Search Results (168)

This study examines the adverse environmental impacts of solar photovoltaic parks located in established protected areas, aiming to determine the level of landscape fragmentation through the calculation of relevant landscape metrics. For this purpose, a case study was carried out in a Mediterranean Natura 2000 Special Protection Area (SPA), and landscape metrics were calculated using Geographic Information System spatial analysis tools. The analysis of metrics showed that the installation of renewable energy parks within the designated protected area negatively affect landscape fragmentation and the absence of carefully defined and evidence-based mitigation measures. The land cover categories that are significantly affected are those considered critical habitats of bird species that have been designated as SPAs. The results of this study highlight the need to integrate, in the National Renewable Energy Spatial Plans, specific biodiversity objectives, such as conservation objectives and the suspension of the installation of photovoltaic parks in certain areas that are important for conservation of biodiversity, in order to ensure the overall sustainability of renewable energy production. Full article

Mobile Charging Robots (MCRs), essentially high-voltage batteries mounted on mobile platforms, offer a flexible solution for electric vehicle (EV) charging, particularly in environments like supermarket parking lots with photovoltaic (PV) generation. Unlike fixed charging stations, MCRs must be strategically dispatched and recharged to maximize operational efficiency and revenue. This study investigates a Model Predictive Control (MPC) approach using Mixed-Integer Linear Programming (MILP) to coordinate MCR charging and movement, accounting for the additional complexity that EVs can park at arbitrary locations. The performance impact of EV arrival and demand forecasts is evaluated, comparing perfect foresight with data-driven predictions using long short-term memory (LSTM) networks. A slack variable method is also introduced to ensure timely recharging of the MCRs. Results show that incorporating forecasts significantly improves performance compared to no prediction, with perfect forecasts outperforming LSTM-based ones due to better-timed recharging decisions. The study highlights that inaccurate forecasts—especially in the evening—can lead to suboptimal MCR utilization and reduced profitability. These findings demonstrate that combining MPC with predictive models enhances MCR-based EV charging strategies and underlines the importance of accurate forecasting for future smart charging systems. Full article

This paper presents a multi-criteria decision-making (MCDM) approach for optimizing a microgrid system to achieve Plus-Energy Building (PEB) performance at the University of Coimbra’s Electrical Engineering Department. Using Python 3.12.8, Rhino 7, and PVsyst 8.0.1, simulations considered architectural and visual constraints, with economic feasibility assessed through a TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) analysis. The system is projected to generate approximately 1 GWh annually, with a 98% probability of exceeding 1076 MWh based on Gaussian estimation. Consumption is estimated at 460 MWh, while a 3.8 MWh battery ensures up to 72 h of autonomy. Rooftop panels and green parking arrays, fixed at 13.5° and 59°, minimize visual impact while contributing a surplus of +160% energy injection (or a net surplus of +60% energy after self-consumption). Assuming a battery cost of EUR 200/kWh, each hour of energy storage for the building requires 61 kWh of extra capacity with a cost of 12,200 (EUR/hr.storage). Recognizing environmental variability, these figures represent cross-validated probabilistic estimates derived from both PVsyst and Monte Carlo simulation using Python, reinforcing confidence in system feasibility. A holistic photovoltaic optimization strategy balances technical, economic, and architectural factors, demonstrating the potential of PEBs as a sustainable energy solution for academic institutions. Full article

Responding to the challenges of global climate change and domestic air pollution, Taiwan revised its energy policy in recent years, introducing an energy transition strategy focused on low-carbon and clean energy. However, if photovoltaic installations are not properly sited, they may have negative impacts on the local environment. Previous research on renewable energy has primarily focused on policy evaluation, with limited attention given to case studies that examine the suitability of site selection for PV system installations. Thus, this study incorporates the Fuzzy Delphi Method (FDM) and the Analytic Hierarchy Process (AHP) to explore the criteria for evaluating site suitability for ground-mounted PV systems. This study considers existing sites with completed ground-mounted PV systems in Tainan City as case study subjects. The results indicate that the most important factor, as prioritized by experts, is the distance from Class I environmentally sensitive areas, followed by the duration of insolation, proximity to the electrical grid, and distance from residential areas. The evaluation model developed in this study provides a valuable reference for future site selection of ground-mounted PV systems. Establishing dedicated PV energy parks also may offer a viable solution to mitigate disputes related to the deployment of ground-mounted PV systems. Full article

