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The recent persistent power interruption in Nigeria has significantly disrupted commercial activities, resulting in a magnificent economic loss, supply chain ripples and revenue loss. As a result, harnessing renewable energy sources to generate electricity has become a popular choice for satisfying ever-increasing load demand and reducing apprehensions on global warming and reliance on depleted fossil fuels. The goal of this research is to determine whether powering a remote community with a hybrid energy system (HES) is technologically, financially and environmentally viable. The optimum design of a standalone HES with the diesel generator (DG), photovoltaic (PV) and battery storage system (BSS) is provided in this study to satisfy the electrical power needs of a farm settlement in Kura, Nigeria by considering generation constraints and load demand. This research work presents a genetic algorithm (GA) to minimize wearing cost of the system (WCS), minimize the land needed for the installation of the DG and PV system, minimize the total annual cost of the system (TAC) and maximize the benefit to cost ratio and revenue from electricity consumption. The findings of the research showed that PV/BSS/DG system is a prospective solution to satisfy the load requirements with least TAC of 67374 $/yr, annual maintenance cost (AMC) of 2808.2 $/yr, annual fuel cost (AFC) of 32300 $/yr and annual emission cost (AEC) of 774.2023 $/yr. The outcomes of the study show that a considerable TAC, AMC, AFC and AEC savings of 26766 $/yr (28.43 %), 2808.2 $/yr (53.09 %), 32300 $/yr (25.4 %) and 774.2023 $/yr (60.69 %) are recorded when compared with using DG alone. The control approach applied in this study has reduced the operational capacity of the DG and prevented about 41157 kg/yr, 419.19 kg/yr and 22.52 kg/yr of CO 2, NOx and SO 2 emissions from being injected into the atmosphere. The simulation outcomes of the research demonstrate that the developed model can significantly reduce cost of electricity in rural communities with the application of HES. Hence, a 45.36 % cost of energy saving has been accomplished through the energy management system introduced in the proposed HES. The study's outcomes can be used as benchmarks to help many countries to enhance access to electricity, raise their living standards and stimulate economic growth. The application of the proposed HES in remote communities can result in greater economic and environmental benefits to a general population of rural dwellers. The findings of the research work are beneficial to designers, independent power providers, investors, researchers and electricity consumers that are looking for a feasible power solution. [ABSTRACT FROM AUTHOR]

The intermittent nature of renewable energy resources is a major obstacle in utilizing such resources for power generation despite their abundance. In this paper, a dynamic analysis of an integrated system based on photovoltaic (PV) panels and wind turbines coupled with pumped hydro energy storage is presented. When the power generation exceeds the power demand, surplus electricity is used to pump the water to the upper reservoir. The natural inflow of the river obviates the necessity for oversized reservoirs and saves costs. A recently introduced multi-objective equilibrium optimizer algorithm is developed to find the optimal size of the integrated hybrid energy system. The objectives are to minimize the levelized cost of electricity and maximize the reliability of the proposed system. The results show that the correlation between solar and wind power generation in the selected location is mildly strong with a value of 0.3. The total energy generation from hydro, solar, and wind resources are 77,508.7 kWh, 103,323 kWh, and 47,375.4 kWh, respectively. Comparing the results with other algorithms indicates that the equilibrium optimizer has a better performance in finding the optimal design. [ABSTRACT FROM AUTHOR]

As the global population ages, the demands imposed by medical treatment and care for the elderly are becoming increasingly pressing. To reduce energy consumption and systemic defects in the process of integrating medical treatment and care for the elderly, the authors of this study designed a highly efficient, flexible and low-carbon combined cooling, heating, and power (CCHP) system for the integration of medical and nursing complexes by using a multi-level model of optimization. The complex was modeled in DeST software to obtain the cooling and heating loads, and the general algebraic modeling system software and mixed-integer linear programming (MILP) were used for the collaborative optimization of the choice of equipment, capacity allocation, and operational strategy. The results showed that the proposed system could reduce the total consumption of electric power by 40.95 % when a semiconductor wall was installed on floors 8–12 of the complex for elderly care. The energy management strategy of the system was also optimized by using the vehicle-to-building subsystem in a novel wind–solar–storage and heat pump-based combined cooling, heating, and power system. The rates of reduction in emissions of CO 2 and NO x , and the rate of reduction in primary energy consumption of the Wind–Solar–Storage and Heat Pump (WSSH)–CCHP system were 96.5 %, 99.1 %, and 95.6 %, respectively. Finally, the heat pump-assisted liquid-gap membrane distillation (HP-LGMD) subsystem were optimized in MATLAB. The resulting gained output ratio, flux, thermal efficiency of the system, and energy consumed for water production were 0.0269, 4.22 kg/m2, 17.07 %, and 46.88 %, respectively. The proposed system is highly energy efficient, is capable of economical scheduling, and can use energy cascading, which provides guidance on sustainable development of environment and energy. [ABSTRACT FROM AUTHOR]

