Period Of Prices Research Articles

Technology Focus: Production and Facilities (December 2018)

Technology Focus Creativity and innovation have long characterized production and facilities, and this year is no exception. Much of the work reported this past year was conducted during the recent period of low oil prices. The economic challenges of the oil industry clearly have provided a strong stimulus for even more creativity and innovation. The use of big data and analytics appeared in a number of papers with an emphasis on the use of artificial intelligence (AI) for building databases used to monitor the health of equipment and structure risk-based-inspection (RBI) strategies. Monitoring data inputs from thousands of sensors (paper OTC 28990) allows an AI application to predict an impending failure and notify operators by text or email when the incipient problem is detected so that proactive maintenance can be scheduled to avoid an unplanned shutdown or catastrophic failure. This strategy is being successfully applied to compressors but no doubt will be used to monitor other high-cost, critical service equipment as well (paper SPE 188803). Progress continues on the design and application of inflow-control devices (ICDs). Introduced only a few years ago, these devices are still in a rapid development stage for both design and application. Now, ICDs are applied successfully to improve the fluid-injection patterns for both steamfloods and waterfloods, the latter being described as a successful field application (paper SPE 189824). For steamfloods, passive and autonomous ICD designs were evaluated and their performance modeled using computational fluid dynamics (paper SPE 189721). The integration of subsurface modeling and surface-facility design by the development of a data-driven stochastic work flow (paper SPE 187462) demonstrated a means to reduce both subsurface and facility costs by reducing the biases that inevitably come into play during the generation of a field-development plan. Other innovative work was reported on field optimization, the prediction of asphaltene precipitation, and the integration of RBI with vibration-induced fatigue failure of installed piping systems. Interesting work not discussed here includes evaluating corrosion under severe conditions and the development of an oil-droplet-coalescing pump for use in water treatment. Recommended additional reading at OnePetro: www.onepetro.org. SPE 188803 Machines Performance Algorithmic Modeling for Anticipating Machines Health Using Real-Time Condition-Monitoring Data by W. Almadhoun, ADMA-OPCO, et al. SPE 189721 Evaluation of Inflow-Control-Device Performance Using Computational Fluid Dynamics by M. Miersma, University of Alberta, et al. SPE 187256 Production Optimization of Shenzi Field in the Deepwater Gulf of Mexico by P. Ashton, BHP, et al. SPE 190149 A Diagnostic Approach To Predict Asphaltene Deposition in Reservoir and Wellbore by Davud Davudov, University of Oklahoma, et al. OTC 28352 Integrating an RBI Approach for Vibration-Induced Fatigue Into a Mechanical-Integrity Program by Paul Crowther, Wood, et al.

Unified Algorithm for Demand-Side Appliance Commitment

Recent energy efficiency and conservation programs have created an unprecedented demand for home energy management systems (HEMS) in the residential sector aimed at reducing electricity consumption and saving on electricity bills. This paper gives a brief review of the basic algorithms found in the literature for HEMS that target optimum scheduling for home appliances participating in demand response (DR) programs. The working principles, as well as the pros and the cons, of these algorithms are explained and analyzed. Then, a unified algorithm to manage the hourly power consumption of home appliances on a daily basis is suggested using two scenarios. The first scenario aims to simultaneously achieve dual utility/customer benefits while avoiding the individual drawbacks of each presented algorithm. The second scenario aims to actively involve DR customers in making the optimum decision regarding their appliances in the face of their dynamic desires. The proposed algorithm is generic in the sense that it has the ability to achieve three different objectives for dual utility/customer benefits. Moreover, the paper takes into consideration a range of constraints, such as load priority, customer preferences, utility request, and electricity dynamic pricing scheme. The essential goal of this algorithm is not only to curtail or control the power consumption of appliances but to also shift it to a better price period based on different tariff rates. The results reflect the effectiveness of the proposed algorithm, which extends the previous findings in the literature by considering a wider range of limitations applied on HEMS.

