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Abstract An improved hybrid vacuum and pressure-assisted infiltration technique was developed for the infiltration of phase change materials (PCM) into the graphite foam matrix. A single chamber with no moving part infiltration setup was designed and fabricated. Pelletized PCM was introduced to provide enough porosity for air removal using vacuum pumps with no need for transfer PCM after melting and infiltration. Simple design, the use of stainless steel, and the corrosion resistance feature of PCM provides a very cost-effective design and easily controllable process. Mixed alkali and alkaline chloride salts as PCM were infiltrated into the high porosity graphite foam to enhance the thermal conductivity of latent heat storage medium. Chloride based PCM with proven corrosion-resistant features, high energy storage density that enables storage and release of energy at nearly constant temperatures close to the melting temperature of 355 °C are used in this study, as an example. The composites of infiltrated graphite foam and chloride salt PCMs were studied using SEM, EDS microstructural analyses to determine the effectiveness of the infiltration process. An infiltration efficiency greater than 90% of the available porosity was achieved. The thermal conductivity of the infiltrated samples was analyzed using a laser Nano-flash thermal conductivity device. The thermal conductivity of the foam/PCM composite was shown to be larger by a factor greater than 40 times of pure chloride PCM (1–2 W/m-K). Low-cost infiltration with proven efficacy and repeatability of infiltrated PCM could be a breakthrough for 3rd generation of CSP plant applications with supercritical CO2 power cycles.

Abstract The smart grid is expected to self-heal, self-optimize, self-configure, and self-protect from physical and cyber-disturbances. These requirements are expected to be built into intelligent electronic devices (IEDs), which would enable autonomous control of power distribution buses in the smart grid. Power distribution buses are used to redistribute electric loads across power generation sources, control voltage/VAR, satisfy economic dispatch objectives and improve the resiliency of the grid against physical disturbance and cyber-attacks. The current power grid has a centralized communication system with a centralized human-in-the-loop controller (such as in a typical SCADA system) in order to adjust operating configurations of equipment within a distribution zone. Implementing autonomous functions by moving from a centralized control architecture to a decentralized architecture can empower bus controllers with greater control over local equipment and operations. We present the secure overlay communication model (SOCOM) for smart microgrids as a solution to decentralizing the traditional centralized control architecture and a decentralized communication platform for peer bus controllers to operate and optimize operations of the grid. We demonstrate the utility of this overlay model in an 11-Bus microgrid network to achieve self-healing. Using this model, we were able to accurately detect data modification attacks that target the controller’s state-estimation and malicious control of switching devices.

Conventional wisdom suggests that energy efficiency (EE) policies are beneficial because they induce investments that pay for themselves and lead to emissions reductions. However, this belief is primarily based on projections from engineering models. This paper reports on the results of an experimental evaluation of the nation’s largest residential EE program conducted on a sample of more than 30,000 households. The findings suggest that the upfront investment costs are about twice the actual energy savings. Further, the model-projected savings are roughly 2.5 times the actual savings. While this might be attributed to the “rebound” effect – when demand for energy end uses increases as a result of greater efficiency – the paper fails to find evidence of significantly higher indoor temperatures at weatherized homes. Even when accounting for the broader societal benefits of energy efficiency investments, the costs still substantially outweigh the benefits; the average rate of return is approximately -9.5% annually.

Nuclear power plants in the United States are increasingly challenged to compete in wholesale electricity markets due to the low electricity costs and increasingly dynamic grid conditions from competing generation sources. An alternative market for nuclear power is industrial facilities that can use the thermal and/or electrical power generated by a nuclear power plant to offset the economic losses incurred by electricity market challenges. A generic pressurized water reactor (PWR) simulator was used to show the results of a basic design for a generic thermal power extraction system and tests were run using a set of procedures to show what happens when a nuclear power plant transitions from full electrical power dispatch to 15% and 50% thermal power dispatch. This type of operation leads to losses in turbine performance efficiency due to the deviation from the design operating point, but because the thermal power is also used by the industry load without conversion losses, the combined thermal efficiency of the PWR increases. For the 15% case, the thermal efficiency increased from 32% to 41.9%, while for the 50% case, the efficiency increased up to 60.1%. In addition, for 50% thermal power dispatch, the power dissipated by the condenser decreased from approximately 2000 to approximately 1300 MW (thermal), indicating a substantially diminished impact on the environment in terms of releasing heat into the cooling water reservoir.

