Renewable Generation Research Articles

Design of a hybrid solar and biomass-based energy system integrated with near-zero energy building: Techno-environment investigation and multicriteria optimization

The current research aims to meet the energy needs of a group of residential buildings in Norway with the least amount of carbon dioxide emission and the greatest amount of renewable energy. The supply side based on the renewable renewable-based energy system is planned and scaled using the real-time data use of domestic hot water (DHW), heating and electricity necessary for the buildings. PVT panels are used in the hybrid solar and biomass-based energy systems to produce both the DHW requirements and the electricity production. The digester is used with the heat pump, which generates heat. A double-effect absorption refrigeration system is also utilized to provide the necessary cooling requirements. On the supply side, the management of the heat streams and the redirection of flows are done using a rule-based regulating system. The whole plant's size is supplied, and the dynamic energy simulation is run. The primary deciding criteria for heating the buildings are the costs of electricity and biomass. The whole system is then optimized depending on operating circumstances, and the outcomes are compared to the design point. PVT may be used to create more than 80% of the yearly DHW. Furthermore, summertime radiation accounts for 64.8% of cooling output since it is more intense and may be converted into cooling energy. Digester/CC also contributes 66.55% of the building's heating, showing that the designers should rely on biomass as wintertime energy costs are higher. The parametric study demonstrates that increasing PVT time and tank capacity has varied effects on efficiency and emissions. Also, On winter days, there was a significant drop in renewable energy generation from summer to autumn, from 82.7 MWh to 28.52 MWh. The optimization results show that at the TOPSIS point, the total cost, efficiency, and emission index are 9.73 $/hr, 36.8%, and 7.75kg/MWh, respectively.

Towards a Standardized LCOE Calculation for Informed Decision-Making in Energy Policy and Investment: Application to the Colombian Context

The Levelized cost of electricity - LCOE represents a constant cost per unit of generated electrical energy, resulting from the analysis of the total costs throughout the life cycle of a generation plant. Its widespread use, thanks to its simplicity of calculation and potential of standardization, has made it one of the primary criteria for comparing electricity generation technologies. However, in the pursuit of simplification and generalization, certain aspects associated with the socioeconomic context of the region, as well as accounting and financial concepts, are excluded due to externalities or incentives related to regulatory and fiscal policies. These exclusions affect the accuracy of LCOE and introduce uncertainty when using it as a criterion for investment decision-making or allocation of public resources for the development of renewable sources. This article proposes a clear and standardized methodology for calculating LCOE, which allows for a fair and precise comparison of renewable energy generation options in rural areas. It contributes to informed and transparent decision-making in the fields of energy policy and public investment for expanding electricity service coverage. The proposed methodology is based on the financial cash flow matrix to address variability sources in the calculation, considering the local context of the generation project.

Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence

The rapid increase in biomass and plastic waste poses significant environmental challenges. Co-pyrolysis of biomass with plastic wastes offers a promising avenue for sustainable waste management and renewable energy generation. This study covers several novel aspects: First, it investigates the impacts of feedstock composition and operating conditions in pyrolysis (individual feedstock) and co-pyrolysis (biomass and plastic wastes). The study reveals that synergistic effects, specifically improved yields and optimized temperature, exist in the co-pyrolysis of biomass and plastic wastes compared to individual feedstock. Secondly, a suitable blended machine learning predictive model (with Random Forest, Gradient Boosting Regressor, and XGBoost) and robust optimization framework are developed to address model accuracy, non-linear interactions, and uncertainties in pyrolysis such as temperature, heating rate, and biomass-to-plastic ratio. This study predicts the bio-oil yield quantitatively (amount) and qualitatively (composition) with high accuracy (R2 > 0.97). Thirdly, key factors contributing to yield include plastic content (18 %) and biomass type (13 %) have been identified through Gini feature importance and Shapley Additive Explanation (SHAP) analysis. Furthermore, multi-objective optimization techniques reveal the most optimal bio-oil yield under specific conditions, supported by uncertainty analysis, which confines bio-oil yield to a range of 30–50 %. Finally, it also demonstrates a case study to find the optimal bio-oil yield and quality conditions using co-pyrolysis of local resources, i.e., biomass (wood and bagasse) and plastic wastes. The case study suggests optimal conditions like > 50 °C heating rate, <50 min pyrolysis time, and > 60 % plastic content in a blend of wood and HDPE. This study assists industries and policymakers to assess and understand the viability of co-pyrolysis, optimal design parameters, and process impacts.

