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Due to the higher energy efficiency as well as the higher flexibility and reliability of energy supply, multi-carrier energy systems (MCESs) have attracted extensive attention. However, the power imbalance caused by uncertainty, the complicated couplings among multiple carriers, and the communication obstacles among multiple MCESs bring challenges to the synergistic scheduling of multiple MCESs. To this end, this paper studies the synergistic scheduling of multi-MCES coupled with electricity, natural gas, heating, and cooling carriers, considering integrated demand response (IDR) program and load volatility. First, an IDR program with electricity, heating, and cooling loads is proposed, where the consumers can change their energy consumption patterns in response to price signals to reduce operating costs. Second, to smooth the electricity load curve and avoid load fluctuations, load volatility is taken into account when implementing the IDR program. In addition, the non-convex constraints of natural gas network are tackled via second-order cone relaxation, and the scheduling of multi-MCES is reformulated as mixed integer second-order cone programming (MISOCP). Finally, the synergistic scheduling model of multi-MCES considering IDR program and load volatility is solved by consensus-based alternating direction method of multipliers with limited boundary information exchange with neighboring MCESs. Numerical results illustrate the effectiveness of the proposed distributed IDR program in a multi-MCES. [ABSTRACT FROM AUTHOR]

Improving the new energy enterprise technological innovation capability can effectively protect the ecology of the environment and reduce the consumption of resources. Based on the gravity model and the quadratic assignment procedure analysis method, this paper builds the spatial interaction network of new energy enterprise technology innovation capability. In this paper, we analyse the structural characteristics of the spatial interaction network and explore the main factors that influence it. The results show that the spatial interaction network of new energy enterprise technological innovation capability is robust. The network relations are closely linked, and there is no strict grade in this spatial interaction network. There are both centralization and marginalization trends in this network, and the block division is obvious. In addition, if there is proper reception, transmission capability, economic distance, and geographical distance are the main factors that can impact the interaction strength of this network. According to empirical research results, the relevant policy recommendations for promoting the new energy enterprise technology innovation capability are proposed. The policy recommendations include establishing the new energy technology innovation exchange platform, formulating regional development policies for the new energy enterprise, and improving the regional investment financing mechanism of the new energy enterprise. [ABSTRACT FROM AUTHOR]

Integrated energy systems (IESs) have attracted increasing attention in recent years due to the high energy efficiency and low emission of carbon dioxide. To deal with the limitation of single IES, distributed energy networks consisting of multi-IESs are proposed to improve the complementarity of both the energy supply and the demand. This paper mainly focuses on the day-ahead energy management of the whole energy network for the economic operation of the system, following which, a cooperative game is formulated to determine the optimal strategy of each IES to minimize the coalition daily cost. Meanwhile, an allocation mechanism is designed from the perspective of probability to allocate coalition cost to each IES. According to the results of the numerical study, the proposed approach can improve the economic performance of both the energy network and the individual IES by interchanging electrical and thermal energies in the network. [ABSTRACT FROM AUTHOR]

Conventional energy sources are limited, whereas the energy demand is increasing exponentially. There is immediate need to develop efficient systems to extract more useful energy from the same fuel input. Cogeneration and trigeneration systems use waste heat from prime movers to produce more useful energy than conventional methods in the form of heat and cooling. In this paper, an experimental and simulation based study of compression ignition engine operated micro-cogeneration and trigeneration systems working on diesel and other vegetable oil based fuel derivatives is presented. The energy and exergy analyses of both the cogeneration and trigeneration systems were done. The results obtained with base line diesel show that the overall thermal efficiency was 79.43% for cogeneration and 78.64% for trigeneration. The exergy effi- ciency of the system was found to be 32.80% for cogeneration and 33.08% for trigeneration. The system was modeled and simulated using TRNSYS, and the simulation results were compared with the experimental results for the validation. The improved system model for trigeneration was developed using TRNSYS to determine the scope for improvement, and it was found that it achieved the energy efficiency of 89.20% and the exergy efficiency of 45.94%. [ABSTRACT FROM AUTHOR]

Electric load forecasting, as a crucial way to tackle the energy tasks, helps to provide correct guidance and reduce energy consumption for an electric system. This paper introduces a novel forecasting method that combines wavelet transform (WT) and particle swarm optimization (PSO) with an extreme learning machine, phase space reconstruction (PSR) and a least squares support vector machine. Because the electric data that are easily interfered by many factors are unstable, directly adopting the data containing noise will affect the forecasting performance. Prior to the electric forecasting conduct, WT is adopted to reduce the noise. Because only a single method is not able to suit for all kinds of data, three individual models with a strong nonlinear learning capability are applied to deal with the whole time series that have complex nonlinear characteristics. They are used to obtain intermediate forecasting results. Besides, the C-C method is utilized to acquire the optimal delay time and embedding dimension of the PSR. PSO is employed to attain the best proportion of each single method of the hybrid model. By multiplying the corresponding optimal weights by all the three forecasting results and then adding them up, the final result of the hybrid method can be attained. In order to assess the accuracy and applicability of the proposed hybrid method, half-hourly electric load data of New South Wales and Victoria of Australia are used as case studies. The experiment results show that the hybrid method outperforms the individual methods and is appropriate for different kinds of data. [ABSTRACT FROM AUTHOR]

