Gauging energy poverty in developing countries with a composite metric of electricity access

Energy poverty is a significant development issue that is not univocally interpreted. In many parts of the world, people do not have access to modern and reliable energy, which can be a big problem, particularly for vulnerable and developing countries. When vulnerable people do not have access to energy, they will often not be able to get the power they need to improve their lives. In addition, they may not be able to get proper food, education, health, sanitation, or basic needs for daily living. We use interval-based composite indicators and triplex representations of intervals to measure and assess access to electricity in 54 developing countries as a concept approximating relevant aspects of energy poverty. The proposed composite metric is innovative because it accurately quantifies how much electricity is available to people and how resilient and vulnerable people in developing countries are when they lose access to energy. After comparing the different representations, we found that one group of developing countries is more vulnerable to national and international events than the other. However, other countries are more resilient to electricity access problems. Conflicts and wars can impact the index used to measure energy poverty. However, as measured by the index, these factors contribute to poor performance.     

Cost-benefit analysis and emission reduction of lighting retrofits in residential sector

This study projects electricity savings, cost-benefit analysis and emission reduction of lighting retrofits in Malaysia residential sector. The cost-benefit is determined as a function of energy savings due to retrofit of more efficient lighting system. The energy savings were calculated based on 25, 50 and 75% of potential retrofits of inefficient lighting in residential sector. The study found that, this strategy save a significant amount of energy and consumers money. However, an effort to create energy efficiency awareness among consumers and subsidies efficient lighting should be identified, because this efficient lighting is quite expensive in Malaysia.     

The impact of transparency policies on local flexibility markets in electric distribution networks

The energy transition brings various technical, economic, and organizational challenges. One major topic, especially in zonal electricity markets, is the organization of future congestion management. Local flexibility market (LFM) is an often discussed concept of market-based congestion management. Like the whole energy system, the market transparency of LFMs can influence individual bidders' behavior. In this context, the predictability of the network status of distribution networks and an LFM's outcome, depending on a given transparency policy, is investigated in this paper. For this, forecast models based on artificial neural networks (ANN) are implemented on synthetic distribution network and LFM data. Three defined transparency policies determine the amount of input data used for the models. The results suggest that the transparency policy can influence the distribution network status and LFM outcome predictability, but appropriate forecasts are generally feasible. Therefore, the transparency policy should not conceal information but provide a level playing field for all parties involved. Providing semi-disaggregated data on the network area level can be suitable for bidders' decision-making and reduces transaction costs.     

山西省高耗能行业用电需求分析

针对山西省以高耗能为主的偏重型工业用电特点,在深入分析全省的高耗能行业发展现状的基础上,对高耗能行业的电力消费情况进行了研究分析,并就未来高耗能行业的用电走势做了预测,为未来进行经济结构调整提供一定的参考。     

Incentives for cost reduction and cost padding in electricity markets with overlapping “green” regulations

We examine overlapping regulations in electricity markets. Using an example based on a stylized model of a competitive energy market, we study cost-reduction and cost-padding incentives by “green-energy” producers in an electricity market employing an emissions tax and the simultaneous use of a green quota for the generation portfolio and a fair rate-of-return constraint implemented via a system of feed-in tariffs. We show inter alia that when subsidies are phased out, exploitation of the green technologies full cost-reduction potential is a Nash Equilibrium but emissions will increase. In addition, green-energy producers can engage in collusive cost padding to increase profits even as they satisfy the policymaker's desired green quota.     

Industrial electricity consumption efficiency and energy policy in Japan

This study analyzes the potential for energy savings by identifying inefficiencies in electricity use and their determinants in the Japanese industrial sector. Specifically, we used stochastic frontier analysis to estimate inefficiencies in electricity consumption based on data obtained from electric power companies. We identified significant determinants of electricity consumption efficiency and that changes in national energy policy following the Great East Japan Earthquake changed electricity consumption behavior. The contribution of this study is that its findings can be used to improve the cost-effectiveness of policies aimed at improving energy efficiency.     

Are shocks to electricity consumption transitory or permanent? Sub-national evidence from Turkey

This is the first study that aims to investigate policy shocks to energy consumption in terms of unit root properties by sector. More precisely, we analyze the stationarity of electricity consumption for 12 regions of Turkey by four sectors in addition to total electricity consumption by region (for a total of 60 cases). We find that 48 cases are non-stationary and 12 cases are stationary. Thus, policies to decrease or stimulate the use of electricity have permanent effects on electricity consumption in 80% of the cases and transitory effects in the rest. Findings and policy implications are further discussed.     