Temporal asynchrony analysis for dynamic operation of hydraulic-thermal-electricity multiple energy networks based on holomorphic embedding method

Analyzing the operational states of multiple energy networks (MEN) in multi-energy systems is crucial for ensuring system stability. The dynamic operational characteristics of different energy flows pose challenges for computational analysis. Traditional steady-state methods are inadequate for addressing the dynamics of MEN, especially when dealing with temporal discrepancies between hydraulic and thermal flows in thermal networks (TN) and the heterogeneity between TN and electrical networks. Therefore, this paper proposes a novel holomorphic embedding method (HEM) based on multi-stage decomposition method. The developed HEM constructs a time coefficient matrix and utilize inner-outer loop recursion to handle the time lag between thermal flow and hydraulic flow in the TN. Additionally, we reconstruct a holomorphic matrix, integrating hydraulic flow to bridge thermal and electric power flows, thereby improving the operational heterogeneity among different networks. Real-case simulations show that when the Taylor expansion order in HEM is equal to 4, the proposed method achieves a mere 1% discrepancy from actual operational data, enhancing computational efficiency by 60% compared to the Newton-Raphson method. Moreover, in this real-case, the TN exhibits a maximum delay response time of 180s compared to electrical networks. Exploiting this delay time effectively increases renewable energy generation within multi-energy systems by 961.58kW per day.

Portfolio effects in green hydrogen production under temporal matching requirements

This article investigates temporal matching requirements between electrolytic hydrogen production and dedicated renewable electricity generation for hydrogen to qualify as “green”. In contrast to previous studies which found that a more granular matching increases production costs, we study cost advantages for hourly matching through technological and spatial diversification. To this end, we develop and apply a linear cost-optimization model to quantify the resulting portfolio effects. We identify two types of portfolio effects, “technological” and “locational” ones, and quantify these for different portfolio sizes and types of power generation technologies. Portfolio effects in Germany turn out to be in the range of 3–8% when aggregating two locations, and up to 21% for a nation-wide portfolio. Finally, the implications of our findings in terms of discrimination against small players and for the modeling of temporal matching requirements are discussed.

A three-stage framework for optimal site selection of hybrid offshore wind-photovoltaic-wave-hydrogen energy system: A case study of China

The integration of offshore wind-photovoltaic-wave-hydrogen production is a sustainable energy development concept that could smooth the intermittency of renewable energy generation, reduce energy abandonment, and improve energy efficiency. However, the successful deployment of a hybrid offshore wind-photovoltaic-wave-hydrogen energy system is premised on the selection of an appropriate location, which necessitates a robust framework to support this decision. This study proposes a three-stage decision framework based on Geographic Information System and multi-criteria decision-making to determine the optimal location from macro and micro perspectives. To ensure the effectiveness of site selection, it develops a comprehensive criteria system, including exclusion criteria and evaluation criteria, encompassing geographical, resource, economy, risk, and sustainable potential aspects. Then, the spatial simulation of alternative sites is conducted according to exclusion criteria to rule out infeasible alternative sites. The multi-criteria decision-making in the third stage is performed in a rough-fuzzy environment to eliminate the uncertainty in decision-making. Finally, a case study is conducted on Hainan Island, China. The results show that the western sea area of Dongfang City is the optimal location to deploy the hybrid offshore wind-photovoltaic-wave-hydrogen energy system. The proposed framework offers a reference for practical offshore renewable energy project implementation.

