• Energy Research
• 2021-2025close
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The use of superconducting magnetic energy storage (SMES) has been widely reported in the literature to mitigate various load frequency control (LFC) issues in a multi-area power system. Most of these are thyristor based SMES, employing proportional type controllers. In this paper, a supervisory adaptive model predictive control scheme (AMPC) is proposed for a voltage source converter based relatively small rating SMES for LFC application. The reference power command for the SMES is derived from the AMPC in such a manner that it effectively handles the operational constraints of the SMES system. A representative first-order system emulating the inner loop dynamics of the SMES chopper system, is tuned offline via genetic algorithm (GA) and is used to derive dynamic constraints for the cost function in AMPC. The effectiveness of the scheme is demonstrated through simulations.

Since long ago, pelagic Sargassum mats have been known to be abundant in the Sargasso Sea, where they provide habitat to diverse organisms. However, over the last few years, massive amounts of pelagic Sargassum have reached the coast of several countries in the Caribbean and West Africa, causing economic and environmental problems. Aiming for lessening the impacts of the blooms, governments and private companies remove the seaweeds from the shore, but this process results expensive. The valorization of this abundant biomass can render Sargassum tides into an economic opportunity and concurrently solve their associated environmental problems. Despite the diverse fields where algae have found applications and the relevance of this recurrent situation, Sargassum biomass remains without large scale applications. Therefore, this review aims to present the potential uses of these algae, identifying the limitations that must be assessed to effectively valorize this bioresource. Due to the constraints identified for each of the presented applications, it is concluded that a biorefinery approach should be developed to effectively valorize this abundant biomass. However, there is an urgent need for investigations focusing on holopelagic Sargassum to be able to truly valorize this seaweed.

The global restoration agenda can help solve the biodiversity extinction crisis by regenerating biodiversity-rich ecosystems, maximising conservation benefits using natural regeneration. Yet, conservation is rarely the core objective of restoration, and biodiversity is often neglected in restoration projects targeted towards carbon sequestration or enhancing ecosystem services for improved local livelihoods. Here, we synthesise evidence to show that promoting biodiversity in restoration planning and delivery is integral to delivering other long-term restoration aims, such as carbon sequestration, timber production, enhanced local farm yields, reduced soil erosion, recovered hydrological services and improved human health. For each of these restoration goals, biodiversity must be a keystone objective to the entire process. Biodiversity integration requires improved evidence and action, delivered via a socio-ecological process operating at landscape scales and backed by supportive regulations and finance. Conceiving restoration and biodiversity conservation as synergistic, mutually reinforcing partners is critical for humanity's bids to tackle the global crises of climate change, land degradation and biodiversity extinction.

Interfacial resistance at electrode‐high Li+ conductive solid electrolytes must be reduced well to develop high‐power all‐solid‐state batteries using oxide‐based solid electrolytes (Ox‐SSBs). Herein, crystalline electrode films of LiCoO2 (LCO) are formed on a high Li+ conductive crystalline‐glass solid electrolyte sheet, Li1.3Al0.3Ti2(PO4)3 (LATP) (σ25 °C = 1 × 10−4 S cm−1), at room temperature by aerosol deposition (AD), and the effects of the annealing temperature on the interfacial resistivities (Rint) at the LCO/LATP are investigated. The Rint visibly increases by annealing over 500 °C with the growth of Co3O4 as a reactant. In contrast, Rint is reduced to ≈100 Ω cm2 by low‐temperature annealing at 250–350 °C due to superior contact through the structural rearrangement of an artificial metastable interface formed by the AD. These results are applied to bulk‐type Ox‐SSB, Li/Li7La3Zr2O12(LLZ)/LCO–LATP, and our best Ox‐SSB delivers a discharge capacity of 100 mA cm−2 at 100 °C.

Interest in the highly efficient energy hub (EH) model has been growing despite the high computational requirements of planning for a multi-energy, multi-device operation. To address both the device size limitation and the multi-scenario issue, we propose a new solution methodology for solving the EH planning problem. In the method, the decision variables are device sizes. First, a dimension reduction technique is proposed to address the curse of dimensionality based on the correlation of unknown variables such as the capacities of different devices in an EH. Second, to avoid local convergence, a solution method called the variable-sized unimodal searching (VUS) approach is proposed to assure a global optimal planning scheme for the one-dimensional non-convex optimization model obtained from the preceding dimension reduction process. The case study indicates that the proposed approach has a higher computing efficiency than the Benders decomposition (BD) algorithm to deal with a scenario-based stochastic planning problem with a large number of scenarios. Thus, the effectiveness of the EH planning approach is verified.

In this work, two heuristic techniques used to reduce the number of simulations of lightning-induced voltages, which are required to assess the lightning performance of distribution lines according to the Monte Carlo methodology, are presented. The first uses the Rusck Formula to discard the events that do not cause damage to the line. The second is based on a multi-nonlinear regression of the previously simulated events. Both techniques were applied to estimate the flashover rate of straight and complex lines above flat ground with finite conductivities. As a result, between 80 \% to 90 \% of the total number of simulations were eliminated with a reduced error.