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A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (30 November 2016) | Viewed by 51516

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Prof. Dr. Robert Lundmark

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Department of Business Administration, Technology and Social Sciences, Luleå University of Technology, SE-971 87 Luleå, Sweden
Interests: forest, energy and environmental economics; econometrics and mathematical programming methods; economic policy; bioeconomy
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Special Issue Information

Dear Colleagues,

The overall aim of this Special Issue of Energies is to publish studies that enhance our understanding of alternative future energy transitions, their implications for energy systems, human well-being, and the environment, and how they might be influenced by decision makers. A number of major challenges face current energy systems. Many of these challenges need to be addressed simultaneously and from a system perspective.

This Special Issue welcomes contributions that take a system perspective on identified challenges and implement them using, e.g., integrated system analysis, spatial and behavioral heterogeneity, multi-criteria analysis, energy technology assessment, and uncertainty and risk analyses. Extended contributions are welcomed to facilitate detailed model or method descriptions.

Prof. Dr. Robert Lundmark
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

systems analysis
energy policy
energy transition
energy scenario
energy scenario

Published Papers (7 papers)

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7684 KiB

Open AccessFeature PaperArticle

Exergoeconomic Performance Comparison and Optimization of Single-Stage Absorption Heat Transformers

by S. Mohammad S. Mahmoudi, Sina Salehi, Mortaza Yari and Marc A. Rosen

Energies 2017, 10(4), 532; https://doi.org/10.3390/en10040532 - 14 Apr 2017

Cited by 19 | Viewed by 4161

Abstract

Three single-stage absorption heat transformer (SSHT) configurations are modeled, analyzed and compared from the viewpoints of thermodynamics and economics, using the Engineering Equation Solver (EES) software. In addition, a multi-objective optimization is carried out for the three configurations to specify the optimal design point considering the second law efficiency and the product unit cost as two objective functions. The configurations differ from one another considering the number of heat exchangers used in them. The results show that the coefficient of performance (COP) and exergy coefficient of performance (ECOP) for configuration 3 are around 35% and 30% higher than the corresponding values for configuration 1, respectively. Also, configuration 2 is found to be more economic with a product unit cost of about 21% and 5% lower than those for configurations 1 and 3, respectively. Furthermore, it is observed that relatively higher absorber temperatures can be achieved by configurations 2 and 3 compared to configuration 1. It is concluded from the multi-objective optimization that the conditions at which the evaporator, condenser and absorber temperatures are 86.51 °C, 39.03 °C and 123.1 °C, respectively, represents an optimal solution. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2016)

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4287 KiB

Open AccessArticle

Effects of Increased Wind Power Generation on Mid-Norway’s Energy Balance under Climate Change: A Market Based Approach

by Baptiste François, Sara Martino, Lena S. Tøfte, Benoit Hingray, Birger Mo and Jean-Dominique Creutin

Energies 2017, 10(2), 227; https://doi.org/10.3390/en10020227 - 15 Feb 2017

Cited by 21 | Viewed by 7424

Abstract

Thanks to its huge water storage capacity, Norway has an excess of energy generation at annual scale, although significant regional disparity exists. On average, the Mid-Norway region has an energy deficit and needs to import more electricity than it exports. We show that this energy deficit can be reduced with an increase in wind generation and transmission line capacity, even in future climate scenarios where both mean annual temperature and precipitation are changed. For the considered scenarios, the deficit observed in winter disappears, i.e., when electricity consumption and prices are high. At the annual scale, the deficit behaviour depends more on future changes in precipitation. Another consequence of changes in wind production and transmission capacity is the modification of electricity exchanges with neighbouring regions which are also modified both in terms of average, variability and seasonality. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2016)

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2202 KiB

Open AccessArticle

How Do Dietary Choices Influence the Energy-System Cost of Stabilizing the Climate?

by David Bryngelsson, Fredrik Hedenus, Daniel J. A. Johansson, Christian Azar and Stefan Wirsenius