Optimal dimensioning of renewable energy generation and storage systems

With high energy demand and large available area, agricultural farms offer significant potential for renewable energy investments, like photovoltaic systems and electrical energy storages. However, the profitability of such investments depends strongly on self-consumption, so accurate planning requires computation-intensive simulation and optimization considering local consumption. This study presents a novel methodology for the optimal dimensioning and configuration of photovoltaic systems and electrical energy storages using efficient techniques from continuous non-linear optimization. Combining physical and economic models with measured consumption data, an investment’s net present value over 20 years is maximized. Using gradient-based solver WORHP, the simulation, optimal control, and optimal dimensioning of the local energy system are calculated simultaneously, allowing for efficient computation over an entire year of hourly data to capture both daily and seasonal variations.The approach is demonstrated with simple use cases, including an exemplary day of a dairy farm’s consumption, for which optimal systems with and without storage achieve 77% and 43% of autarky, respectively. Saturation effects of optimal plant size can be observed when sizes are large enough for optimal self-consumption but not expanded further for grid export. With energy storage, this saturation is reached at higher values. Optimizing photovoltaic plants with different orientations to match the specific consumption patterns characteristic of the dairy farm achieves similar autarky as a single plant while reducing investment costs by more than 20%. While thorough validation and comparison against heuristic methods predominantly used in the field is part of ongoing research, the presented use cases demonstrate the flexibility and efficiency of the proposed method and highlight its promise as a planning tool in the agricultural domain and beyond.

Renewable energy communities: Democratically legitimate agents in governing the energy transition?

It is crucial that the energy transition enfolds democratically, to increase its legitimacy and improve its outcomes. Although practitioners and scholars increasingly point to renewable energy communities (RECs) as legitimate agents for governing a democratic energy transition, RECs' democratic practices are poorly understood, which challenges assumptions about their legitimacy. We therefore analyzed how and to what extent democratic legitimacy is being pursued and met by RECs in their governance of renewable energy generation projects. Our comparative case study examined four different RECs in Utrecht, The Netherlands. We found that three out of the four studied RECs broadly meet the principles of energy democracy in the initial, developing and implementation phase of their energy generation projects. Significant differences between principles and RECs were found, which refutes the simplistic general assumption that RECs are either fully democratically legitimate or are not democratically legitimate at all. In reality, RECs face several trade-offs between democratic principles, which arise from the different legitimacy needs related to the REC's stage of maturity and the type of energy source it uses. To overcome these trade-offs and uphold legitimacy internally as well as with various stakeholders, RECs strategically organize participation and decision making in different governance spaces and prioritize certain specific legitimacy principles over others. Combining the concepts of energy democracy and democratic legitimacy has brought novel theoretical insights to the fore, and we recommend other researchers to further bridge these distinct but related fields of study.

The effect of green hydrogen feed rate variations on e-methanol synthesis by dynamic simulation

Methanol is a promising fuel and important intermediate chemical in the transformation of renewable power to chemical products since it can be directly synthesized from captured CO2 and electrolytic H2. However, the intermittency of renewable power generation poses challenges to green methanol production process design and operation, necessitating high operational flexibility to facilitate coupling with intermittent renewable power.In this study, a green crude methanol (a mixture of methanol and water from methanol synthesis) production process was dynamically modeled. The results show that the minimum load of the model is 20%, with maximum allowable ramping rates of 3.25%/minute for ramp-down and 2.10%/minute for ramp-up between full and minimum load. The introduction of a standby mode, in which a make-up H2 stream is supplied when electrolytic H2 is unavailable, allows continuous operation of the process at the minimum load. With the constructed control structure, the model demonstrates that the process can effectively handle continuous variations of electrolytic H2 input.

