We address entropic uncertainty relations between time and energy or, more precisely, between measurements of an observable G and the displacement r of the G-generated evolution e−irG. We derive ...lower bounds on the entropic uncertainty in two frequently considered scenarios, which can be illustrated as two different guessing games in which the role of the guessers are fixed or not. In particular, our bound for the first game improves the previous result by Coles et al Phys. Rev. Lett. 122 100401 (2019). To derive our bounds, we extend a recently proposed novel algebraic method by Gao et al arXiv:1710.10038 quant-ph which was used to derive both strong subadditivity and entropic uncertainty relations for measurements.
We derive the Mandelstam-Tamm time-energy uncertainty relation for neutrino oscillations in a generic stationary curved spacetime. In particular, by resorting to Stodolsky covariant formula of the ...quantum mechanical phase, we estimate gravity effects on the neutrino energy uncertainty. Deviations from the standard Minkowski result are explicitly evaluated in Schwarzschild, Lense-Thirring and Rindler (uniformly accelerated) geometries. Finally, we discuss how spacetime could affect the characteristic neutrino oscillation length in connection with the recent view of flavor neutrinos as unstable particles.
Combined the new metric Energy-Related Uncertainty Index (EUI) and novel Decomposed R2 Connectedness framework, with monthly dataset covers 19 G20 stock market returns from January 2004 to October ...2022, this paper examines the dynamic overall, contemporaneous and lagged spillover effect between energy market and G20 stock markets. This paper has the following important and interesting conclusions: Firstly, the spillover effect of EUI and G20 stock markets are contemporaneous dominated. All the contemporaneous From and To connectedness indicators are higher than lagged connectedness except for EUI. Secondly, the spillover effect shows heterogeneity. The stock of France, the United Kingdom, and the United States are net transmitter, while China, Saudi Arabia, and EUI are the net recipient. Finally, the EUI plays a unique and subtle role in the transmission dynamics of market shocks. The multifaceted impact of EUI on the individual stock markets of the G20 has exacerbated the complexity of this interaction. Specifically, the spillover effects between the EUI and G20 stock markets are significantly affected by economic events such as global crises and technological changes. Our research is poised to offer valuable insights to investors, policymakers, and researchers alike. By delving into the specificities of the G20 context, we aim to contribute nuanced perspectives that can inform decision-making processes amidst the complexities of energy-related uncertainties in the financial landscape.
•Contemporaneous spillover effects are more pronounced than lagged spillovers.•The distribution of shock transmission is asymmetrical.•EUI plays a unique role in market shock transmission dynamics.•EUI-G20 spillovers significantly influenced by global crises and technological changes.
Approximately half of the annual global energy supply is consumed in constructing, operating, and maintaining buildings. Because most of this energy comes from fossil fuels, it also contributes ...greatly to annual carbon emissions. When constructing a building, embodied energy is consumed through construction materials, building products, and construction processes along with any transportation, administration, and management involved. Operating energy is used in space conditioning, heating, lighting, and powering building appliances. In order to effectively reduce the carbon footprint of buildings, a comprehensive reduction in both embodied and operating energy is needed. Studies so far have focused on reducing either embodied or operating energy in isolation without realizing the trade-off that exists between them. Also, building energy research has concentrated more on operating energy than embodied energy, and as a result, the operating energy of buildings is gradually decreasing. Due to a variety of issues, however, few efforts have been undertaken to comprehensively minimize embodied energy.
Quantifying embodied energy is more tedious, complex, and resource-consuming than measuring operating energy. Furthermore, the reported values of embodied energy vary significantly within and across geographic regions owing to certain methodological and data quality parameters. The literature has repeatedly pointed out a need to standardize these parameters to bring consistency to embodied energy calculations. This paper presents a rigorous review of literature in order to investigate these parameters and their impact on embodied energy calculations. The reported values of initial and life-cycle embodied energy are also presented to highlight variations due to differing parameters. Finally, we suggest a two-step solution to make the process of embodied energy analysis more streamlined and transparent through a set of guidelines and an uncertainty calculation model.
A district integrated energy system characterized by multi-energy complementary and supply-demand interaction is a new idea to promote the resilience of urban energy systems. Compared with the ...post-disaster emergency response and rapid recovery, incorporating the impact of extreme events into the early-stage energy system planning is crucial to improve its resilience. While considering the uncertainty of renewable energy and demand response, this study proposes an optimal planning method which can deal with both economic performance and resilience of a district integrated energy system under extreme natural disasters. Firstly, by employing the k-means clustering algorithm and the extreme natural hazard modeling method, three typical days and five extreme natural disasters are deduced, respectively. Secondly, the critical load and non-critical load are decomposed according to the energy consumption characteristics of multiple end-users. Thirdly, taking the lowest overall energy cost of the system as the objective function and satisfaction of critical loads as the core constraint, a mathematical model for collaborative optimization of equipment configuration and operation strategy is developed. Finally, the evaluation index of the system resilience is proposed, and the marginal cost of resilience improvement is calculated. According to the simulation results of an illustrative example, the consideration of extreme natural disasters may increase the total system cost by 6.78% within the planning period. Moreover, The marginal cost of resilience improvement increases exponentially with the advancement of system resilience.
