation, and SDR coordination. The model is solved via mixed-integer linear programming (MILP) to minimize total system operating costs. Systematic comparative analysis across six scenarios quantifies the incremental benefits: P2G–CCS coupling achieves a 15.2% cost reduction and 49.3% emission reduction during transitional seasons; supply–demand response contributes 3.5% cost and 5.6% emission reductions; technology synergies yield an additional 21.6 percentage points of emission reduction beyond individual contributions. The integrated system achieves 100% renewable energy utilization and optimizes peak-to-valley differences across electricity, heating, and cooling loads. Carbon price sensitivity analysis reveals three response stages—low sensitivity, rapid reduction, and saturation—with the saturation point at 200 CNY/t (28.6 USD/t), providing quantitative guidance for tiered carbon pricing design. This research provides theoretical support and practical guidance for achieving low-carbon economic operations in industrial parks. Full article

The rapid growth of electric vehicles (EVs) is expected to create a substantial stream of retired automotive batteries over the coming decades, offering an opportunity for low-cost stationary storage deployment. This paper quantifies how much additional photovoltaic (PV) capacity can be unlocked in Greece through the systematic use of second-life EV batteries under the new self-consumption and zero feed-in regulatory framework. First, a deterministic cohort model is developed to estimate the annual potential of second-life batteries, considering parameters like EV sales, first-life duration, repurposing eligibility, and second-life operational lifetime. The results indicate that Greece could accumulate from 3.5 GWh to 12.1 GWh of second-life batteries until 2050, depending on future EV growth rates. Next, to link battery capacity with PV unlocked potential, an hourly time-series simulation is implemented under a zero feed-in scheme, i.e., without exporting energy to the grid, indicating that each kilowatt-hour of second-life battery can unlock 0.33 kW of PVs in residential zero feed-in systems. On this basis, second-life batteries could unlock from 1.1 GW to 3.9 GW of additional PV capacity that would otherwise be infeasible. For comparison, the peak load of Greece is about 10 GW. Importantly, unlike large-scale grid-connected PV plants—where transmission system operators increasingly impose curtailments—zero feed-in installations can operate seamlessly without creating additional operational stress for the grid. Full article

With the energy consumption of data centers continuously increasing in recent years, green data centers as a transformative solution have grown increasingly significant. In this paper, a proton exchange membrane fuel cell-based combined cooling, heating, and power (PEMFC-CCHP) system coupled with wind and solar energy is proposed to ensure an energy supply that matches the dynamic load requirements of data centers. Taking a data center located in Guiyang, China, as a case study, a TRNSYS 18 simulation model for the integrated energy system is developed, and the analysis on the energy, economic, and environmental performance of the system is performed. The results demonstrate that the integrated energy system can effectively accommodate the load fluctuations of data centers through multi-energy complementarity. The PEMFC-CCHP system achieves a high energy utilization efficiency of 0.85–0.90. Furthermore, the payback period of the integrated energy system is estimated to be between 8.2 and 13.1 years, yielding an annual reduction in CO₂ emissions of 1847 t. Full article

Molten salt thermal energy storage (TES) provides an efficient solution to improve the flexibility of combined heat and power (CHP) plants. This study investigated two operation modes of TES: the Power-Augmenting TES Mode (Mode 1), which enhances power generation flexibility, and the Heating-Augmenting TES Mode (Mode 2), which improves the flexibility of industrial steam supply. Based on a validated thermodynamic model, the flexibility, energy efficiency, exergy efficiency, and economic performance of the integrated system are evaluated. Results show that Mode 1 offers stronger peak-shaving capability, while Mode 2 achieves comparable peak-topping performance and is more suitable for high industrial heating load scenarios due to its inherent heat–power decoupling effect. Mode 2 exhibits more pronounced energy efficiency improvement, whereas both modes reach identical maximum exergy efficiency. Additionally, the integration of molten salt TES significantly enhances profitability, increasing annual profit to 97.3 million RMB under Mode 1 and 85.4 million RMB under Mode 2 from a baseline of 79.7 million RMB. While Mode 1 generates higher profit at lower heating loads, Mode 2 becomes progressively more advantageous as industrial heating load increases. Full article

This study explores the effect of Energy Inequality (EINQ) on environmental sustainability within the frameworks of the Environmental Kuznets Curve (EKC) and the Load Capacity Curve (LCC), while accounting for technological progress (TECH), financial development (FD), and foreign direct investment (FDI). Using annual data for six Gulf Cooperation Council (GCC) countries from 2005 to 2024, the analysis applies the Method of Moments Quantile Regression (MMQR) to capture heterogeneous effects across the distribution of the Load Capacity Factor (LCF). The results show that energy inequality consistently reduces environmental sustainability, indicating that unequal access to efficient and clean energy services heightens ecological pressure. In contrast, technological innovation and financial development enhance sustainability by improving energy efficiency and supporting green investments. Economic growth exhibits an inverted U-shape, validating the EKC and LCC hypotheses. These findings are especially important for the GCC, where hydrocarbon dependence, uneven access to clean energy, and rapid structural change intensify the environmental consequences of inequality. The study underscores the need for policies that promote equitable energy access, innovation-led diversification, and sustainable financial mechanisms. Full article