Bacterial synergy and relay for thermophilic hydrogen production through dark fermentation using food waste

BackgroundFood waste is a significant global issue, with 1.3 billion tons generated annually, a figure expected to rise to 2.1 billion tons by 2030. Conventional disposal methods, such as landfilling and incineration, present environmental challenges, including methane emissions and pollution. Hydrogen production through dark fermentation presents a sustainable alternative, offering both waste management and renewable energy generation. This study investigates the bacterial synergy and relay mechanisms involved in thermophilic H2 production using food waste as a substrate. PurposeThe primary aim of this research was to analyze the metabolic pathways and dynamics of functional genes prediction during thermophilic H2 production from food waste, focusing on the role of bacterial consortia in enhancing H2 yields. MethodsA continuous stirred-tank reactor (CSTR) was operated using food waste as the substrate and a thermophilic bacterial consortium as the inoculum. The study utilized genomic analysis to monitor changes in bacteriobiome composition over time and to correlate these changes with H2 production. Volatile fatty acids (VFAs) and H2 production rates were analyzed using gas chromatography and high-performance liquid chromatography (HPLC). The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was employed to identify functional genes involved in the fermentation process. ResultsThe study identified key bacterial species, including Caproiciproducens and Caproicibacter, that dominated during the later stages of H2 production, replacing earlier dominant species such as Clostridium. These shifts in bacterial dominance were strongly correlated with sustained H2 production rates ranging from 353 to 403 mL·L−1·h−1, with H2 concentrations between 55 % and 62 % (v/v). Functional gene analysis revealed significant pathways related to polysaccharide degradation, glycolysis, and dark fermentation. ConclusionsThis study highlights the importance of bacterial synergy and relay in maintaining continuous H2 production from food waste under thermophilic conditions. The findings provide insights into optimizing biohydrogen production processes, emphasizing the role of specific bacterial species in enhancing efficiency. These results contribute to the development of sustainable waste management strategies and renewable energy production.

Flexible electricity market clearing zones

Zonal markets and nodal pricing are the dominant designs for liberalized electricity markets. We propose an alternative design that changes zones in each bidding period according to the estimated most efficient dispatch. These flexible electricity market clearing zones consider the grid’s physical constraints to a larger degree than zonal markets but maintain their bidding simplicity and few price areas. We propose a proof-of-concept framework for flexible electricity market clearing zones, including a method to enumerate all zonal configurations. We illustrate the performance of this framework on a case study in the Nordic countries using flow-based market clearing (FBMC), considering a model for the day-ahead market and a real-time balancing market. Our results suggest that flexible electricity market clearing zones on sequential day-ahead and real-time balancing markets achieve costs slightly above nodal stochastic clearing. But, contrary to stochastic clearing, it can guarantee short-term revenue adequacy and cost recovery. Moreover, the flexible market design increases day-ahead market price levels and price variability at the nodal level, particularly in scenarios with high renewable generation, demonstrating its capacity to align price signals with network congestion and real-time supply conditions. Flexible electricity market clearing zones can thus facilitate the integration of renewables by enhancing system adaptability and promoting more efficient resource allocation.

Increasing Renewable Energy Penetration on Low-Voltage Networks: An Expert Knowledge Approach

While South Africa is deemed one of the countries with the highest irradiation levels, it still utilises coal as its primary energy source due to its abundance. Due to the world-wide drive towards carbon neutrality, residential, commercial, agricultural, and industrial consumers are considering small-scale embedded generation systems. The National Rationalised Specifications 097-2-3 document specifies the scale of the embedded generation capacity a consumer is allowed to install. However, specifications do not yet make the required provisions for the addition of energy storage. The effective collective management of the grouped small-scale embedded generation systems could provide a high level of energy security and increase the percentage of renewable energy generation in the total energy mix. Potential challenges come into play when considering the stochastic nature of photovoltaic generation and its effect on the storage capacity and the dispersion in load profiles of the residential units typically present on a low-voltage network. This paper contributes by investigating the utilisation of photovoltaic generation in conjunction with storage as the basis for virtual power plant control, with the aim to safely increase renewable energy penetration and improve energy security, all while remaining within the South African low-voltage regulatory limits. A two-level virtual power plant controller is proposed with the dispersed energy storage units as the primary controllable resources and the dispersed photovoltaic generation as the secondary controllable resources. The objective of the controller is to achieve nodal energy management, energy sharing, and ancillary service provision and finally to increase renewable energy penetration. A representative single-feeder low-voltage network is simulated, and test cases of 50% and 75% renewable energy penetration are investigated as the basis for evaluation. The proposed controller architecture proved to maintain network integrity for both test cases. The adaptability of the controller architecture was also confirmed for a changed feeder topology; in this case, it was a multi-feeder topology. Future work is warranted to inform policy on the allowed levels of renewable energy penetration to be based not only on demand but also on the level of energy storage present in a network.

