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Day-ahead electricity price forecasting using back propagation neural networks and weighted least square

S. Surender REDDY,Chan-Mook JUNG,Ko Jun SEOG

《能源前沿（英文）》 2016年第10卷第1期页码 105-113 doi: 10.1007/s11708-016-0393-y

摘要： This paper proposes the day-ahead electricity price forecasting using the artificial neural networks (ANN) and weighted least square (WLS) technique in the restructured electricity markets. Price forecasting is very important for online trading, e-commerce and power system operation. Forecasting the hourly locational marginal prices (LMP) in the electricity markets is a very important basis for the decision making in order to maximize the profits/benefits. The novel approach proposed in this paper for forecasting the electricity prices uses WLS technique and compares the results with the results obtained by using ANNs. To perform this price forecasting, the market knowledge is utilized to optimize the selection of input data for the electricity price forecasting tool. In this paper, price forecasting for Pennsylvania-New Jersey-Maryland (PJM) interconnection is demonstrated using the ANNs and the proposed WLS technique. The data used for this price forecasting is obtained from the PJM website. The forecasting results obtained by both methods are compared, which shows the effectiveness of the proposed forecasting approach. From the simulation results, it can be observed that the accuracy of prediction has increased in both seasons using the proposed WLS technique. Another important advantage of the proposed WLS technique is that it is not an iterative method.

关键词： day-ahead electricity markets price forecasting load forecasting artificial neural networks load serving entities

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Can the Shanghai LNG Price Index indicate Chinese market?An econometric investigation using price discovery theory

Yeli ZENG, Cong DONG, Mikael HÖÖK, Jinhua SUN, Danyang SHI

《能源前沿（英文）》 2020年第14卷第4期页码 726-739 doi: 10.1007/s11708-020-0701-4

摘要： China became the world’s second largest liquefied natural gas (LNG) importer in 2018 but has faced extremely high import costs due to a lack of bargaining power. Assessments of the Shanghai LNG Price Index, first released in 2015, are vital for improving the understanding of these cost dynamics. This paper, using the LNG price index data from the Shanghai Petroleum and Gas Exchange (SHPGX) coupled with domestic and international LNG prices from July 1, 2015 to December 31, 2018, estimates several econometric models to evaluate the long-term and short-term equilibriums of the Shanghai LNG Price Index, the responses to market information shocks and the leading or lagging relationships with LNG and alternative energy prices from other agencies. The results show that the LNG price index of the SHPGX has already exhibited a long-term equilibrium and short-term adjustment mechanisms to reflect the average price level and market movements, but the market information transparency and price discovery efficiency of the index are still inadequate. China’s LNG market is still relatively independent of other natural gas markets, and marketization reforms are under way in China. The influence of the SHPGX LNG price index on the trading decisions of market participants is expected to improve with further development of China’s LNG reforms, the formation of a natural gas entry-exit system, and the increasing liquidity of the hub.

关键词： liquefied natural gas price index Shanghai Petroleum and Gas Exchange price discovery market reforms

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Exploring price effects on the residential water conservation technology diffusion process: a case study

Junying CHU, Hao WANG, Can WANG

《环境科学与工程前沿（英文）》 2013年第7卷第5期页码 688-698 doi: 10.1007/s11783-013-0559-3

摘要： Reforms of the water pricing management system and the establishment of a flexible water pricing system are significant for cities in northern China to tackle their critical water issues. The WATAP (Water conservation Technology Adoption Processes) model is developed in order to capture the water conservation technology adoption process under different price scenarios with disaggregate water demands down to the end use level. This model is explicitly characterized by the technological selection process under maximum marginal benefit assumption by different categories of households. In particular, when households need to purchase water devices in the provision market with the consideration of complex factors such as the life span, investment and operating costs of the device, as well as the regulated water price by the government. Applied to Tianjin city, four scenarios of water price evolutions for a long-term perspective (from year 2011 to 2030) are considered, including BAU (Business As Usual), SP1 (Scenario of Price increase with constant annual rate), SP2 (Scenario of Price increase every four years) and SP3 (Scenario of Price increase with affordable constraint), considering many factors such as historic trends, affordability and incentives for conservation. Results show that on aggregate 2.3%, 11.0% and 18.2% of fresh water can be saved in the residential sector in scenario SP1, SP2 and SP3, respectively, compared with the BAU scenario in the year 2030. The water price signals can change the market shares of different water appliances, as well as the water end use structure of households, and ultimately improve water use efficiency. The WATAP model may potentially be a helpful tool to provide insights for policy makers on water conservation technology policy analysis and assessment.