Building energy consumption is a major source of carbon emissions, with the heating energy demand of rural buildings in the hot summer and cold winter (HSCW) zone having increased 575-fold over the past 15 years. This research investigated an optimized solar–air source heat pump (SASHP) system to meet the heating demand of rural residences in this region. First, a typical rural building model was developed using SketchUp, and its heating load was simulated using TRNSYS, revealing an average load of 3.38 kW and a peak load of 5.9 kW. Based on the latest technical standards, the SASHP system was designed and simulated using TRNSYS, achieving an overall coefficient of performance (COP) of 3.67 while maintaining indoor thermal comfort within ISO 7730 Category II. Subsequently, the system was optimized through GenOpt to minimize the annual equivalent cost, yielding key parameters: a 15 m² solar collector at a 40.75° tilt, a 0.35 m³ water tank, and a 10.16 kW air source heat pump. Compared with the initial design, the optimized configuration achieved reductions of 35.60% in initial investment and 32.68% in annual equivalent costs. By ensuring thermal comfort and overcoming the economic barrier, this study provides a viable pathway for adoption and promotion of renewable heating technology in rural areas. Full article

This paper compares two common dispatch policies—Load-Following (LF) and Cycle-Charging (CC)—for a photovoltaic Battery Energy Storage System (PV–BESS) microgrid (MG) with a 12 kW diesel generator, using a full-year of real 15 min PV and load data from an industrial use case in Germany. A forward time-step simulation enforces the battery State-of-Energy (SoE) window (total basis [20, 100] %, DoD = 80%) and computes curtailment, generator use, and unmet energy. Feasible designs satisfy a Loss of Power Supply Probability (LPSP) ≤ 0.03. Economic evaluation follows an Equivalent Annual Cost (EUAC) model with PV and BESS Capital Expenditure/Operation and Maintenance (CAPEX/O&M) (cycle life dependent on DoD and 15-year calendar life), generator costs, and fuel via SFC and diesel price. A value of lost load (VOLL) can be applied to unserved energy, with an optional curtailment penalty. Across the design space, a clear cost valley appears toward moderate storage and modest PV, with the baseline optimum at ≈56 kWp PV and 200 kWh BESS (DoD = 80%). Both policies meet the reliability target (in our runs LPSP ≈ 0), and their SoE trajectories are nearly identical; CC only lifts the SoE slightly after generator-ON events by using headroom to charge, while LF supplies just the residual deficit. Sensitivity analyses show that the optimum is most affected by diesel price and discount rate, with smaller shifts for ±10% changes in SFC. The study provides a transparent, reproducible workflow—grounded in real data—for controller selection and capacity planning. Full article

Many electricity providers are offering their customers an array of tariff options intended to discourage electricity consumption at specific times of the day. The problem facing a customer is whether to switch from their existing tariff to a new tariff. The aim of this paper is twofold: first, to develop two analytical methods that help residential customers evaluate when switching from a flat-rate tariff to time-varying pricing options, specifically the Time-of-Use (TOU) tariff and an event-based tariff, becomes economically beneficial, and second, to review customers’ experiences with the tariffs. The methods identify the specific consumption distributions at which the TOU or event-based tariffs are in energy- and cost-equilibrium with the domestic service tariff for residential customers. For the TOU structure, the analysis shows that customers must maintain a non-winter-to-winter-peak consumption ratio exceeding 3.0756 for cost neutrality, a condition rarely met by households with winter-dominant loads. In contrast, event-based structures require only minimal behavioral adjustments to achieve savings, with as little as 1.75% of annual consumption needing to be avoided during event periods to match domestic-service costs. Additional savings are observed with partial or full load shifting away from peak events. The findings highlight that while TOU may benefit households with high summer usage, event-based tariffs present a more practical and economically favorable option for residential customers living in the Canadian province of Nova Scotia. The paper concludes with implications for tariff selection and consumer behavior. This research will be of value to anyone considering designing a time-varying rate or having to choose between an existing flat-rate tariff and a time-varying tariff. Full article