Water electrolysis (WE) from renewable energy sources is broadly acknowledged as a critical future route for hydrogen production. Reducing energy consumption and enhancing hydrogen production rates are both important directions for future WE technology. In this work, pulsed potential coupled anodic sulfite (SO 3 2−) electrooxidation water electrolysis (PSWE) system was proposed, enabling the production of hydrogen at low cell voltages as well as enhanced rates. The onset potential for the electrooxidation of sulfite to sulfate (SO 4 2−) is as low as 0.6 V vs. RHE. Under pulsed parameter of 0.75 V vs. RHE and frequency of 0.5 Hz, the hydrogen production rate increased by 321 % compared to constant potential of 0.75 V vs. RHE. Pulsed potential increased the local concentration of SO 3 2− anions at the anode, thereby enhancing the accumulation of total charges on the electrode surface. In the H-cell, operating voltage as low as 1.15 V could drive current density of 10 mA cm−2, demonstrating excellent hydrogen production capability and lower electricity consumption. The proposed PSWE system offers a potential route for coupling WE with intermittent renewable energy sources, as well as with low-energy consumption. [Display omitted] [ABSTRACT FROM AUTHOR]

The German government's goal of achieving climate neutrality by 2045 and increasing the use of renewable energy, particularly wind and solar power, has public support. However, the local siting of wind and solar farms is highly controversial due to land-use conflicts. We have developed a comprehensive Geographic Information System (GIS) model that integrates criteria from the literature to identify optimal locations for ground-mounted photovoltaic (GM-PV). The model is based on a holistic approach considering energy-related factors and broader environmental and climate aspects. The unique feature of the model is its integration of socio-technical and environmental criteria, including a novel approach to achieving a dual land-use climate benefit by protecting erosion-prone soils and conserving soil carbon in areas prone to organic matter decomposition and associated CO 2 release. Our multi-criteria GM-PV model includes 12 restrictions and five suitability criteria representing key socio-technical, economic and environmental aspects. Scenario analysis highlights the sensitivity of Germany's GM-PV potential to defined criteria. In Scenario 1, with minimal constraint, 14.2 % of Germany's land is available for GM-PV, decreasing to 1.9 % in the highly constrained Scenario 12. Suitable areas (>10 ha) account for 0.4 % of Germany's land area, which could cover 8.1 % of Germany's electricity consumption in 2045 in the highly restricted scenario. The spatial distribution results show that the innovative approach of the model changes the preference of GM-PV locations based on factors such as solar radiation in the south and soil carbon storage in the north of Germany. The application of restriction and suitability criteria significantly reduces the potential for GM-PV in Germany but also potential pitfalls for decision-makers. The GIS model can be applied in regional context to integrate stakeholder values and generate region-specific scenarios, as criteria and thresholds can be easily adapted to regional characteristics, preferences, and concerns, including those related to agriculture, biodiversity, and social acceptance. • The model considers climate aspects and integrates socio-technical and ecological criteria. • The novel approach includes soil erosion and CO 2 release from the decomposition of organic matter. • Ground-mounted PV meets at least 8.1 % of Germany's electricity demand in 2045, using 0.4 % of the country's land. • The innovative approach of the model changes the preferred locations for Ground-mounted PV. • The model can integrate stakeholders' local preferences and generate region-specific scenarios. [ABSTRACT FROM AUTHOR]

Stand-alone renewable energy systems, which harness and use electricity without connection to a distribution grid, can benefit from using resource forecasts when making real-time decisions on how to manage power. An example of this is an ocean observation system that uses a wave energy converter (WEC) and battery bank to produce and store electricity in order to meet electrical load requirements for oceanographic sensors and instrumentation. By using wave forecasts to optimize the power consumption of this system, it is possible to reduce the size of the WEC and battery bank needed, thereby reducing the overall system's cost and complexity. In this paper, we assess the benefits of forecasting for a generic wave-powered ocean observation system. We model an observation platform powered by a WEC and battery-storage system that can switch between four power states, full power: 600 W, medium power: 450 W, low power: 45 W, and survival mode: 1 W. To determine which power state to enter over time, we present a stochastic optimization method that interprets wave forecasts and system information to select a power state on an hourly basis and simulate over two months of consecutive decisions. Using this simulation framework, we compare 8 power management strategies across a range of WEC sizes (3–5 m) and battery capacities (2.5–35 kWh). We find that it is possible to maintain full (600 W) power consumption over the entire simulation window with a 5 m diameter WEC and 25 kWh battery bank, which is on the upper end of the ranges evaluated. To employ a smaller WEC or battery, load flexibility is required. We find that forecast-based methods for this power management handle tradeoffs in performance (e.g., cumulative power consumption, reducing intermittencies and meeting scheduled load targets) more effectively than power management strategies that do not use forecasting. Overall, our results indicate that forecasting for our stand-alone renewable energy system is most impactful when some loads must be met on or within a defined schedule. • A forecast-based method for managing a load met by wave energy is presented. • This method handles performance tradeoffs better than non-forecasting strategies. • These benefits are most impactful when loads must be met on or within a schedule. • Forecast uncertainty has notable influence, suggesting opportunities for improvement. [ABSTRACT FROM AUTHOR]