The increased uptake of Electric Vehicles (EVs) requires the installation of charging stations in parking lots, both to facilitate charging while running daily errands and to support EV owners with no access to home charging. Photovoltaic (PV) generation is ideal for powering up EVs, both for environmental reasons and for the benefit it creates for Charging Point Operators (CPOs). In this paper, we propose a centralised V1G Smart Charging (SC) algorithm for EV parking lots, considering real EV charging dynamics, which minimises both the EV charging costs for their owners and the CPO electricity provision costs or the related CO₂ emissions. We also introduce an innovative SC benefit-splitting algorithm that makes sure SC savings are fairly split between EV owners. Eight scenarios are described, considering costs or emissions minimisation, with and without a PV system. The centralised algorithm is benchmarked against a decentralised one, and tested in an exemplary workplace parking lot in Denmark, that includes includes 12 charging stations and one PV system, owned by the same entity. Reductions of up to 11% in EV charging costs, 67% in electricity provision costs for the CPO, and 8% in CO₂ emissions are achieved by making smart use of a 35 kWp rooftop PV system. Additionally, the SC benefit-splitting algorithm successfully ensures that EV owners save money when adopting SC. Full article

With the acceleration of global climate warming and agricultural modernization, the energy and carbon emission issues of agricultural parks (APs) have drawn increasing attention. An AP equipped with biogas-based combined heat and power (CHP) generation and photovoltaic systems serves as a prosumer terminal in a distribution network (DN). This paper introduces carbon emission flow (CEF) theory into the coordinated dispatch of APs and DNs. First, a CEF model for APs is established. Then, based on this model, a carbon–energy coordinated dispatch is carried out under bidirectional CEF interaction between the park and DN. A bidirectional carbon tax mechanism is adopted to explore the low-carbon synergy potential between them. Finally, the Stackelberg game approach is employed to address the pricing of electricity purchase/sale and carbon taxes in a DN, and the particle swarm optimization algorithm is used for rapid generating solutions. The case study shows that the proposed CEF model can effectively determine CEF distribution in the park. Moreover, the proposed bidirectional carbon tax mechanism significantly enhances the low-carbon economic benefits of both the AP and the DN. Full article

The growing integration of renewable energy and electric vehicle loads in parks has intensified the intermittency of photovoltaic (PV) output and demand-side uncertainty, complicating energy storage system design and operation. Meanwhile, under carbon neutrality goals, the energy system must balance economic efficiency with emission reductions, raising the bar for storage planning. To address these challenges, this study proposes a two-stage robust optimization method for shared energy storage configuration in a park-level integrated PV–storage–charging system (PV-SESS-CS). The method considers the uncertainties of PV and electric vehicle (EV) loads and incorporates carbon emission reduction benefits. First, a configuration model for shared energy storage that accounts for carbon emission reduction is established. Then, a two-stage robust optimization model is developed to characterize the uncertainties of PV output and EV charging demand. Typical PV output scenarios are generated using Latin Hypercube Sampling, and representative PV profiles are extracted via K-means clustering. For EV charging loads, uncertainty scenarios are generated using Monte Carlo Sampling. Finally, simulations are conducted based on real-world industrial park data. The results demonstrate that the proposed method can effectively mitigate the negative impact of source-load fluctuations, significantly reduce operating costs, and enhance carbon emission reductions. This study provides strong methodological support for optimal energy storage planning and low-carbon operation in park-level PV-SESS-CS. Full article

The energy transition of the road transport sector is now a strategic priority for achieving global decarbonization targets. In particular, the highway sector offers the opportunity to integrate sustainable solutions without additional land consumption, thanks to the availability of relevant areas that are already covered by infrastructure. This study proposes a large-scale analysis of the potential photoelectric energy that can be produced within highway infrastructures, with the aim of evaluating the contribution that these assets can make to electric mobility. The analysis was conducted using geographic information systems (GISs), applied to the case study of the A3 Napoli–Pompei–Salerno highway. The processing of topographical, orographic, and solar data has made it possible to identify a total surface area of approximately 27,100 m² that is potentially suitable for the installation of photovoltaic systems, distributed among service areas, toll stations, car parks, and side sections. This result highlights the concrete possibility of making the most of the energy potential of highway infrastructure, promoting self-production and local consumption models to power the electric vehicle charging network, thus contributing directly to the reduction of emissions and the sustainability of the transport system. Full article

