Abstract

The transient response of proton exchange membrane fuel cell (PEMFC) during start-up is an important issue for a system. In this paper, the start-up process of the 6-cell stack with the dead-end anode and recirculation cathode is studied. The effects of starting load, step size on voltage variation are studied via the measurement of time evolution of the stack voltage. In addition, the different start-up responses of the single-cell under the flow-through and recirculation are compared. It is found that increasing the start-up current density and reducing the step load change can shorten the start-up time. However, the shorter start-up time will result in the lower critical membrane dehydration temperature. Compared with the gas-through mode, when the stack with dead-end anode and cathode recirculation is started, the single cell near the outlet is more likely to be flooded at the moment of high current density start-up due to the closing of anode outlet.

Abstract

The various power market challenges of the conventional power system are projected to be addressed by a smart grid. It entails a synergy between the three pillars of electricity trading, 1) energy market economics, 2) power network balancing, and 3). market policies and regulations. This paper explores an overview of peer-to-peer (P2P) trading under a smart grid milieu from these three pillars’ perspectives. The first pillar delineates the energy user’s role flipping between the consumer and prosumer due to behind-the-meter distributed energy resources integration to maximize their payoffs. At the power network, P2P trading necessitates a). robust and sophisticated network infrastructure, and b). bi-directional Internet and communication technologies for successful electricity trading in the distributed electricity market. This is defined as physical and virtual levels of P2P architecture under the second pillar of P2P. Lastly, the third pillar is essential for adequately constructing an optimal business strategy to maximize the player’s profit function.

Abstract

CO2 huff and puff is an important means to achieve efficient development of tight reservoirs. The authors carried out CO2 huff and puff simulation experiments by using one-dimensional long core to simulate the whole process of CO2 huff and puff development in tight reservoirs. The main mechanism and the effect of well stuffing time and production pressure difference on the development effect of CO2 huff and puff in tight reservoir are expounded.The simulation results show that compared with the flow sweep caused by pressure difference, the contribution of molecular diffusion sweep to CO2huff and puff recovery is higher.

Abstract

Intermittent electricity generation from variable renewable energies will lead to an increased demand for flexibility options in the future. Power-to-heat-to-power storage technologies present high potentials for large-scale application. However, investments in such technologies are still hampered by technical and economic challenges. To address the latter the possible revenues in electricity markets need to be analyzed. For this, we simulate the German electricity market in ambitious defossilization scenarios. We use different operational strategies for the storage (minimizing system costs versus maximizing storage profits) that show a wide range of storage profitability. The operator benefits from its attributed market power (i.e. assuming perfect foresight in a rolling horizon window) to generate positive net profits. Further research may focus on market situations with increased market competition.

Abstract

This study proposed a new thin cambered bent biomimetic wind turbine design that adopted the 3D geometry of the wing of a Borneo camphor seed sample. The wings of the Borneo camphor seed are thin, cambered, and bent. The unique geometry and orientation of the wings cause the seed to autorotate during propagation, subsequently slowing down its falling speed. It was presumed that by mimicking the wings of a Borneo camphor seed, a high-performance biomimetic wind turbine design could be proposed since the wind turbine, and Borneo camphor seed shares a similar rotating mechanism. Computational fluid dynamics was adopted to predict the power coefficient, thrust coefficient, and torque of the proposed biomimetic wind turbine models. The results show that the highest power coefficient was 0.3861 for the biomimetic wind turbine model, which is 20.14% higher than that of a benchmark case when the fold axis and fold angles are equal to 30° and 30°, respectively. The findings of this study concluded that the proposed biomimetic wind turbine design is cost-effective and worthy of further investigation.

Abstract

Detailed energy consumption data is key to data-driven urban energy modeling efforts. However, privacy considerations often prevent such data to be shared directly with researchers. Here, we present an approach based on the “15/15 rule,” used in several states in the United States, to enable energy data to be shared while protecting the information of individual customers. We do so based on a case study typical for urban energy data, where public information is combined with privacy-sensitive data. We compare two implementations, showing that our custom algorithm achieves a 1,000 times higher computational speed at only a 10% increase in information loss compared to a previously published clustering method. Our work aims to provide a mechanism to accelerate broader energy data sharing and serve as a baseline for similar efforts in different regulatory contexts, including potential future policy frameworks based on differential privacy.

Abstract

This work presents a two-stage stochastic Mixed Integer Linear Programming model for the optimization of the design of an aggregated energy system (AES) (i.e., multi-energy systems, microgrids, energy districts, etc.) serving a university campus featuring electricity and heating demands. The off-grid system design is obtained by considering a set of representative periods for both demands by means of a carefully modified k-medoids algorithm. N-1 reliability is also considered in the model, by introducing the concept of “break-down scenarios” that allows the solution of the problem to be able to meet the user demands for every possible contingency in which one of the AES’s units fails. The effect of including N-1 reliability in the model is then showed by comparing the optimal design obtained by considering such approach against one with no break-down scenarios.

Abstract

Decarbonizing the electricity sector is not an easy task. To reach the decarbonization of the electricity sector in Latvia by 2050, there are a lot of barriers that need to be addressed. To reduce or completely remove different social, technical, economic, administrative, and other barriers, a set of policies needs to be defined. Research results show that there is a combination of policy instruments that would allow for complete decarbonization of the electricity sector, however, it is crucial to implement the whole set of policies, not just one or two of them, and implement them as soon as possible to gain the maximum effect.

Abstract

Flexible devices with remote monitoring and control availabilities, integrated behind-the-meter or last mile of electricity (grid edge) have significantly become widespread in the past decade. There are emerging distributed energy resource (DER) management solutions that give DER more active roles in power system and energy market operation. DER coordination incorporates inherent uncertainties related to distributed generation from intermittent renewables, non-flexible loads and dynamic prices. Consideration of uncertainties in optimum energy scheduling in community microgrids with a large number of electric vehicles can provide considerable benefits. This study presents a cloud-based optimal energy scheduling approach that considers diverse uncertainties in EV charging coordination as part of community microgrid energy scheduling. A case study is conducted for a representative community microgrid to investigate the benefits and challenges in uncertainty considered optimal energy scheduling.

Abstract

The solar power tower (SPT) is regarded as the most promising technology used for the next-generation concentrated solar-thermal power (CSP) plant. However, the degraded solar-thermal conversion performance of the solar tower receiver in the SPT system significantly reduces its power generation efficiency and capacity. In the previous study carried out by the authors, an unperceived negative thermal-flux phenomenon was discovered in the tower receiver, which is one of the main reasons for the degradation of the tower receiver’s thermal performance. Aiming to eliminate the negative thermal-flux phenomenon, this study proposes a novel optimization method by depositing the unique solar selective-absorbing coatings on the negative thermal-flux regions to improve the solar-thermal conversion performance of these regions. Four kinds of solar selective-absorbing coatings (SSCs) with different spectral selectivities, namely, silver coating, black chrome coating, and ideal coatings with cutoff wavelengths of 2.5 μm and 1.5 μm, are employed to investigate the effects on the heat transfer characteristics of the negative thermal-flux region and overall thermal performance of the tower receiver. Besides, the economic metrics of the above four kinds of novel tower receivers with different solar selective coatings are also evaluated in this study. The results show that the optimization method by SSC substitution at negative thermal-flux regions exerts an excellent role in eliminating the adverse effects of the negative thermal-flux region. The efficiency of the novel tower receiver with an ideal coating could be significantly improved by 12.03 %. In addition, the annual power output of an SPT plant with the novel receiver is effectively improved by 5.0 %, and the levelized cost of energy is reduced by 4.9 %.