To advance sustainable development and emission reduction efforts within the maritime industry, a novel combined cooling, heating, power, and storage (CCHPS) system is proposed. This system comprises a cogeneration system (ORC + ARC) and a thermal energy storage (TES) system. Initially, optimal working fluids are selected for the ORC and TES discharge systems. Subsequently, an analysis is conducted regarding the correlation between sensitivity parameters and system performance. Then, the cogeneration system's optimum design parameters are determined utilizing the multi-objective grey wolf optimization (MOGWO) algorithm. Finally, the TES system is analyzed and matched with the diesel generators to meet the ship's electricity demand. The CCHPS system achieves optimal thermal efficiency, payback period, annual CO 2 emission reduction, and annual fuel savings of 30.07%, 6.22 years, 8910.49 tons, and 2791.74 kL, respectively. In contrast to the TES-absent system, the CCHPS system exhibits a 12.88% increase in thermal efficiency, along with a 25.48% improvement in annual fuel savings and annual CO 2 emission reduction. [Display omitted] [ABSTRACT FROM AUTHOR]

The escalating demand for electricity and the imperative to reconstruct underprivileged areas in Afghanistan necessitates a resilient energy supply system. This study advocates for the implementation of a cost-effective and high-performing microgrid in a region situated in the northern of Kandahar City, Afghanistan. Utilizing a mix of diesel engines, batteries, wind, and solar energy sources, the microgrid aims to provide a sustainable and eco-friendly solution to meet the electricity requirements. Employing the HOMER software for comprehensive analysis, the proposed microgrid configuration comprises a 3.69 kW PV, a 1.50 kW diesel generator, and 27 units of 1 kWh LA batteries. The study investigates six different configurations to identify the optimal solution based on community-specific criteria. Factors such as energy generation, cost, and system performance are rigorously evaluated by the software, culminating in the selection of components that constitute the hybrid system. The optimal configuration includes a capital cost of 5962 $, a net present cost (NPC) of 10108$, operating and maintenance (O&M) costs amounting to 320.69$, and a cost of energy (COE) at 0.190$/kWh. These results show the viability and economic feasibility of the proposed microgrid as a sustainable energy solution for the studied community in Afghanistan. [ABSTRACT FROM AUTHOR]

The increase in electricity consumption in rural areas has led to an overall increase in the peak load in both winter and summer, challenging the reliability of low-voltage distribution networks. A typical rural house in Xi 'an area of Shaanxi Province is considered a case study. To aid the investigation, a ground source heat pump system is developed, installed, and used as the experimental platform. The simulation model of the rural residential building's energy consumption is established, and the demand response peak regulation strategy for the rural residential building in winter is investigated. Using the developed model, two demand response peak regulation models, Direct Compressor Control Mechanism (DCCM) and Thermostat Set-point Control Mechanism (TSCM) are formulated. Combined with a long-term and short-term memory neural network power load forecasting model, a simulation is carried out to analyze and study the indoor temperature, operating energy consumption, and other parameters under the two peak regulation scenarios. The proposed strategy is assessed and evaluated. Compared with the baseline model, the proposed strategy allows a reduction in the total building operating energy consumption of 41.9 % for the DCCM model and 17.2 % for the TSCM model. [ABSTRACT FROM AUTHOR]

Rooftop solar is increasingly promoted as a source of low-carbon household energy; however, there is a plausible concern that solar installations might influence energy consumption patterns in ways that undermine potential environmental benefits. In this study, we examine the impact of residential rooftop solar panels on energy usage in Vietnam. Leveraging a comprehensive and unique panel dataset, we employ a difference-in-differences identification strategy to estimate the effects of solar installation on consumption. Our models reveal that households installing solar panels reduce grid consumption (typically carbon-intensive) by approximately 3.6 %. This reduction occurs concomitantly with an increase in total consumption of around 16 %, indicating a substantial rebound effect from solar panels. Nonetheless, dynamic models suggest a diminishing trend over time for both the decline in grid usage and the rebound effect, leveling off to 1.5 % and 3.5 %, respectively, within one year of solar installation. Acknowledging the marked differences in household consumption behavior and electricity demand dynamics between developing and developed nations, our research provides valuable insights into the understanding of the solar rebound effect and its dynamics over time. [ABSTRACT FROM AUTHOR]