The large-scale integration of renewable energy and the use of high-energy-consuming equipment in agricultural parks have a great influence on the security of rural distribution networks. To ensure reliable power delivery for residential and agricultural activities and sustainable management of distributed energy resources, this paper develops a distributed generation-supported interactive optimization framework coordinating distribution networks and agricultural parks. Specifically, a wind–photovoltaic scenario generation method based on Copula functions is first proposed to characterize the uncertainties of renewable generation. Based on the generated scenario, a bi-level interactive optimization framework consisting of a distribution network and agricultural park is constructed. At the upper level, the distribution network operators ensure the security of the distribution network by reconfiguration, coordinated distributed resource dispatch, and dynamic price compensation mechanisms to guide the agricultural park’s electricity consumption strategy. At the lower level, the agricultural park users maximize their economic benefits by adjusting controllable loads in response to price compensation incentives. Additionally, an improved particle swarm optimization combined with a Gurobi solver is proposed to obtain equilibrium by iterative solving. The simulation analysis demonstrates that the proposed method can reduce the operation costs of the distribution network and improve the satisfaction of users in agricultural parks. Full article

The transition from fossil fuels to renewable energy is fundamental to the mitigation of global climate change. Renewable power capacity is increasing globally, and solar photovoltaics will be the dominant renewable energy source by 2050. Photovoltaic parks (PVPs) require great expanses of land, usually in drylands, creating impacts that can compromise the sustainability of surrounding ecosystems and PVPs. But both novel ecosystems in PVPs and the effect of PVPs on ecosystems are rarely studied. This paper reviews the current knowledge on the impact of PVPs on arid and semi-arid ecosystems and describes the structure and functioning of these novel ecosystems, including changes in microclimatic conditions, soil properties, vegetation and fauna, and shows how these factors hinder the full recovery of ecosystems in PVPs. Ensuring that we do not sacrifice biodiversity for clean energy production restoration is necessary; hence, we address the limitations and challenges of restoring ecosystems within PVPs and suggest the use of modern ecological restoration techniques and the incorporation of grazing into rational planning. More research is needed to fully understand the long-term impacts and interactions of PVPs with the environment, the evolution of novel ecosystems in PVPs and the restoration techniques needed to achieve the long-term sustainability of these infrastructures. Full article

Waste-to-energy (WTE) is considered the most promising method for municipal solid waste treatment. An integrated energy system (IES) with carbon capture systems (CCS) and power-to-gas (P2G) can reduce carbon emissions. The incorporation of a “green-carbon” offset mechanism further enhances renewable energy consumption. Therefore, this study constructs a WTE-IES hybrid system, which conducts multi-dimensional integration of IES-WTP, CCS-P2G, photovoltaic (PV), wind turbine (WT), multiple energy storage technologies, and the “green-carbon” offset mechanism. It breaks through the limitations of traditional single-technology optimization and achieves the coordinated improvement of energy, environmental, and economic triple benefits. First, waste incineration power generation is coupled into the IES. A mathematical model is then established for the waste incineration and CCS-P2G IES. The CO₂ produced by waste incineration is absorbed and reused. Finally, the “green-carbon” offset mechanism is introduced to convert tradable green certificates (TGCs) into carbon emission rights. This approach ensures energy demand satisfaction while minimizing carbon emissions. Economic incentives are also provided for the carbon capture and conversion processes. A case study of an industrial park is conducted for validation. The industrial park has achieved a reduction in carbon emissions of approximately 72.1% and a reduction in the total cost of approximately 33.5%. The results demonstrate that the proposed method significantly reduces carbon emissions. The energy utilization efficiency and system economic performance are also improved. This study provides theoretical and technical support for the low-carbon development of future IES. Full article