ENHANCING EFFICIENCY AND SUSTAINABILITY: GREEN ENERGY SOLUTIONS FOR WATER SUPPLY COMPANIES

Water supply enterprises significantly impact local communities by providing essential services. These companies face high electricity costs for water extraction, purification, and transportation, affecting efficiency and reliability. Therefore, implementing innovative technologies to enhance sustainability in the water supply sector is crucial. This article explores the opportunities and strategies for renewable energy transition at water supply companies. Using investment, sensitivity, and strategic analyses, as well as a case study approach, the research examines technologies, conceptual frameworks, mechanisms, and approaches to integrate green power into water supply operations, addressing high energy costs and promoting sustainability. The article identifies solar, wind, hydroelectric, biomass, and geothermal energy technologies as the most prominent renewable power solutions for water supply enterprises. The developed conceptual framework for implementing these technologies includes needs assessment and goal setting; resource assessment and technology selection; system design and integration; financing and investment; regulatory compliance and permitting; stakeholder engagement and capacity building; and monitoring, evaluation, and continuous improvement. The mechanisms and approaches to integrate green energy solutions within the developed framework can involve on-site renewable energy generation, power purchase agreements, energy storage and microgrid systems, energy efficiency and demand management, and collaborative and community-based models. As a case study, the article examines a 120-kW solar power plant project for a water supply enterprise, demonstrating profitability with a net present value of 60,370 USD and an internal rate of return exceeding 21%. The project's payback period is estimated at 8.38 years, acceptable within industry standards. Sensitivity analysis indicates the project's financial resilience. Increasing electricity prices will boost profitability, justifying the solar power plant investment amid inflation and economic instability. Additionally, the project ensures reliable water transport and environmental benefits by reducing CO2 emissions through solar energy use. Thus, transitioning to renewable energy at water supply enterprises is feasible and essential for long-term sustainability, transforming operations to be more resilient, efficient, and environmentally friendly.

The Sharing Energy Storage Mechanism for Demand Side Energy Communities

Energy storage (ES) units are vital for the reliable and economical operation of the power system with a high penetration of renewable distributed generators (DGs). Due to ES’s high investment costs and long payback period, energy management with shared ESs becomes a suitable choice for the demand side. This work investigates the sharing mechanism of ES units for low-voltage (LV) energy prosumer (EP) communities, in which energy interactions of multiple styles among the EPs are enabled, and the aggregated ES dispatch center (AESDC) is established as a special energy service provider to facilitate the scheduling and marketing mechanism. A shared ES operation framework considering multiple EP communities is established, in which both the energy scheduling and cost allocation methods are studied. Then a shared ES model and energy marketing scheme for multiple communities based on the leader–follower game is proposed. The Karush–Kuhn–Tucker (KKT) condition is used to transform the double-layer model into a single-layer model, and then the large M method and PSO-HS algorithm are used to solve it, which improves convergence features in both speed and performance. On this basis, a cost allocation strategy based on the Owen value method is proposed to resolve the issues of benefit distribution fairness and user privacy under current situations. A case study simulation is carried out, and the results show that, with the ES scheduling strategy shared by multiple renewable communities in the leader–follower game, the energy cost is reduced significantly, and all communities acquire benefits from shared ES operators and aggregated ES dispatch centers, which verifies the advantageous and economical features of the proposed framework and strategy. With the cost allocation strategy based on the Owen value method, the distribution results are rational and equitable both for the groups and individuals among the multiple EP communities. Comparing it with other algorithms, the presented PSO-HS algorithm demonstrates better features in computing speed and convergence. Therefore, the proposed mechanism can be implemented in multiple scenarios on the demand side.