关键词： technology selection model optimization water price scenario analysis consumer behavior

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Does oil price affect the value of firms? Evidence from Tunisian listed firms

Kaouther ZAABOUTI,Ezzeddine BEN MOHAMED,Abdelfettah BOURI

《能源前沿（英文）》 2016年第10卷第1期页码 1-13 doi: 10.1007/s11708-016-0396-8

摘要： A new debate on the potential impact of oil price changes on the value of firms was initiated in this paper. Using a stochastic frontier approach, an attempt was made to derive the optimal value * of firms and calculate the value observed. Then the shortfall ( *– ) which represents the inefficiency term was explained. Starting from 19 industrial Tunisian firms listed on the Tunis Stock Exchange between 2007 and 2011, the fact that variation of oil prices can largely explain distortions in the value of firms was empirically demonstrated.

关键词： industrial Tunisian firms oil price value of firm stochastic frontier approach

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Macroeconomic impacts of oil price volatility: mitigation and resilience

Zoheir EBRAHIM, Oliver R. INDERWILDI, David A. KING

《能源前沿（英文）》 2014年第8卷第1期页码 9-24 doi: 10.1007/s11708-014-0303-0

摘要： Dependency on oil-derived fuels in various sectors, most notably in mobility, has left the global economy vulnerable to several macroeconomic economic side effects. Numerous studies have addressed the effect of price volatility on specific economic parameters. However, the current literature lacks a comprehensive review of the interactions between global macroeconomic performance and oil price volatility (OPV). Price volatility is intrinsic in commodity markets, but has been advancing at a faster rate in the crude oil market in comparison to other commodities over the past decade, reflecting the status of oil as the most globalised commodity. In this paper, the analytical literature review and analysis of the behavioral responses of macroeconomic agents to OPV shows that such volatility has several damaging and destabilizing macroeconomic impacts that will present a fundamental barrier to future sustainable economic growth if left unchecked. To ensure macroeconomic isolation from OPV, a combination of supply and demand-side policies have been recommended that can help to mitigate and build resilience to the economic uncertainty advanced by OPV.

关键词： conventional oil price volatility macroeconomy economic stability energy security

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Regional wind power forecasting model with NWP grid data optimized

Zhao WANG, Weisheng WANG, Bo WANG

《能源前沿（英文）》 2017年第11卷第2期页码 175-183 doi: 10.1007/s11708-017-0471-9

摘要： Unlike the traditional fossil energy, wind, as the clean renewable energy, can reduce the emission of the greenhouse gas. To take full advantage of the environmental benefits of wind energy, wind power forecasting has to be studied to overcome the troubles brought by the variable nature of wind. Power forecasting for regional wind farm groups is the problem that many power system operators care about. The high-dimensional feature sets with redundant information are frequently encountered when dealing with this problem. In this paper, two kinds of feature set construction methods are proposed which can achieve the proper feature set either by selecting the subsets or by transforming the original variables with specific combinations. The former method selects the subset according to the criterion of minimal-redundancy-maximal-relevance (mRMR), while the latter does so based on the method of principal component analysis (PCA). A locally weighted learning method is also proposed to utilize the processed feature set to produce the power forecast results. The proposed model is simple and easy to use with parameters optimized automatically. Finally, a case study of 28 wind farms in East China is provided to verify the effectiveness of the proposed method.

关键词： regional wind power forecasting feature set minimal-redundancy-maximal-relevance (mRMR) principal component analysis (PCA) locally weighted learning model

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A comprehensive review and analysis of solar forecasting techniques