Exchange market pressure and primary commodity – exporting emerging markets

ABSTRACTThis paper studies short-term sensitivity between exchange market pressure and various domestic and external factors in primary commodity-exporting emerging markets. The paper focuses on the top country-commodity groups in sugar, cereal, fuels, ores and coffee during the pre-peak and post-peak commodity price periods across floating and pegged exchange rate regimes, using the price of crude oil as a general benchmark. Employing a panel model and panel VAR analysis, the paper finds the heterogeneity of response patterns unique to country-commodity groups and exchange rate regimes. According to the results, in flexible regimes, volatility occurs via the foreign exchange market, interest rates, and domestic credit cycles, feeding into the social costs for structurally weaker economies. Hard exchange-rate pegs often result in a drain on international reserves as the terms of trade deteriorate following post-price peaks, leading to unpopular depreciation. These results accentuate concerns over uneven international trade patterns, an open economy’s short-term foreign exchange policy, and speculative capital flows. Such sensitivity has broad implications for macroeconomic balance and the sustainability of implied exchange rate targets in the presence of a foreign exchange constraint across emerging markets.

The impact of generics and generic reference pricing on candesartan and rosuvastatin utilisation, price and expenditure in South Africa

Background In the South African private sector context, generically similar products are grouped together and the reimbursement rate is set at the average price of the generically equivalent products. Very little evidence exists in low and middle-income countries with regards to the impact of this policy over time. Objectives To determine the impact of the introduction of generics and generic reference pricing on candesartan and rosuvastatin in the South African private health care sector in terms of medicine utilisation, medicine price and medicine expenditure. Setting South African private health sector. Method Medicine claims for candesartan and rosuvastatin was obtained from a Pharmacy Benefit Manager in South Africa. The claims covered a 48-month period from January 2012 to December 2015 and provided a pre- and post-reference price period for analysis. Medicine utilisation was measured as the number of Defined Daily Doses dispensed per 100,000 beneficiaries. Medicine price and expenditure was calculated as the average per Defined Daily Dose. Main outcome measure Medicine utilisation, price and expenditure. Results Candesartan experienced an average 7.0% year-on-year decline in utilisation and rosuvastatin a 5.0% increase. Medicine expenditure reduced by an additional 34.6% and 20.9% for candesartan and rosuvastatin respectively. The total savings was 54.8% for candesartan and 31.9% for rosuvastatin. Conclusion The introduction of generics and generic reference pricing did not have an impact on medicine utilisation, but reduced the price and expenditure of both candesartan and rosuvastatin.

Demand response-oriented dynamic modeling and operational optimization of membrane-based chlor-alkali plants

Power-intensive processes can potentially provide significant demand response (DR) services. Modeling such processes for demand response is not trivial as models must depict plant transient properties under highly dynamic operation while remaining computationally efficient. We develop a demand response-oriented model for an important power-intensive process i.e., chlor-alkali production using membrane cells, and demonstrate the provision of fast demand response by an industrial-size plant. Through an extensive simulation and optimization case study, we show that the fast modulation of the cell power demand is possible without adverse impact on cell concentration and temperature. Additionally, the cell temperature dynamics are found to restrict the demand response capacity of the plant and must to be explicitly accounted for to support dynamic cell operation in DR scenarios. Substantial load curtailment during peak electricity price periods can be achieved and the energy cost to the electrolysis plant can be reduced.

Impacts of Residential Energy Management on Reliability of Distribution Systems Considering a Customer Satisfaction Model

Residential energy management (REM) systems facilitate the application of residential demand response programs to manage the increasing demand of electricity in power systems. The load curtailment at high price periods and the load shift from high-price to low-price periods are the main results of REM implementation, which may improve the technical and economical operation of the distribution systems. Customers' satisfaction should be considered in the REM procedure to motivate the customers to respond to the received price signals. This paper proposes an optimization-based REM to minimize not only the customer's energy cost but also customer dissatisfaction, which is modeled as a function of load curtailment. In addition, the impact of broad application of REM in bus 6 of RBTS is studied on the reliability of a distribution system. To this end, two different methods for reliability evaluation are used to show the effect of load shift and load curtailment on the energy not supplied by the distribution system. The results verify the validity and effectiveness of the proposed REM approach and show the impact of application of REM programs with different penetration levels on the reliability of the distribution system.

Advanced control strategy for an energy storage system in a grid‐connected microgrid with renewable energy generation

The operating cost of the consumer can be reduced in an electricity market-based environment by shifting consumption to a lower price period. This study presents the design of an advanced control strategy to be embedded in a grid-connected microgrid with renewable and energy storage capability. The objectives of the control strategy are to control the charging and discharging rates of the energy storage system to reduce the end-user operating cost through arbitrage operation of the energy storage system and to reduce the power exchange between the main and microgrid. Instead of using a forecasting-based approach, the proposed methodology takes the difference between the available renewable generation and load, state-of-charge of energy storage system and electricity market price to determine the charging and discharging rates of the energy storage system in a rolling horizon. The proposed control strategy is compared with a self-adaptive energy storage system controller and mixed-integer linear programming with the same objectives. Empirical evidence shows that the proposed controller can achieve a lower operating cost and reduce the power exchange between the main and microgrid.