Generación renovable eólica y fotovoltaica en Ecuador: Una revisión sistemática de literatura

INTRODUCTION. Photovoltaic and wind renewable generation has grown exponentially in recent years worldwide, in Ecuador this technology has not been the exception, as several photovoltaic and wind power plants have been installed, increasing the generation of renewable energy. OBJECTIVE. This article presents a systematic review of the literature on operational photovoltaic and wind power plants in Ecuador, offering a perspective on the renewable sources connected to the national energy system. METHOD. Through a bibliographic search in the Scopus database, 8 publications were obtained that met the eligibility criteria, in addition to reports issued by government entities, to ensure that the information and technical aspects are accurate. RESULTS. The documentary analysis allows us to know the current status of photovoltaic and wind power plants, identifying their installed capacity, technology used, and operational characteristics. DISCUSSION AND CONCLUSIONS. The information collected provides a solid basis for understanding the current status and development prospects of photovoltaic and wind power generation in Ecuador. Despite certain limitations related to the availability of data in open sources, it was possible to obtain significant information on the main renewable plants in the country. These results serve as a basis for future research aimed at the expansion and optimization of renewable energies in the national context..

Weather as Fuel — The Wicked Problem of Renewable Energy

Abstract A key component of mitigating climate change is reducing society’s dependence on fossil fuels, which will require replacing them with clean energy sources. The key strategy being pursued in the United States (and most other countries) is to rapidly scale up our use of renewable energy sources. Electricity generation provided by wind turbines and solar photovoltaic panels, in particular, has been growing rapidly, and most energy experts expect them to be the dominant forms of electricity generation in the future. Given the dependence these energy sources have on weather conditions (windiness and cloudiness, respectively), it is useful to view weather as the “fuel” for these renewables in the same way that coal or natural gas serves as the fuel in generating electricity in a fossil-fuel power plant. This paper uses a novel thought experiment to drive home this concept, while also exploring the complexity of providing reliable power on a grid dominated by renewable generation. The paper then shows how the transition to renewable energy falls into the class of problems known as “wicked problems,” and discusses approaches that will be needed to make progress. The current status of addressing these complex issues is reviewed through the lens of the wicked problem paradigm.

Collaborative Optimization of Multi-regional Integrated Energy System Based on Improved Beluga Whale Optimization Algorithm

With the installed capacity of the renewable energy power generation is growing at a high speed, a large number of the renewable energy is connected to the grid, the energy problem has been solved to a large extent, but the ensuing problems can not be ignored, the first is the consumption of the renewable energy, which is followed by the stability problem of the power system, and a multi-regional integrated energy system (MRIES) is constructed to solve the problem. In view of the wind power uncertainty, the absorption treatment is carried out by the equipment layer and the optimization layer respectively. A hybrid energy storage system (HESS) is introduced in the equipment layer to suppress the influence of the wind power uncertainty on the system stability. A combination of the convolutional filtering algorithm, the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise algorithm and the fuzzy control algorithm is introduced in the optimization layer to develop the charging and discharging strategy of the HESS. With the strategy, the impact of the electric power fluctuations on the power system during the optimization process can be reduced largely. Then, on the basis of fully considering the energy coupling in different equipments, a collaborative optimization model of the MRIES is constructed. And the integrated demand response model considering the time-of-use electric price is introduced in the load side. Finally, the improved Beluga optimization(IBWO) algorithm is developed to optimize the model. The optimization results show that the IBWO algorithm plays a good optimization effect both in the participation of energy supply equipments and the economy, plays a collaborative optimization role in the MRIES and ensures the stability of the whole power system.

