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Editorial Complex Optimization and Simulation in Power Systems

The Intergovernmental Panel on Climate Change (IPCC) report that to limit warming to 1.5 °C, Bioenergy with Carbon Capture and Storage (BECCS) is required. Integrated assessment models (IAMS) predict that a land area between the size of Argentina and Australia is required for bioenergy crops, a 3–7 time increase in the current bioenergy planting area globally. The authors pose the question of whether vertical farming (VF) technology can enable BECCS deployment, either via land sparing or supply. VF involves indoor controlled environment cultivation, and can increase productivity per unit land area by 5–10 times. VF is predominantly being used to grow small, high value leafy greens with rapid growth cycles. Capital expenditure, operational expenditure, and sustainability are challenges in current VF industries, and will affect the ability to utilise this technology for other crops. The authors argue that, whilst challenging, VF could help reach wider climate goals. Application of VF for bioenergy crops could be a game changer in delivering BECCS technologies and may reduce the land footprint required as well as the subsequent associated negative environmental impacts. VF bioenergy could allow us to cultivate the future demand for bioenergy for BECCS on the same, or less, land area than is currently used globally.

The path congestion and communication risks of electric power communication network have emerged as the carried businesses are becoming more and more heavy. In this paper, a multi-objective optimization method for power communication network routing considering the importance of the carried businesses is proposed to reduce load imbalance and transmission risk. Firstly, information entropy is introduced as the objective of communication network load balancing optimization. And a risk assessment model for power communication network nodes and links is established. Then fuzzy membership functions are adopted to singularize the two objectives to jointly optimize path congestion and communication risks. The device nodes are dynamically divided according to the carried businesses to pursue the global optimization of the power communication network in which the Yen's algorithm is adopted. Finally, this paper uses the IEEE 30-bus communication network to carry out case simulations and analyzes the proposed method to verify the effectiveness and feasibility.

In this paper, we study the interactions among interconnected autonomous microgrids, and propose a joint energy trading and scheduling strategy. Each interconnected microgrid not only schedules its local power supply and demand, but also trades energy with other microgrids in a distribution network. Specifically, microgrids with excessive renewable generations can trade with other microgrids in deficit of power supplies for mutual benefits. Since interconnected microgrids operate autonomously, they aim to optimize their own performance and expect to gain benefits through energy trading. We design an incentive mechanism using Nash bargaining theory to encourage proactive energy trading and fair benefit sharing. We solve the bargaining problem by decomposing it into two sequential problems on social cost minimization and trading benefit sharing, respectively. For practical implementation, we propose a decentralized solution method with minimum information exchange overhead. Numerical studies based on realistic data demonstrate that the total cost of the interconnected-microgrids operation can be reduced by up to 13.2% through energy trading, and an individual participating microgrid can achieve up to 29.4% reduction in its cost through energy trading. To appear in IEEE Transactions on Smart Grid

Wind characteristics (e.g., mean wind speed, gust factor, turbulence intensity and integral scale, etc.) are quite scattered in different measurement conditions, especially during typhoon and/or hurricane processes, which results in the structural engineer ambiguously determining the wind parameters in wind-resistant design of buildings and structures in cyclone-prone regions. In tropical cyclones (including typhoons and hurricanes), the inconsistent wind characteristics may be in part ascribed to the complex flow structure with the coexistence of both mechanical and convective turbulence in the boundary layer of tropical cyclones. Another significant contribution to the scattered wind characteristics is due to various measurement conditions (e.g., terrain exposure and height) and data processing schemes (e.g., averaging time). The removal of the inconsistency in the field-measurement system may offer a more rational comparison of measured wind data from various observation platforms, and hence facilitates a better identification scheme of the wind characteristics to guide the urban planning design and wind-resistant design of buildings and structures. In this study, an analytical framework was firstly proposed to eliminate the potential observation-related effects in wind characteristics and then the wind characteristics of seven field measured tropical cyclones (four typhoons and three hurricanes) were comparatively investigated. Specifically, field measurements of wind characteristics were converted to a standard reference station with a roughness length of 0.03 m, observation duration of 10 min for mean wind and averaging time of 3 s for gusty wind at a 10 m height. The differences of the measured wind characteristics between the typhoons and hurricanes were highlighted. The standardized turbulent wind characteristics under the analytical framework for typhoons and hurricanes were compared with the corresponding recommendations in standard of American Society of Civil Engineers (ASCE 7-10) and Architectural Institute of Japan Recommendations for Loads on Buildings (AIJ-RLB-2004).

Upwelling processes bring nutrient-rich waters from the deep ocean to the surface. Areas of upwelling are often associated with high productivity, offering great economic value in terms of fisheries. The sensitivity of spring/summer-time coastal upwelling systems to climate change has recently received a lot of attention. Several studies have suggested that their intensity may increase in the future while other authors have shown decreasing intensity in their equatorward portions. Yet, recent observations do not show robust evidence of this intensification. The Senegalo-Mauritanian upwelling system (SMUS) located at the southern edge of the north Atlantic system (12°N–20°N) and most active in winter/spring has been largely excluded from these studies. Here, the seasonal cycle of the SMUS and its response to climate change is investigated in the database of the Coupled Models Inter comparison Project Phase 5 (CMIP5). Upwelling magnitude and surface signature are characterized by several sea surface temperature and wind stress indices. We highlight the ability of the climate models to reproduce the system, as well as their biases. The simulations suggest that the intensity of the SMUS winter/spring upwelling will moderately decrease in the future, primarily because of a reduction of the wind forcing linked to a northward shift of Azores anticyclone and a more regional modulation of the low pressures found over Northwest Africa. The implications of such an upwelling reduction on the ecosystems and local communities exploiting them remains very uncertain.

This article describes an innovative method for measuring lighting levels and other lighting parameters through the use of aerial imagery of towns and cities. Combined with electricity consumption data from smart electricity meters, it was possible to measure the energy efficiency of public lighting installations. The results of this study also confirmed that lighting measurements, installation material, luminaire position, and electricity consumption data can be easily integrated into geographic information systems (GIS). The main advantage of this new methodology is that it provides information about lighting installations in large areas in less time than more conventional procedures. It is thus a more effective way of obtaining the data required to calculate the energy efficiency of lighting levels and electricity consumption. There is even the possibility of generating street lighting maps that provide local administrations with up-to-date information regarding the status of public lighting installations in their city. In this way, modifications or improvements can be made to achieve greater energy savings and, if necessary, to correct the distribution or configuration of public lighting systems to make them more efficient and sustainable. This research studied levels of street lighting and calculated the energy efficiency in various streets of Deifontes (Granada), through the use of aerial imagery.