Electricity price forecasting using neural networks with an improved iterative training algorithm

In a competitive electricity market, the forecasting of energy prices is an important activity for all market participants either for developing bidding strategies or for making investment decisions. In this article, a new forecasting strategy is proposed for short-term prediction of the electricity price, which is a complex quantity with nonlinear, volatile and time-dependent behaviour. Our forecast strategy includes two novelties: a new two-stage feature selection algorithm and a new iterative training algorithm. The feature selection algorithm has two filtering stages to remove irrelevant and redundant candidate inputs, respectively. This algorithm is based on mutual information and correlation analysis. The improved iterative training algorithm is composed of two neural networks in which the output of the first neural network is one of the inputs to the second. The overall proposed strategy is applied to the Pennsylvania–New Jersey–Maryland (PJM) electricity markets and compared with some of the most recent price forecast methods.     

The status of and opportunities for utility-scale battery storage in Australia: A regulatory and market perspective

Australia's electricity market is rapidly adding renewable energy generation. Utility-scale batteries could have a major role in facilitating these transitions; however, their deployment is still largely state-subsidized. We summarize the current and future roles for batteries from a legal-economic perspective in the context of Australia's electricity market framework. We find that the future of batteries in Australia is not only a function of the large-scale deployment of renewables, their cost development and the comparative future cost of competing gas turbines but also of national electricity market and state policy reforms focusing on reliability.     

通信基站空调基准耗电量计算方法的研究

采用合同能源管理模式对通信基站空调系统进行节能改造时,准确计算基准能耗是核定节能量的关键。本文以广东中山地区90 mm厚彩钢板结构通信基站为研究对象,实时测量了空调系统节能改造后的能耗数据,提出了利用基站总耗电量、空调及新风系统耗电量、室内外气温的实测数据计算空调基准耗电量的方法,并用基站耗电量的实测值对计算结果进行了验证。分析了计算周期、样本数据温度范围对计算准确性的影响,得到最优计算方案。研究结果表明,利用该计算方法可方便、准确地得到空调基准耗电量,对核定通信基站节电量具有参考价值。     

Energy policy scenarios to reach challenging climate protection targets in the German electricity sector until 2050

In this article we demonstrate how challenging greenhouse gas reduction targets of up to 95% until 2050 can be achieved in the German electricity sector. In the analysis, we focus on the main requirements to reach such challenging targets. To account for interdependencies between the electricity market and the rest of the economy, different models were used to account for feedback loops with all other sectors. We include scenarios with different runtimes and retrofit costs for existing nuclear plants to determine the effects of a prolongation of nuclear power plants in Germany. Key findings for the electricity sector include the importance of a European-wide coordinated electricity grid extension and the exploitation of regional comparative cost effects for renewable sites. Due to political restrictions, nuclear energy will not be available in Germany in 2050. However, the nuclear life-time extension has a positive impact on end consumer electricity prices as well as economic growth in the medium term, if retrofit costs do not exceed certain limits.     

Power grid balancing of energy systems with high renewable energy penetration by demand response

It is generally accepted that the integration of intermittent energy resources like wind energy and photovoltaics into an electricity system cannot exceed a limit of around 20% or 25%, see, e.g. [EWEA, 2005. Large-scale integration of wind energy in the European power supply: analysis, issues and recommendations. The European Wind Energy Association]. However, the decoupling of electricity generation and consumption cannot be implemented only by use of electricity storage. In the end, electricity is converted into many different energy services – quite often into thermal energy – which is better suited for storage. This article presents the results of investigations which studied the potential of those demand response activities for Germany. The investigations are based on both modelling of thermal storage devices and laboratory tests.     

重庆某医院中央空调系统改造及评估

该文以重庆市某医院为对象,对医院进行用能设备统计和能源审计,得到该建筑单位面积能耗为136.82k Wh/m~2·a,计算建筑分类能源占比及逐月用电量,分析存在的问题,锁定该建筑的主要节能改造目标在中央空调系统,结合测试数据计算空调系统各部分能耗值及比例,确定改造手段为主机加装智能控制装置、水泵变频、冷却塔自控进行改造,医院改造后空调系统节能率达39.85%,占建筑总用电量的8.96%,相当于节省40.73万元的经济效益。     

Interactive Time-of-use demand response for industrial electricity customers: A case study