Pardeep SINGLA, Manoj DUHAN, Sumit SAROHA

《能源前沿（英文）》 2022年第16卷第2期页码 187-223 doi: 10.1007/s11708-021-0722-7

摘要： In the last two decades, renewable energy has been paid immeasurable attention to toward the attainment of electricity requirements for domestic, industrial, and agriculture sectors. Solar forecasting plays a vital role in smooth operation, scheduling, and balancing of electricity production by standalone PV plants as well as grid interconnected solar PV plants. Numerous models and techniques have been developed in short, mid and long-term solar forecasting. This paper analyzes some of the potential solar forecasting models based on various methodologies discussed in literature, by mainly focusing on investigating the influence of meteorological variables, time horizon, climatic zone, pre-processing techniques, air pollution, and sample size on the complexity and accuracy of the model. To make the paper reader-friendly, it presents all-important parameters and findings of the models revealed from different studies in a tabular mode having the year of publication, time resolution, input parameters, forecasted parameters, error metrics, and performance. The literature studied showed that ANN-based models outperform the others due to their nonlinear complex problem-solving capabilities. Their accuracy can be further improved by hybridization of the two models or by performing pre-processing on the input data. Besides, it also discusses the diverse key constituents that affect the accuracy of a model. It has been observed that the proper selection of training and testing period along with the correlated dependent variables also enhances the accuracy of the model.

关键词： forecasting techniques hybrid models neural network solar forecasting error metric support vector machine (SVM)

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Direct energy rebound effect for road transportation in China

《工程管理前沿（英文）》页码 597-611 doi: 10.1007/s42524-023-0276-y

摘要： The enhancement of energy efficiency stands as the principal avenue for attaining energy conservation and emissions reduction objectives within the realm of road transportation. Nevertheless, it is imperative to acknowledge that these objectives may, in part or in entirety, be offset by the phenomenon known as the energy rebound effect (ERE). To quantify the long-term EREs and short-term EREs specific to China’s road transportation, this study employed panel cointegration and panel error correction models, accounting for asymmetric price effects. The findings reveal the following: The long-term EREs observed in road passenger transportation and road freight transportation range from 13% to 25% and 14% to 48%, respectively; in contrast, the short-term EREs in road passenger transportation and road freight transportation span from 36% to 41% and 3.9% to 32%, respectively. It is noteworthy that the EREs associated with road passenger transportation and road freight transportation represent a partial rebound effect, falling short of reaching the magnitude of a counterproductive backfire effect. This leads to the inference that the upsurge in energy consumption within the road transportation sector cannot be solely attributed to advancements in energy efficiency. Instead, various factors, including income levels, the scale of commodity trade, and industrial structure, exert more substantial facilitating influences. Furthermore, the escalation of fuel prices fails to dampen the demand for energy services, whether in the domain of road passenger transportation or road freight transportation. In light of these conclusions, recommendations are proffered for the formulation of energy efficiency policies pertinent to road transportation.

关键词： road transportation direct energy rebound effect asymmetric price effects panel data model

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Conceptual study on incorporating user information into forecasting systems

Jiarui HAN, Qian YE, Zhongwei YAN, Meiyan JIAO, Jiangjiang XIA

《环境科学与工程前沿（英文）》 2011年第5卷第4期页码 533-542 doi: 10.1007/s11783-010-0246-6

摘要： The purpose of improving weather forecast is to enhance the accuracy in weather prediction. An ideal forecasting system would incorporate user-end information. In recent years, the meteorological community has begun to realize that while general improvements to the physical characteristics of weather forecasting systems are becoming asymptotically limited, the improvement from the user end still has potential. The weather forecasting system should include user interaction because user needs may change with different weather. A study was conducted on the conceptual forecasting system that included a dynamic, user-oriented interactive component. This research took advantage of the recently implemented TIGGE (THORPEX interactive grand global ensemble) project in China, a case study that was conducted to test the new forecasting system with reservoir managers in Linyi City, Shandong Province, a region rich in rivers and reservoirs in eastern China. A self-improving forecast system was developed involving user feedback throughout a flood season, changing thresholds for flood-inducing rainfall that were responsive to previous weather and hydrological conditions, and dynamic user-oriented assessments of the skill and uncertainty inherent in weather prediction. This paper discusses ideas for developing interactive, user-oriented forecast systems.

关键词： user-end information user-oriented interactive forecasting system TIGGE (THORPEX interactive grand global ensemble)

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An approach to locational marginal price based zonal congestion management in deregulated electricity

Md SARWAR,Anwar Shahzad SIDDIQUI

《能源前沿（英文）》 2016年第10卷第2期页码 240-248 doi: 10.1007/s11708-016-0404-z

摘要： Congestion of transmission line is a vital issue and its management pose a technical challenge in power system deregulation. Congestion occurs in deregulated electricity market when transmission capacity is not sufficient to simultaneously accommodate all constraints of power transmission through a line. Therefore, to manage congestion, a locational marginal price (LMP) based zonal congestion management approach in a deregulated electricity market has been proposed in this paper. As LMP is an economic indicator and its difference between two buses across a transmission line provides the measure of the degree of congestion, therefore, it is efficiently and reliably used in deregulated electricity market for congestion management. This paper utilizes the difference of LMP across a transmission line to categorize various congestion zones in the system. After the identification of congestion zones, distributed generation is optimally placed in most congestion sensitive zones using LMP difference in order to manage congestion. The performance of the proposed methodology has been tested on the IEEE 14-bus system and IEEE 57-bus system.