Incentive properties of coincident peak pricing

Coincident peak pricing is used in several electricity markets to recover the embedded cost of infrastructure, such as transmission. In this approach, measured consumption at the time of the peak is used to set charges for that pricing period or a subsequent period. If transmission costs are truly sunk, then such a recovery is unlikely to be efficient. However, in the context of growing peak demand, new additions must be built. We consider the incentive properties of coincident peak pricing when related investments are not considered to be sunk, finding that it can reproduce the incentive properties of an ideal time-varying price. We also consider several variations on this assumption.

Novel Soft-Constrained Distributed Strategy to meet high penetration trend of PEVs at homes

This paper shows that the Demand Response Program is not sufficient to solve the problem of high penetration level of Plug-in Electric Vehicles (PEVs), even when energy management systems are used in homes. In the presence of Time-varying electricity price, PEVs tend to charge during low price periods. The problem starts when the number of PEVs exceeds a certain threshold. A total load of all homes on a transformer may exceed its capacity and create high peak-demand during low-electricity price. To overcome this situation, we propose a novel Soft-Constrained Distributed Strategy. The novelty consists of defining a new distributed information exchange between Power Utility and end-users, new constraints are developed at home level taking into account the transformer and Distribution Network's technical limits, and a new optimization model is proposed to implement the strategy. A case study is conducted using data provided by Hydro-Quebec. Simulations and comparative results show the validity of our approach. The proposed strategy reduces the peak–demand, energy loss, depreciation cost, transformer's Loss Of Life, and voltage deviations. Lastly, our study shows that it is not necessary for the power utility (e.g. Hydro-Quebec) to upgrade all Distribution Transformers on the network and the infrastructure during the increasing penetration of PEVs.

FLUCTUACIONES ESTACIONALES Y CÍCLICAS DE LOS PRECIOS DEL AZÚCAR EN MÉXICO

El análisis de las fluctuaciones del precio del azúcar es importante porque en periodos de bajos precios disminuye el ingreso del productor. Con el objetivo de hacer recomendaciones que permitan enfrentar la volatilidad de precios del azúcar estándar, se realizó un análisis para determinar los componentes estacionales y cíclicos de los precios al mayoreo del azúcar en el periodo de octubre de 2004 a septiembre de 2016, en las centrales de abasto de la Ciudad de México, Guadalajara y Monterrey. El conocimiento de los componentes del precio (tendencia, estacional, cíclico e irregular) es importante porque permite seleccionar la mejor política para enfrentar las fluctuaciones. Los resultados indican la existencia de un fuerte componente estacional con diferencias máximas en periodos de precios altos de 1.83, 1.65 y 1.78 $1 kg-1, entre los precios reales y desestacionalizados del azúcar estándar en septiembre de 2009 en las centrales de abasto de la Ciudad de México, Guadalajara y Monterrey, respectivamente. Las diferencias mínimas entre ambos precios en meses de precios bajos fueron de -0.95, -0.88 y -0.94 $ kg-1 en marzo de 2010 en las mismas centrales de abasto. También existe un fuerte componente cíclico, ya que en el periodo analizado se detectaron cuatro ciclos con una duración promedio de 19 meses. Por los efectos negativos que una volatilidad extrema pueda tener sobre el ingreso del productor serían recomendables políticas de control de la oferta como un envío constante de azúcar al mercado y la planeación de la superficie cosechada de caña de azúcar (Saccharum officinarum L.) a través del tiempo.

Healthy Nutrition and Dietary Considerations for the Workplace

Healthy Nutrition and Dietary Considerations for the Workplace

Does investor attention to energy stocks exhibit power law?