This paper presents a load shifting algorithm for optimizing consumption patterns by taking preferences of customers and electricity costs into account. A load shifting cost component is introduced for recording inconvenience experienced by customers while load shifting. Load shifting cost reflects the reluctance of customers for their inconvenience where the customers are unique in terms of their preferences and costs. The proposed algorithm would allow demand side management to be conducted in a decentralized manner, where no problem of load synchronization exists. Multi-agent system based simulation studies were carried out on three types of customers namely, residential, commercial, and industrial customers to verify this algorithm. The simulation results show that substantial load levelling is achieved by the proposed algorithm. This study is further extended to examine the effects of incentives that encourage customers to participate in load shifting. However, this does not lead to a better load levelling perhaps due to the small sample sized simulation systems. Instead, incentives could be used as a short-term measure for customers to know that how the mechanism would work for them. [ABSTRACT FROM AUTHOR]

Globally, buildings are responsible for approximately 40% of the total world annual energy consumption. Most of this energy is for the provision of lighting, heating, cooling, and air conditioning. Increasing awareness of the environmental impact of CO2 and NOx emissions and chlorofluorocarbons triggered a renewed interest in environmentally friendly cooling and heating technologies. Under the 1997 Montreal Protocol, governments agreed to phase out chemicals used as refrigerants that have the potential to destroy stratospheric ozone. It was therefore considered desirable to reduce energy consumption and decrease the rate of depletion of world energy reserves and pollution of the environment. One way of reducing building energy consumption is to design buildings that are more economical in their use of energy for heating, lighting, cooling, ventilation, and hot water supply. Passive measures, particularly natural or hybrid ventilation rather than air conditioning, can dramatically reduce primary energy consumption. However, exploitation of renewable energy in buildings and agricultural greenhouses can also significantly contribute toward reducing dependency on fossil fuels. Therefore, promoting innovative renewable applications and reinforcing the renewable energy market will contribute to preservation of the ecosystem by reducing emissions at local and global levels. This will also contribute to the amelioration of environmental conditions by replacing conventional fuels with renewable energies that produce no air pollution or greenhouse gases. The provision of good indoor environmental quality (IEQ) while achieving energy and cost efficient operation of the heating, ventilating, and air-conditioning plants in buildings represents a multivariant problem. The comfort of building occupants is dependent on many environmental parameters including air speed, temperature, relative humidity, and quality in addition to lighting and noise. The overall objective is to provide a high level of building performance, which can be defined as IEQ, energy efficiency (EE), and cost efficiency (CE). IEQ is the perceived condition of comfort that building occupants experience due to the physical and psychological conditions to which they are exposed by their surroundings. The main physical parameters affecting IEQ are air speed, temperature, relative humidity, and quality. EE is related to the provision of the desired environmental conditions while consuming the minimal quantity of energy. CE is the financial expenditure on energy relative to the level of environmental comfort and productivity that the building occupants attained. The overall CE can be improved by improving the IEQ and the EE of a building. The increased availability of reliable and efficient energy services stimulates new development alternatives. Anticipated patterns of future energy use and consequent environmental impacts (acid precipitation, ozone depletion, and greenhouse effect or global warming) are comprehensively discussed in this paper. Throughout the theme several issues relating to renewable energies, environment, and sustainable development are exam-ined from both current and future perspectives. It is concluded that renewable environmentally friendly energy must be encouraged, promoted, implemented, and demonstrated by full-scale plant especially for use in remote rural areas. [ABSTRACT FROM AUTHOR]

In this paper, we present a numerical study on the thermocapillary migration of drops. The Navier–Stokes equations coupled with the energy conservation equation are solved by the finite-difference front-tracking scheme. The axisymmetric model is adopted in our simulations, and the drops are assumed to be perfectly spherical and nondeformable. The benchmark simulation starts from the classical initial condition with a uniform temperature gradient. The detailed discussions and physical explanations of migration phenomena are presented for the different values of (1) the Marangoni numbers and Reynolds numbers of continuous phases and drops and (2) the ratios of drop densities and specific heats to those of continuous phases. It is found that fairly large Marangoni numbers may lead to fluctuations in drop velocities at the beginning part of simulations. Finally, we also discuss the influence of initial conditions on the thermocapillary migrations. [ABSTRACT FROM AUTHOR]

We revisit a series of papers on science and society issues by David Hafemeister in the 1970s and 1980s. The emphasis in the present work is on world oil production limits and some consequences of various possible scenarios for the near future. Some of the data and scenarios used by Hafemeister are updated for U.S. oil production in the past two decades, and extended to an analysis of a peak in world oil production in the future. We discuss some simple scenarios for future energy use patterns and look at the consequence of these scenarios as world oil production begins to decline. We also provide a list of resources for critical investigations of natural resource extraction and depletion patterns. [ABSTRACT FROM AUTHOR]

In this paper, the causality analysis between biomass energy consumption and economic growth was investigated in the selected 10 countries by using Autoregressive Distributed Lag bounds testing approach and vector error-correction models. Annual data cover the period from 1960 to 2010. The short run, long run, and strong causality results suggest that there is unidirectional causality from Y to biomass energy consumption for Austria and Turkey, and there is unidirectional causality from biomass energy consumption to Y for Hungary and Poland. For Spain, Sweden, and France, it was found as bidirectional causality. According to strong and long run causalities, bidirectional causality was found for all the countries. [ABSTRACT FROM AUTHOR]

In this paper, a robotic fish with a caudal fin with vertical phase differences is studied, especially focusing on the energy consumption. Energies for thrusting a conventional robotic fish and one with caudal fin with vertical phase differences are obtained and compared each other. It is shown that a robotic fish with a caudal fin with vertical phase differences can save more energy, which implies the efficient thrusting via a vertically waving caudal fin. [ABSTRACT FROM AUTHOR]