Abstract The residual biomass of Cupriavidus necator , a biopolyester-producing bacterium, was liquefied in subcritical water at 300 °C. The hydrophobic organic compounds, accounting for about 45% carbon of the original biomass, were recovered with methylene dichloride for analysis. The organic compounds included hydrocarbons such as long chain alkane and benzene, and nitrogen-containing heterocycles such as pyrroles and indoles. The liquid had the similar elemental composition (C, H, O, N) and high heating value (34 MJ kg −1 HHV) of the bio-oils derived from microalgae biomass.

In order to reliably simulate the energy yield of photovoltaic (PV) systems, it is necessary to have an accurate model of how the PV modules perform with respect to irradiance and cell temperature. Building on previous work that addresses the irradiance dependence, two approaches to fit the temperature dependence of module power in PVsyst have been developed and are applied here to recent multi-irradiance and -temperature data for a standard Yingli Solar PV module type. The results demonstrate that it is possible to match the measured irradiance and temperature dependence of PV modules in PVsyst. As a result, improvements in energy yield prediction using the optimized models relative to the PVsyst standard model are considered significant for decisions about project financing.

The majority of local respondents in a large-scale survey were in favour of planned local wind farms on the Danish coast, despite these wind farm plans being the source of wider public and political contestation and opposition. Here we discuss results from the open-ended questions in the survey, specifically focusing on comments expressing how some respondents felt split in their views of these wind farms, accepting the need for renewable energy while at the same time being concerned about the potential local impact of the wind farms. Building on previous theoretical propositions relating to energy infrastructure opposition, here we apply the concept of cognitive polyphasia in some depth, providing a socio-cognitive account of the internal contradiction of being positively disposed to renewable energy in principle, but concerned about or opposed to specific de­velopments in localities. We distinguish a cognitive polyphasic account of such mixed feelings from cognitive dissonance accounts, and we identify several types of polyphasic representations, providing a basis for further work in other cases. The majority of local respondents in a large-scale survey were in favour of planned local wind farms on theDanish coast, despite these wind farm plans being the source of wider public and political contestation andopposition. Here we discuss results from the open-ended questions in the survey, specifically focusing oncommentsexpressinghowsomerespondentsfeltsplitintheirviewsofthesewindfarms,acceptingtheneedforrenewableenergywhileatthesametimebeingconcernedaboutthepotentiallocalimpactofthewindfarms.Building on previous theoretical propositions relating to energy infrastructure opposition, here we apply theconceptofcognitivepolyphasiainsomedepth,providingasocio-cognitiveaccountoftheinternalcontradictionof being positively disposed to renewable energy in principle, but concerned about or opposed to specific de-velopments in localities. We distinguish a cognitive polyphasic account of such mixed feelings from cognitivedissonanceaccounts,andweidentify severaltypesofpolyphasicrepresentations,providingabasisforfurtherworkinothercases

AbstractRecently, modern power systems depend heavily on MicroGrids (MGs), which can accommodate Distributed Energy Resources (DERs) economically and with high flexibility. MGs integrated with DERs can assist in enhancing energy security, significant cost savings, and reduction in emission of greenhouse gases. In this paper, the assessment of operating performance of proposed MG system with DERs is employed to investigate the multi‐objective problems of cost optimization and economic scheduling. A grid‐connected Micro‐grid (MG) combined with solar photovoltaic (PV), wind turbine (WT), fuel cell (FC), and Battery Energy Storage System (BESS) is implemented to model the problem. This proposed model is considered as a test system for cost optimization and battery charging/discharging optimization. The developed framework is presented as multi‐objective function with constraints that can be tackled using an effective optimization technique. The above stochastic multi‐objective problem is optimized using various commonly used Physics based Meta‐heuristic techniques such as Simulated Annealing (SA), Harmony Search (HS), Slime Mold Algorithm (SMA), Gravitational Search Algorithm (GSA), Black Hole Optimization (BHO), Sine Cosine Algorithm (SCA), Multiverse optimization (MVO) and Lightning Search Algorithm (LSA). The assessment of the aforementioned physics‐based optimization techniques used on the proposed MG test system is compared using the results. According to the analysis, Black Hole Optimization (BHO) and Lightning Search Algorithm (LSA) both provide greater cost savings overall and for battery charging, respectively. The suggested optimization methods will take the BESS charging/discharging pattern and total cost savings into account.