Energy management and demand side management framework for nano-grid under various utility strategies and consumer’s preference

This research proposes a day-ahead scheduling utilizing both demand side management (DSM), and Energy Management (EM) in a grid-tied nanogrid comprises of photovoltaic, battery, and diesel generator for optimizing the generation cost and the energy not supplied (at grid-outage). Wider terminology is introduced to combine both load controllability (considered in traditional DSM), and interval capability to accommodate additional loads defined as flexible, non-flexible, and semi-flexible intervals. Moreover, the user selection for EM or combined operation of EM with DSM at different degrees of interval flexibility is defined as user preference. In addition, three utility’s operations are considered denoted as fixed rate pricing (FRP), time-of-use (ToU) pricing, and FRP with grid-outage. Hence, the suggested framework utilizes the opportunities of generation diversity, the electricity pricing strategy, and the load flexibility. The obtained result show that, DSM with flexible intervals reduces the cost by 21.02%, 25.23%, and 18.15% for FRP, ToU, and FRP with grid-outage scenarios respectively. And cost reduction by 20.41%, 22.42%, and 17.81% for DSM with semi-flexible intervals and 16.24%, 21.15%, and 13.8% for DSM with non-flexible intervals. This cost reduction is associated with full utilization of renewable energy generation and reduction of the energy from/to battery which enhances its lifetime or reduces the required battery size during design stage for cost and provisions saving in flexible and semi-flexible intervals. A hybrid optimization technique of Moth-flame optimization algorithm, and Lagrange’s multiplier is proposed and confirms its effectiveness with detailed comparison with other techniques.

Shining a Light on Equitable Solar Energy: Addressing Challenges and Enhancing Opportunities for Business Participation in Community Solar

Solar energy plays a vital role in achieving the United States’ decarbonization goals. Enabling community solar projects is an underutilized strategy for increasing renewable energy generation and offers potential solutions for addressing disparities in solar energy distribution. Although community solar use has been initiated through utility-scale platforms, less attention and efforts have gone into facilitating community solar programs that collaborate with businesses who use distributed solar (i.e., rooftop) panels. Engaging businesses in community solar programs provides opportunities for commercial buildings to expand solar energy panels, maximizing use of available space for solar installations and decreasing land-use for solar farms, increasing use and energy resiliency at the residential level, and improving equitable access. We propose three policy recommendations: (1) Renewing and expanding the Sunny Awards recognition program; (2) Modifying tax incentives for businesses to reduce costs of solar installation and encourage energy distribution; and (3) Introducing a new business model for energy distribution. These recommendations provide strategies and insights for encouraging businesses to implement community solar on a broader scale.

Anaerobic digestion of agricultural waste for biogas production and sustainable bioenergy recovery: a review

AbstractAnaerobic digestion constitutes a sustainable method for waste management and renewable energy generation, addressing significant environmental and societal challenges. The growing global waste crisis and the increasing momentum toward sustainable energy solutions emphasize the critical need to enhance anaerobic digestion technology for improved efficiency and environmental advantages. This process mitigates waste accumulation, enhances energy security, and reduces greenhouse gas emissions, providing a feasible solution within the framework of a circular bioeconomy. Here, we review the principles of anaerobic digestion and biogas production, focusing on agricultural waste and the utilization of biogas for energy within a sustainable framework. We specifically explore biogas applications in rural and industrial settings, assess the environmental impacts, and discuss the regulatory landscape with insights from China and Europe. This study reveals that the strategic implementation of anaerobic digestion can markedly improve energy yield and sustainability, demonstrating how focused policies and advanced technological practices can optimize biogas utilization. The review enhances comprehension of environmental impacts, emphasizing insights from China and Europe as key examples.