•The critical load and non-critical load are decomposed for different users.•Scenario-based modeling method for extreme natural disasters is proposed.•The optimal operating strategy considering the whole disaster cycle is discussed.•The trade-off between resilience and economics is examined.
•the distributionally robust optimization method is adopted for renewable uncertainty.•an alternating direction method of multipliers algorithm is used for privacy protection.•peer-to-peer ...transactive energy trading improves the profit of microgrids.•the network transmission cost will encourage the electricity transactions nearby.
Distributed renewable energy requires market-based measures to remain competitive as subsidies are phased out. However, the intermittence and volatility of renewable energy power generation lead to great challenges in decision-making. To address the uncertainty issues induced by inaccurate RE forecast, this paper proposed a peer-to-peer transactive energy trading strategy for multiple microgrids based on distributionally robust optimization. First, an uncertainty fuzzy set based on Wasserstein distance is created for the renewable energy prediction errors in each microgrid. Second, a day-ahead microgrids peer-to-peer transactive energy trading model is proposed based on the distributionally robust optimization theory to address the power fluctuation problems of renewable energy. Third, using the dual theory, the proposed nonlinear model is addressed by transforming it into a linear and convex programming problem. Considering the independence of microgrids, a distributed strategy based on the alternating direction method of multipliers is then developed to preserve their privacy. Finally, the case study proves that the method proposed can increase the income of microgrids containing renewable energy through peer-to-peer transactions, protect the privacy of microgrids, and then promote the development of renewable energy. The distributionally robust optimization approach also guarantees the economy and reliability of the transaction results for real-time deployment.
Many modern industries are equipped with onsite renewable generation and are normally connected to the grid. A battery energy storage system (BESS) can complement the intermittency of the available ...onsite renewable generation. The combination of the BESS and the renewable generation can operate as a microgrid. If the microgrid is properly sized and managed, it is possible to reduce the electricity bill to have a huge saving in the electricity cost. This article proposes an energy management system for such an industrial microgrids. The decisions to charge and discharge the BESS in the proposed energy management are usually constrained by the size of the energy storage. The proposed energy management strategy aims to optimize the operation of the industrial microgrids subject to the scalability of the BESS under uncertainties. The proposed optimization involves two stages. In the first stage of optimization, it determines the optimum size of the energy storage taking into account the cost of the BESS, and in the second stage, it minimizes the cost of the microgrid operation based on the decision made in the first stage. This proposed two-stage energy management strategy is formulated as a single-stage linear program that incorporates stochastic scenarios for addressing uncertainties. In addition, the proposed strategy also considers the various operating limits of the energy storage, such as the efficiency and the charging and the discharging rates, and considers the fading effect of the batteries of the BESS. The proposed strategy is then validated using two typical datasets from two different industrial units in New South Wales, Australia. The simulation results show that the proposed strategy effectively calculates the optimum size of the BESS and reduces the operational cost.
Times of arrival and gauge invariance Das, Siddhant; Nöth, Markus
Proceedings of the Royal Society. A, Mathematical, physical, and engineering sciences,
06/2021, Letnik:
477, Številka:
2250
Journal Article
Recenzirano
Odprti dostop
We revisit the arguments underlying two well-known arrival-time distributions in quantum mechanics, viz., the Aharonov–Bohm–Kijowski (ABK) distribution, applicable for freely moving particles, and ...the quantum flux (QF) distribution. An inconsistency in the original axiomatic derivation of Kijowski’s result is pointed out, along with an inescapable consequence of the ‘negative arrival times’ inherent to this proposal (and generalizations thereof). The ABK free-particle restriction is lifted in a discussion of an explicit arrival-time set-up featuring a charged particle moving in a constant magnetic field. A natural generalization of the ABK distribution is in this case shown to be critically gauge-dependent. A direct comparison to the QF distribution, which does not exhibit this flaw, is drawn (its acknowledged drawback concerning the quantum backflow effect notwithstanding).
This study presents a novel building energy management system scheme addressing the challenges of biased photovoltaic voltage prediction and optimal energy management methods applicable to existing ...infrastructure. A biased PV prediction model is proposed to obtain predictions aligned with the intended uncertainty tendencies. In addition, an energy management scheme is introduced to increase energy efficiency by reducing the overall cost without requiring additional controllable power sources. Furthermore, a control scheme for optimizing the operational cost while considering the occupants’ thermal discomfort is proposed by analyzing the occupancy rate in the building and implementing appropriate temperature settings and elevator operations. This approach has the advantage of minimizing overall electricity cost while considering the users’ dissatisfaction, without the installation of additional controllable power resources. Here, the feasibility of the proposed approach is demonstrated through a reduction in the daily electricity cost and peak power by 8.56% and 11.75%, respectively, compared with scenarios without a proper building energy management system. These results demonstrated the effectiveness of the proposed building energy management system for achieving energy efficiency and cost savings in practical building environments. The proposed scheme can be used in buildings with diverse users to reduce energy consumption and overall building cost.
•Proposed a building energy management system model robust against data uncertainty.•The proposed scheme reduced energy consumption and overall building cost.•Optimized energy consumption using a biased prediction scheme.•Optimized operational cost while considering the occupants’ thermal discomfort.
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