Energies 2017, 10(2), 182; https://doi.org/10.3390/en10020182 - 05 Feb 2017

Cited by 14 | Viewed by 16659

Abstract

We investigate how different global dietary scenarios affect the constraints on, and costs of, transforming the energy system to reach a global temperature stabilization limit of 2 °C above the pre-industrial level. A global food and agriculture model, World Food Supply Model (WOFSUM), is used to create three dietary scenarios and to calculate the CH₄ and N₂O emissions resulting from their respective food-supply chains. The diets are: (i) a reference diet based on current trends; (ii) a diet with high (reference-level) meat consumption, but without ruminant products (i.e., no beef, lamb, or dairy, only pork and poultry); and (iii) a vegan diet. The estimated CH₄ and N₂O emissions from food production are fed into a coupled energy and climate-system optimization model to quantify the energy system implications of the different dietary scenarios, given a 2 °C target. The results indicate that a phase-out of ruminant products substantially increases the emission space for CO₂ by about 250 GtC which reduces the necessary pace of the energy system transition and cuts the net present value energy-system mitigation costs by 25%, for staying below 2 °C. Importantly, the additional cost savings with a vegan diet––beyond those achieved with a phase-out of ruminant products––are marginal (only one additional percentage point). This means that a general reduction of meat consumption is a far less effective strategy for meeting the 2 °C target than a reduction of beef and dairy consumption. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2016)

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2215 KiB

Open AccessArticle

A System Dynamics Analysis of Investment, Technology and Policy that Affect Natural Gas Exploration and Exploitation in China

by Jianzhong Xiao, Jinhua Cheng, Jun Shen and Xiaolin Wang

Energies 2017, 10(2), 154; https://doi.org/10.3390/en10020154 - 25 Jan 2017

Cited by 14 | Viewed by 6794

Abstract

Natural gas has an increasing role in Chinese energy transformation. We present a system dynamics model of the natural gas industry in China. A new system dynamics model for natural gas companies based on reserve exploration and well construction as well as investment dynamics is proposed. The contribution of the paper is to analyze the influence of technology, investment and policy factors on the natural gas industry. We found that the dynamics of the main variables, including gas policy, cost of investment, accounting depreciation and exploitation technology, are sensitive to the sustainable development of resources. The simulations and results presented here will be helpful for government to reform policies, and for upstream companies to make decisions. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2016)

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1627 KiB

Open AccessArticle

Economic Growth, Electricity Consumption, Labor Force and Capital Input: A More Comprehensive Analysis on North China Using Panel Data

by Huiru Zhao, Haoran Zhao, Xiaoyu Han, Zhonghua He and Sen Guo

Energies 2016, 9(11), 891; https://doi.org/10.3390/en9110891 - 29 Oct 2016

Cited by 26 | Viewed by 5585

Abstract

Over the past three decades, China’s economy has witnessed remarkable growth, with an average annual growth rate over 9%. However, China also faces great challenges to balance this spectacular economic growth and continuously increasing energy use like many other economies in the world. With the aim of designing effective energy and environmental policies, policymakers are required to master the relationship between energy consumption and economic growth. Therefore, in the case of North China, a multivariate model employing panel data analysis method based on the Cobb-Douglas production function which introduces electricity consumption as a main factor was established in this paper. The equilibrium relationship and causal relationship between real GDP, electricity consumption, total investment in fixed assets, and the employment were explored using data during the period of 1995–2014 for six provinces in North China, including Beijing City, Tianjin City, Hebei Province, Shanxi Province, Shandong Province and Inner Mongolia. The results of panel co-integration tests clearly state that all variables are co-integrated in the long term. Finally, Granger causality tests were used to examine the causal relationship between economic growth, electricity consumption, labor force and capital. From the Granger causality test results, we can draw the conclusions that: (1) There exist bi-directional causal relationships between electricity consumption and real GDP in six provinces except Hebei; and (2) there is a bi-directional relationship between capital input and economic growth and between labor force input and economic growth except Beijing and Hebei. Therefore, the ways to solve the contradiction of economic growth and energy consumption in North China are to reduce fossil energy consumption, develop renewable and sustainable energy sources, improve energy efficiency, and increase the proportion of the third industry, especially the sectors which hold the characteristics of low energy consumption and high value-added. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2016)