In this article, we explore the dynamics of memory and the correlation structure in investor attention. Information on whether a time series is a pure noise or has a short or long range memory is important for predictive modeling of the series and analyzing its relationship with other variables. Existing studies on time series memory of stock variables are limited to price, volume, returns and conditional variance of returns. We carry out an in-depth analysis to understand the dependence structure of stock's investor attention time series (IATS) for energy market. In this process, we first investigate the existence of correlated dependence in IATS and analyze its dynamics using detrended fluctuation analysis. Further, we check how this dependence changes a) with frequency of sampled data b) during volatility clustering periods of price and volume of underlying stocks. Finally, we perfom detrended cross correlation analysis on local and global IATS to find any cross correlation dependence between the two. We use relative search query volume in Google to quantify IATS for a particular stock and analyze top 20 energy companies based on their market capitalization. The obtained detrended fluctuation coefficients for stock's IATS differ significantly from 0.5 indicating the existence of memory in the series. The dynamics of this memory exhibits persistent and mean reverting behavior. We also observed a reasonably high positive cross correlation dependence between local and global IATS. Finally we find that volatility clustering has little effect on dependence structure of investor attention time series. We also include a few examples to illustrate practical implications of these results.

The Effects of Climate Change on GDP by Country and the Global Economic Gains From Complying With the Paris Climate Accord

Computable general equilibrium (CGE) models are a standard tool for policy analysis and forecasts of economic growth. Unfortunately, due to computational constraints, many CGE models are dimensionally small, aggregating countries into an often limited set of regions or using assumptions such as static price‐level expectations, where next period's price is conditional only on current or past prices. This is a concern for climate change modeling, since the effects of global warming by country, in a fully disaggregated and global trade model, are needed, and the known future effects of global warming should be included in forward‐looking forecasts for prices and profitability. This work extends a large dimensional intertemporal CGE trade model to account for the various effects of global warming (e.g., loss in agricultural productivity, sea level rise, and health effects) on Gross Domestic Product (GDP) growth and levels for 139 countries, by decade and over the long term, where producers look forward and adjust price expectations and capital stocks to account for future climate effects. The potential economic gains from complying with the Paris Accord are also estimated, showing that even with a limited set of possible damages from global warming, these gains are substantial. For example, with the comparative case of Representative Concentration Pathway 8.5 (4°C), the global gains from complying with the 2°C target (Representative Concentration Pathway 4.5) are approximately US$17,489 billion per year in the long run (year 2100). The relative damages from not complying to Sub‐Sahara Africa, India, and Southeast Asia, across all temperature ranges, are especially severe.

Design, Operation, Modeling and Grid Integration of Power-to-Gas Bioelectrochemical Systems

This paper deals with the design, operation, modeling, and grid integration of bioelectrochemical systems (BES) for power-to-gas application, through an electromethanogenesis process. The paper objective is to show that BES-based power-to-gas energy storage is feasible on a large scale, showing a first approximation that goes from the BES design and operation to the electrical grid integration. It is the first study attempting to cover all aspects of a BES-based power-to-gas technology, on authors’ knowledge. Designed BES reactors were based on a modular architecture, suitable for a future scaling-up. They were operated in steady state for eight months, and continuously monitored in terms of power consumption, water treatment, and biomethane production, in order to obtain data for the following modeling activity. A black box linear model of the BES was computed by using least-square methods, and validated through comparison with collected experimental data. Afterwards, a BES stack was simulated through several series and parallel connections of reactors, in order to obtain higher power consumption and test the grid integration of a real application system. The renewable energy surplus and energy price variability were evaluated for the grid integration of the BES stack. The BES stack was then simulated as energy storage system during low energy price periods, and tested experimentally with a real time system.

Reducing residential mortgage default: Should policy act before or after home purchases?

We examine two possible approaches to reducing residential mortgage default using a dynamic model of heterogeneous infinitely-lived agents acting optimally subject to uninsurable idiosyncratic earnings shocks and systemic house price shocks. We find higher down payments are very effective in minimizing residential mortgage foreclosures, even in periods of house price declines and recessions. In contrast, the length of the credit exclusionary period for people who experience bankruptcy or foreclosure has a much smaller impact on mortgage defaults. Thus, it is much more effective to prevent mortgage default before the mortgage closes than to pressure homeowners not to default once they are in financial trouble. This also suggests a major aspect of credit scores and credit policy is non-productive and punitive, harming people in return for little societal gain.

Economic value of underground natural gas storage for the Brazilian power sector

This paper aims at assessing the main obstacles to the development of underground natural gas storage (UGS) in Brazil and at identifying the conditions required for the feasibility of UGS projects in the country. The paper estimates the economic value of UGS facilities for the power sector in Brazil, considering the specificities of the Brazilian power and gas sectors. It is shown that the Brazilian gas demand does not have a seasonal characteristic; instead, the demand is volatile of a random nature associated with the demand from thermal power plants, which are complementary to hydropower generation. This paper has proved that there is an important economic value associated with the storage of gas in periods of low power prices and its consumption in period of high power prices. Finally, this paper argues that it is essential to seek mechanisms to include the economic value of UGS for the power sector into the UGS regulation and market design, as well as to explore the possibility of making gas storage a resource for the power sector operation.