The higher integration of photovoltaic (PV) units is an inevitable component of smart city development. Thanks to smart meter devices that can record the exchange of power between the grid and customers, it is expected that homeowners and businesses will tend to install PV arrays on their rooftops and parking lots to benefit from selling power back to the grid. However, the overvoltage issue resulting from high PV penetration is a major challenge that necessitates the active power curtailment of PV units to ensure power grid stability. Fairness-oriented methods aim to minimize the active power of PV units as much as possible, adopting a fairer approach, and then address the PV owner’s satisfaction with fair profit and loss. Maintaining voltage within a limited standard range under very low load conditions while prioritizing PV inverters’ participation in reactive power contribution and attempting to ensure fairer curtailment of active power presents challenges to existing control design approaches. This paper presents twelve new volt–watt curve design methods to achieve these goals and address the challenges. The methods yield polynomial curves, piecewise linear curves, and single linear curves. A unique voltage sensitivity value for each PV inverter is used to determine the control region area and the slope of the curve at the starting point in certain instances. The effectiveness of the proposed methods is discussed by evaluating their capabilities on the 37-bus IEEE system. Full article

In recent years, the energy policies of both Spain and the European Union have pursued the development of renewable energies, including solar power. One way these installations will appear in the Region of Murcia is on bodies of water, which do not alter existing land uses, but ground-mounted solar energy installations do bring about such changes. The Region of Murcia is located in the south-eastern quadrant of the Iberian Peninsula. Positioned on the leeward side of the westerly zonal circulation, characteristic of mid-latitudes, and influenced by the layout of the Betic mountain ranges that cross it from north-west to south-east, it experiences significant scarcity and irregularity of rainfall. In contrast, it benefits from an abundance of sunlight, with more than 3400 h of sunshine per year. This makes it one of the most productive locations for capturing solar energy and converting it into electricity. As a result, the land occupied by photovoltaic parks has increased at the expense of dry farming areas, irrigated land, and woodland. High energy prices have also led to self-consumption measures, with solar panels being installed on the roofs of industrial buildings, floating panels in irrigation reservoirs, photovoltaic solar farms associated with desalination and lift irrigation pumps, and pressure required by localized irrigation, etc. Full article

With the increasing liberalization of energy markets, the penetration of renewable clean energy sources, such as photovoltaics and wind power, has gradually increased, providing more sustainable energy solutions for energy-intensive industrial sectors or parks, such as iron and steel production. However, the issues of the intermittency and volatility of renewable energy have become increasingly evident in practical applications, and the economic performance and operational efficiency of localized microgrid systems also demand thorough consideration, posing significant challenges to the decision and management of power system operation. A smart microgrid can effectively enhance the flexibility, reliability, and resilience of the grid, through the frequent interaction of generation–grid–load. Therefore, this paper will provide a comprehensive summary of existing knowledge and a review of the research progress on the methodologies and strategies of modeling technologies for intelligent power systems integrating renewable energy in industrial production. Full article

Nature-based solutions (NBSs) offer a promising framework for addressing urban environmental challenges while also enhancing social and economic resilience. As cities seek to achieve carbon neutrality, the integration of NBSs with renewable energy sources (RESs) presents both an opportunity and a challenge, requiring an interdisciplinary approach and an innovative planning strategy. This study aims to explore potential ways of achieving synergies between NBSs and RESs to contribute to urban resilience and climate neutrality. Focusing on the railway station district in western Thessaloniki (Greece), this research is situated within the ReGenWest project, part of the EU Cities Mission. This study develops a comprehensive, well-structured framework for integrating NBSs and RESs, drawing on principles of urban planning and energy systems to address the area’s specific spatial and ecological characteristics. Using the diverse typologies of open spaces in the district as a foundation, this research analyzes the potential for combining NBSs with RESs, such as green roofs with photovoltaic panels, solar-powered lighting, and solar parking shaders, while assessing the resulting impacts on ecosystem services. The findings reveal consistent benefits for cultural and regulatory services across all interventions, with provisioning and supporting services varying according to the specific solution applied. In addition, this study identifies larger-scale opportunities for integration, including the incorporation of NBSs and RESs into green and blue corridors and metropolitan mobility infrastructures and the development of virtual power plants to enable smart, decentralized energy management. A critical component of the proposed strategy is the implementation of an environmental monitoring system that combines hardware installation, real-time data collection and visualization, and citizen participation. Aligning NBS–RES integration with Positive Energy Districts is another aspect that is stressed in this paper, as achieving carbon neutrality demands broader systemic transformations. This approach supports iterative, adaptive planning processes that enhance the efficiency and responsiveness of NBS–RES integration in urban regeneration efforts. Full article