关键词： locational marginal price (LMP) distributed generation pool market deregulated electricity market congestion management

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美国NRC颠覆性技术持续预测系统浅析

张晓林

《中国工程科学》 2018年第20卷第6期页码 117-121 doi: 10.15302/J-SSCAE-2018.06.019

摘要：

美国国家研究委员会（NRC）发布的《颠覆性技术持续性预测》（Persistent Forecasting of Disruptive Technologies

关键词：颠覆性技术持续预测理想系统

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Forecasting industrial emissions: a monetary approach

Yang DONG, Yi LIU, Jining CHEN, Yebin DONG, Benliang QU

《环境科学与工程前沿（英文）》 2012年第6卷第5期页码 734-742 doi: 10.1007/s11783-012-0451-6

摘要： Forecasts of industrial emissions provide a basis for impact assessment and development planning. To date, most studies have assumed that industrial emissions are simply coupled to production value at a given stage of technical progress. It has been argued that the monetary method tends to overestimate pollution loads because it is highly influenced by market prices and fails to address spatial development schemes. This article develops a land use-based environmental performance index (L-EPI) that treats the industrial land areas as a dependent variable for pollution emissions. The basic assumption of the method is that at a planning level, industrial land use change can represent the change in industrial structure and production yield. This physical metric provides a connection between the state-of-the-art and potential impacts of future development and thus avoids the intrinsic pitfalls of the industrial Gross Domestic Product-based approach. Both methods were applied to examine future industrial emissions at the planning area of Dalian Municipality, North-west China, under a development scheme provided by the urban master plan. The results suggested that the L-EPI method is highly reliable and applicable for the estimation and explanation of the spatial variation associated with industrial emissions.

关键词： industrial emissions environmental performance index spatial planning industrial land use

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智能预报模式与水文中长期智能预报方法

陈守煜,郭瑜,王大刚

《中国工程科学》 2006年第8卷第7期页码 30-35

摘要：

建立了以模糊优选、BP神经网络及遗传算法有机结合的智能预报模式与方法。在应用该方法进行中长期水文智能预报时，首先选取训练样本的数量，根据预报因子与预报对象的相关关系得到相对隶属度矩阵;再将其作为BP神经网络输入值以训练连接权重；最后将得到的连接权重值用于预报检验。计算结果表明，智能预报模式与方法的运行速度、精度及稳定性都达到了实际应用的要求。

关键词：模糊优选 BP神经网络遗传算法智能预报模式中长期水文智能预报

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基于BP-AGA的非线性组合预测方法研究

王硕,张有富,金菊良

《中国工程科学》 2005年第7卷第4期页码 83-87

摘要：

运用神经网络和加速遗传算法建立非线性组合预测模型，在BP算法训练网络出现收敛速度缓慢时启用加速遗传算法（AGA）来优化网络参数，把AGA的优化结果作为BP算法的初始值，再用BP算法训练网络，如此交替运行BP算法和AGA以加快网络的收敛速度，同时改善局部最小问题。最后给出实例研究，结果表明，该方法能明显提高预测精度。

关键词：神经网络加速遗传算法非线性组合预测预测精度

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峰谷电价体制下东北输油管网日输油优化研究

崔慧,吴长春,吴江林,孙青峰

《中国工程科学》 2004年第6卷第8期页码 69-73

摘要：

东北原油长输管网是中国规模最大的地区性原油运输系统，就该管网基于峰谷电价体制下的运行现状，建立了线性规划数学模型，提出了日输油计划优化问题，并以铁秦线为例进行分析；初步揭示了峰谷电价体制下日输油计划方式的一些基本规律，表明在该体制下东北管网具有一定的节能降耗潜力。但该方式在一定程度上受到管道本身运行特性的约束，与热油管道相比它更适合于等温管道。

关键词：东北管网峰谷电价日输油优化