Demand response (DR) programs are regarded as one of the most reliable and reasonable methods to benefit electricity suppliers and consumers. This paper presents a modified approach to DR based on an Interactive Time-of-Use (ITOU) model by which volunteer industrial customers and their electricity suppliers obtain the best possible performance. Owing to this aim, when studying the region's electrical load profile to determine the peak-hours, the one-year production and sales profile of industrial customers is also studied to select off-peak hours for industrial subscribers. The results of program implementation for the selected and volunteer industrial customers at the sub-transmission level are presented to evaluate the performance of the proposed model. Considering the electricity bills of the subscribers in the program based on reduced energy consumption at peak hours (selected by the utility), and increased energy consumption at the off-peak price (selected by industrial customers), the economic benefits to industrial customers are calculated and verified. Plotting new load curves confirms load shifting from the peak to the valley of the load curve. The obtained results of the conventional TOU and ITOU models indicate that the proposed ITOU is more effective in achieving program goals.     

Regulatory energy calculations versus real energy use in high-performance houses

How accurately can official energy performance calculations assess the real energy use in high-performance houses? This question was investigated by analysing 537 dwellings. Data on building characteristics and calculated performance from the Flemish Energy Performance of Buildings (EPB) database were complemented with data from energy utilities and surveys of inhabitants, their socio-demographic characteristics and user behaviours. While the real and theoretical energy uses were strongly correlated, the official calculation method overestimated the heating energy use of most houses while neglecting important electricity end uses. The prediction error varied strongly between individual cases. Two options within the calculation procedure had a significant impact on these prediction errors: the use of default values for the air tightness of the building envelope and the reported return temperature of the space heating system. The simplified calculation of net domestic hot water consumption and the real heating of the master bedrooms also affected prediction accuracy. However, extrapolations are hazardous due to the risk of selection and non-response biases implied by the approach and the need for further research into the causalities. Nonetheless, the findings stress the importance of accurate input data and realistic default values for calculation models used for high-performance buildings.     

滨海道路软土路基沉降工后预测——以厦门杏林北外环道路为例

通过对软土路基的沉降机理进行沉降组成分析,得出杏林软土地基沉降主要由主固结沉降组成。并运用灰色理论选用连续型直接数据GM（1,1）模型对厦门市杏林北环路高浦至锦园段公路软土路基沉降进行预测,通过与现场监测数据进行对比和分析发现,二者误差在1％内,表明用灰色模型预测软土沉降在该工程段中是适用的,预测的沉降值比较准确。     

Does market concentration affect wholesale electricity prices? An analysis of the Indian electricity sector in the COVID-19 pandemic context

This study explores whether the market concentration affects the wholesale prices of electricity generation among Indian companies by drawing 15-min frequency data related to electricity production, wholesale prices, and electricity demand in August 2020 during the COVID-19 pandemic. The ARDL model estimates show a positive relationship between market concentration and wholesale energy prices. The study recommends the adoption of policies to reduce market concentration and enhance clean energy development.     

On the relation between the energy and social characteristics of the residential sector

Social, financial, energy and technical data from about 1110 households have been collected during 2004 in the major Athens area. The sample has been divided in seven income groups and a detailed analysis has been performed. Important conclusions have been drawn regarding the quality of households, the operational conditions and the energy spent per income group. Low income people are more likely to be living in old buildings with poor envelope conditions. The cost per person and unit area is much higher for the low income group for both heating and electricity. Fuel poverty is quite high, especially when the actual oil prices are considered.     

Design of regional flexibility markets for electricity: A product classification framework for and application to German pilot projects

With the growing role of distributed energy resources, the electricity network is challenged by numerous technical problems, such as capacity congestion and over- or under-voltage. An often-discussed response, especially in the European zonal electricity system, is to implement regional flexibility markets. We contribute to this discussion by providing a comprehensive classification framework for the design of flexibility products by combining technical requirements with classical auction theory. The framework structures 23 product parameters in four stages of abstraction. By applying the framework to five market approaches used in current German research projects, we demonstrate its usefulness for consistent comparison of flexibility products at a high level of detail. This framework can empower national and international policymakers and practitioners in assessing flexibility markets holistically, thereby facilitating the implementation of sound solutions.     

基于前馈网络的岩体爆破效应预测研究

将神经网络理论知识和爆破专业知识有机地结合在一起，提出了一种新的岩体爆破效应预测的前馈网络理论方法。该方法适合于不同的爆破参数和不同的岩体条件，是一种普遍适用的方法，同时也是一种“面向数据”的方法。通过对三峡工程左岸坝区岩体爆破效应预测的研究表明，本文方法与通常的经验公式法、回归分析法以及ＢＰ网络方法相比，具有较高的预报精度