Hydrothermal liquefaction (HTL) occurs at high pressures (160–200 bar) and temperatures (300–350 °C), where the conditions in the reactor drive the conversion of wet biomass to biocrude oil (BC). Before drop-in, BC needs further upgrading (hydrogenation) to increase the energy content and decrease the concentration of heteroatoms. Normally this is done in hydrogenation reactors at high pressures and temperatures, which require an external high pressure H 2 source. The main HTL by-product is process water (PW), which is either recirculated or cleaned before being disposed. Herein we investigated a membrane-less electrochemical method, which uses PW as hydrogen source and can be seamlessly integrated in HTL plants. We demonstrate a proof-of concept of a membrane-less electrochemical reactor that oxidizes PW at the anode and uses hydrogen in form of protons and electrons to hydrogenate BC at the cathode. We report BC upgrading (atomic H/C ratio increase up to 17 %) at high-pressure (up to 100 bar) and high-temperature (up to 200 °C), which mimic the conditions of an actual HTL plant. The proof-of-concept discussed here is a novel way of increasing the hydrogen content of biocrude oil within HTL reactor by using electricity, with no need of an external high-pressure H 2 source. [Display omitted] [ABSTRACT FROM AUTHOR]

Hydrothermal liquefaction (HTL) occurs at high pressures (160–200 bar) and temperatures (300–350 °C), where the conditions in the reactor drive the conversion of wet biomass to biocrude oil (BC). Before drop-in, BC needs further upgrading (hydrogenation) to increase the energy content and decrease the concentration of heteroatoms. Normally this is done in hydrogenation reactors at high pressures and temperatures, which require an external high pressure H 2 source. The main HTL by-product is process water (PW), which is either recirculated or cleaned before being disposed. Herein we investigated a membrane-less electrochemical method, which uses PW as hydrogen source and can be seamlessly integrated in HTL plants. We demonstrate a proof-of concept of a membrane-less electrochemical reactor that oxidizes PW at the anode and uses hydrogen in form of protons and electrons to hydrogenate BC at the cathode. We report BC upgrading (atomic H/C ratio increase up to 17 %) at high-pressure (up to 100 bar) and high-temperature (up to 200 °C), which mimic the conditions of an actual HTL plant. The proof-of-concept discussed here is a novel way of increasing the hydrogen content of biocrude oil within HTL reactor by using electricity, with no need of an external high-pressure H 2 source. [Display omitted] [ABSTRACT FROM AUTHOR]

Due to the inherent uncertainty and the mismatch between renewable energy output and load demand, renewable energy-based system optimization is increasingly important in China. Therefore, electricity demand response (EDR) is critical to the stability and efficiency of an integrated renewable energy system (IRES). The customers' demand response under the time-of-use (TOU) mechanism is the key to the entire process. However, how to optimize integrated renewable energy system based on accurately identifying the electricity demand response participation of customers is one of the main issues at this stage. To solve the problem, this paper presents a novel approach for integrated renewable energy system optimization considering electricity demand response management and multistage energy storage systems from the perspective of Fujian Province, China. To enable large-scale renewable energy integration, the original output is processed using the Hampel identifier (HI)-Savitzky-Golay filter (SGF) technology. A machine learning (ML)-based identification model is developed for EDR to determine whether the customers are participating or not. Driven by the time-of-use mechanism, customers can make dynamic adjustments based on the Logistics function. After that, an integrated renewable energy system model optimization strategy is proposed based on satisfying customers' electricity demand response. Throughout the optimization process, the multistage energy storage system plays a vital role in the residual fluctuation absorption for renewable energy filtering, the dynamic adjustment process of the demand response, and the integrated renewable energy system optimization. Through extensive case studies and discussions, it is demonstrated that random forest (RF) and support vector machine (SVM) reach 80 % identification accuracy with a 20 % testing ratio. According to the optimization approach proposed in this paper, the minimum operation cost can be calculated to be 9.336*106 CNY. The methodology presented in this paper establishes a special relationship between electricity demand response identification and dynamic adjustments, and provides an optimization model for Fujian Province, China, which is a reliable reference for future work. [ABSTRACT FROM AUTHOR]