This paper proposes a hybrid integer optimization method based on the Whale Optimization Algorithm (WOA) for the asymmetric central air conditioning chiller system of a 530-m super high-rise building in Guangzhou. Firstly, a three-hidden-layer multilayer perceptron (MLP) chiller model based on 16,276 sets of measured data and a gradient boosting regression cooling tower model based on 21,369 sets of operating condition data were constructed, achieving high-precision modeling of the energy consumption of all equipment in the chiller system. Secondly, a hybrid encoding strategy of “threshold truncation + continuous relaxation” was proposed to integrate discrete on-off states and continuous operating parameters into WOA, and a three-layer constraint repair mechanism was designed to ensure the physical feasibility of the optimization process and the safe operation of equipment. Verification across three load scenarios—low, medium, and high—showed that the optimized system’s energy efficiency ratio (EER) increased by 15.01%, 12.61%, and 11.86%, respectively, with energy savings of 12.91%, 11.18%, and 10.58%. The annual rolling optimization results showed that the average EER increased from 5.07 to 5.88 (16.1%), with energy savings ranging from 8.59% to 18.92%. Sensitivity analysis indicated that pump quantity is the most influential parameter affecting system energy consumption, with an additional pump reducing it by 1.1%. The optimization method proposed in this paper meets the minute-level real-time scheduling requirements of building automation systems and provides an implementable solution for energy-saving optimization of central air conditioning chiller systems in super high-rise buildings. Full article

Autonomous vehicles (AVs) promise improved safety and sustainability, yet their sophisticated sensing, computing, and communication systems impose auxiliary power loads of 1.5–3.2 kW, risking an increase of up to 45% in global transport energy demand by 2040 if left unaddressed. Existing energy management strategies fail to jointly optimize propulsion and autonomy subsystems under real-world dynamic traffic, treat ADAS loads as static, and lack statistically rigorous validation. This paper proposes a novel Adaptive Neuro-Fuzzy Inference System (ANFIS)-PID framework that integrates (i) 5 s V2X traffic preview, (ii) online PID gain scheduling, and (iii) energy-aware rule pruning for real-time energy allocation. Validated on a real-world trajectory dataset, the approach consistently reduces fuel consumption by up to 4.4% over pure fuzzy logic, 0.05% over FL-RWOA, 1.16% over FL-GWO, and 2.39% over FL-PSO across 25–100 km segments (paired t-test, p ≤ 0.001 on 50 random segments). Additional benefits include 18% faster transient response and 18% lower inference computational load compared to metaheuristic baselines. Scaled to fleet level, the 0.51 L/100 km average saving equates to over CAD 100 million annual savings in Canada. The hybrid neuro-fuzzy architecture offers a deployable, adaptive solution for sustainable autonomous transportation. Full article

To achieve carbon neutrality in shipping and comply with the IMO’s increasingly stringent environmental regulations, the transition of small and medium-sized workboats to eco-friendly alternatives is an urgent issue. This study quantitatively compares the fuel efficiency and operational fuel cost savings of hybrid propulsion systems based on actual operational data from a buoy maintenance vessel. The methodology comprised four stages: First, measurement equipment was installed on the vessel to collect real-sea data. Second, the collected data were processed to derive specific fuel oil consumption curves and load profiles. Third, fuel consumption models for mechanical and hybrid propulsion systems were developed. The battery capacity of the hybrid models was selected based on actual operational requirements. Performance indicators and economic analyses were conducted for a comparative evaluation. Fourth, simulation results indicated that the hybrid electric system achieves 2.02% fuel savings, translating to annual fuel savings of USD 1053.24 and a corresponding 2.02% CO₂ reduction. The hybrid mechanical system yielded 0.66% savings. These improvements are attributed to a rule-based energy management strategy of operating generators at their optimal efficiency points and shutting down main engines during low-load periods. This study provides empirical evidence supporting Korea’s 2030 eco-friendly public vessel transition plan. Full article

High-altitude cold regions suffer from severe diurnal temperature fluctuations and limited energy supply, posing persistent challenges for maintaining indoor thermal comfort. This study investigates how the spatial configuration and thermal buffer effect can be optimized to improve the energy and comfort performance of new-type vernacular housing in Lhasa, China. Based on field-measured data, two representative housing prototypes—a self-built U-shaped dwelling and a government-designed resettlement house—were modeled and validated using EnergyPlus through the Rhino/Grasshopper platform. Parametric simulations and multi-objective optimization employing the NSGA-II algorithm were conducted to optimize both annual heating load and heating-season comfort percentage. Results show that optimized configurations combining south-facing sunspaces, north-facing enclosed corridors, and attic buffer cavities can reduce heating load by up to 80% compared with the baseline model without buffer spaces, and increase comfort duration by more than 50% under identical envelope and climatic conditions. The findings quantitatively reveal how spatial hierarchy and boundary buffering synergistically enhance passive solar utilization and thermal stability. This research establishes an integrated form–space–boundary optimization framework for energy-efficient housing design in extreme climates and provides a transferable reference for sustainable building strategies in other high-altitude regions. Full article