Optimal Penetration of Home Energy Management Systems in Distribution Networks Considering Transformer Aging

In the near future, home energy management systems (HEMSs) will become common in reaction to time-varying pricing, and residential electricity customers’ striving to minimize their energy costs. However, if many residences connected to a common pole-top transformer are all optimizing their electricity consumption based on the same electricity tariff, their aggregated demand may result in large, short-lived peaks. Traditional demand peaks would be reduced since the electricity prices are high, but early morning (low price periods) demand peaks would be increased. Since high demand increases transformer temperatures and degrades their insulation, managing these peaks extends transformer life and reduces network upkeep costs. This paper presents an approach for managing the rollout of HEMSs on a distribution feeder. Several heuristic strategies for incentivizing customer adoption of HEMSs are investigated and compared to the optimal adoption strategy. A case study using representative data is conducted and the results show that transformer aging costs can be reduced by an order of magnitude by managing adoption rates and strategies. When incentivization costs are included, the optimal HEMS penetration and net benefit are reduced, but a value proposition still exists for targeted HEMS adoption.

Analisis Pengaruh Tingkat Suku Bunga SBI, Kurs Rupiah, Harga Emas Dunia, Harga Minyak Dunia dan Indeks Hang Seng Terhadap Indeks Harga Saham Gabungan (Studi Kasus pada IHSG di Bursa Efek Indonesia Periode 2005-2012)


 
 
 Capital market is macroeconomic indicator, which is very important for a country. This study is intended to test the effect of SBI interest rate, rate of exchange of Rupiah against US Dollar, world gold price, oil price and Hangseng index on Indonesian Composite Index. Samples taken in this research are SBI interest rate, rate of exchange of rupiah against US Dollar, world gold price, oil price, hangseng index and Indonesian Composite Index period of 2005-2012. Data analysis method use is multiple linear regression analysis, classical assumption test, correlation analysis of Pearson, determination coefficient, and hypothetical test accounted uses an application of SPSS 17.0 for windows. The result shows that variable the world gold price and hangseng index partially has found that there is significant influence toward IHSG, while in a whole SBI interest rate, rate of exchange of Rupiah against US Dollar, world gold price, oil price and hangseng index have significant effect to IHSG.
 
 

Does the Introduction of One Derivative Affect Another Derivative? The Effect of Credit Default Swaps Trading on Equity Options

A significant event for equity options since the 1987 stock market crash is the rise of credit default swaps (CDS). We show that equity options of CDS-referenced firms are more expensive than those without CDS. Instrumental variable estimation and other analysis suggest that the CDS effect on option pricing is likely causal. Transactions data reveal that brokers and dealers’ demand is higher for options linked to CDS. The effect of CDS trading on option pricing is more pronounced when financial institutions have less capital or higher leverage. Our findings are consistent with theories that intermediation capacity constraints affect derivatives pricing.

Contracting and renegotiating with a loss-averse private firm in BOT road projects

In BOT road project, the government offers a firm an ex ante contract, which specifies toll price and concession period based on the forecasted demand. When the demand states are observed in the operation period, the government may request renegotiation to adapt the initial contract to the realized demand state. By considering the loss aversion behavior of the private firm, this paper shows that renegotiation takes place only if the private firm’s extent of loss aversion is sufficiently small. However, in what direction the government adjusts toll price and concession period depends on the combined effects of initial price, demand level, and demand uncertainty in each demand state. This paper has further investigated the optimal initial contract. We find that if one demand state realizes with a sufficiently large probability, then the optimal initial contract is renegotiation-proof in this demand state while inducing renegotiation in other demand states; if all demand states realize with almost equal probabilities, whether the optimal initial contract prevents or induces renegotiations in all demand states depends on the private firm’s extent of loss aversion. This paper makes two major contributions to the literature. First, we apply loss aversion to the context of renegotiation in BOT road projects and show that renegotiation is costly. Second, we consider the optimal initial contract in anticipation of ex post renegotiation and show that the government should trade off between ex ante social welfare and ex post psychological loss. To obtain more insights and to strengthen our model results, we have reexamined the optimal renegotiation and initial contracts under some relaxed assumptions.