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2507 KiB

Open AccessArticle

Two-Stage Multi-Objective Collaborative Scheduling for Wind Farm and Battery Switch Station

by Zhe Jiang, Xueshan Han, Zhimin Li, Wenbo Li, Mengxia Wang and Mingqiang Wang

Energies 2016, 9(11), 886; https://doi.org/10.3390/en9110886 - 29 Oct 2016

Cited by 3 | Viewed by 4071

Abstract

In order to deal with the uncertainties of wind power, wind farm and electric vehicle (EV) battery switch station (BSS) were proposed to work together as an integrated system. In this paper, the collaborative scheduling problems of such a system were studied. Considering the features of the integrated system, three indices, which include battery swapping demand curtailment of BSS, wind curtailment of wind farm, and generation schedule tracking of the integrated system are proposed. In addition, a two-stage multi-objective collaborative scheduling model was designed. In the first stage, a day-ahead model was built based on the theory of dependent chance programming. With the aim of maximizing the realization probabilities of these three operating indices, random fluctuations of wind power and battery switch demand were taken into account simultaneously. In order to explore the capability of BSS as reserve, the readjustment process of the BSS within each hour was considered in this stage. In addition, the stored energy rather than the charging/discharging power of BSS during each period was optimized, which will provide basis for hour-ahead further correction of BSS. In the second stage, an hour-ahead model was established. In order to cope with the randomness of wind power and battery swapping demand, the proposed hour-ahead model utilized ultra-short term prediction of the wind power and the battery switch demand to schedule the charging/discharging power of BSS in a rolling manner. Finally, the effectiveness of the proposed models was validated by case studies. The simulation results indicated that the proposed model could realize complement between wind farm and BSS, reduce the dependence on power grid, and facilitate the accommodation of wind power. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2016)

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5394 KiB

Open AccessArticle

Application of a Gradient Descent Continuous Actor-Critic Algorithm for Double-Side Day-Ahead Electricity Market Modeling

by Huiru Zhao, Yuwei Wang, Sen Guo, Mingrui Zhao and Chao Zhang

Energies 2016, 9(9), 725; https://doi.org/10.3390/en9090725 - 09 Sep 2016

Cited by 12 | Viewed by 6154

Abstract

An important goal of China’s electric power system reform is to create a double-side day-ahead wholesale electricity market in the future, where the suppliers (represented by GenCOs) and demanders (represented by DisCOs) compete simultaneously with each other in one market. Therefore, modeling and simulating the dynamic bidding process and the equilibrium in the double-side day-ahead electricity market scientifically is not only important to some developed countries, but also to China to provide a bidding decision-making tool to help GenCOs and DisCOs obtain more profits in market competition. Meanwhile, it can also provide an economic analysis tool to help government officials design the proper market mechanisms and policies. The traditional dynamic game model and table-based reinforcement learning algorithm have already been employed in the day-ahead electricity market modeling. However, those models are based on some assumptions, such as taking the probability distribution function of market clearing price (MCP) and each rival’s bidding strategy as common knowledge (in dynamic game market models), and assuming the discrete state and action sets of every agent (in table-based reinforcement learning market models), which are no longer applicable in a realistic situation. In this paper, a modified reinforcement learning method, called gradient descent continuous Actor-Critic (GDCAC) algorithm was employed in the double-side day-ahead electricity market modeling and simulation. This algorithm can not only get rid of the abovementioned unrealistic assumptions, but also cope with the Markov decision-making process with continuous state and action sets just like the real electricity market. Meanwhile, the time complexity of our proposed model is only O(n). The simulation result of employing the proposed model in the double-side day-ahead electricity market shows the superiority of our approach in terms of participant’s profit or social welfare compared with traditional reinforcement learning methods. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2016)

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