Price Scenarios Research Articles

A hybrid electricity price scenario generation method for stochastic virtual bidding in the electricity market

Stochastic optimization can be used to generate optimal bidding strategies for virtual bidders in which the uncertain electricity prices are represented by using scenarios. This paper proposes a hybrid scenario generation method for electricity price using a seasonal autoregressive integrated moving average (SARIMA) model and historical data. The electricity price spikes are first identified by using an outlier detection method. Then, the historical data are decomposed into base and spike components. Next, the base and spike component scenarios are generated by using the SARIMA- and historical data-based methods, respectively. Finally, the electricity price scenarios are obtained by combining the base and spike component scenarios. Case studies are carried out for a virtual bidder in the PJM electricity market to validate the proposed method. The optimal bidding strategies of the virtual bidder are generated by solving a stochastic optimization problem using the electricity price scenarios generated by the proposed method, the SARIMA method, and a historical data-based method, respectively. Case study results show that the proposed method is better than the SARIMA method in preserving statistical properties of the electricity price in the generated scenarios and is better than the historical data-based method in predicting the future trend of the electricity price and, therefore, can help the virtual bidder earn more profit in the electricity market.

Towards Improved Cost Evaluation of Carbon Capture, Transport and Storage From Industry

This paper briefly summarises the development of improved guidelines for cost evaluation of carbon dioxide capture, transport and storage (CCS) from industrial applications [1] building on previous work in the field. It discusses key challenges and factors that have a large impact on the results of cost evaluations but are often overlooked or insufficiently addressed. These include cost metrics (especially in the context of industrial plants with multiple output products), energy supply aspects, retrofitting costs, CO2 transport and storage, and maturity of the capture technology. Where possible, examples are given to demonstrate their quantitative impact and show how costs may vary widely on a case-by-case basis. Recommendations are given to consider different possible heat and power supply strategies, as well as future energy and carbon price scenarios, in order to better understand CCS costs under various conditions. Since retrofitting CCS is especially relevant for industrial facilities, further recommendations are made on how to better account for the key elements that constitute retrofitting costs. Furthermore, instead of using a fixed unit cost for CO2 transport and storage, cost estimates should at least consider the CO2 flowrate, transport mode, transport distance and type of storage, to obtain more realistic cost estimates. Recommendations are also given on factors to consider when assessing the technological maturity level of CCS in various industrial applications, which is important when assessing cost contingencies and uncertainties. Lastly, we urge techno-economic analysis practitioners to clearly report all major assumptions and methods, as well as comprehensively examine the impact of uncertainties on their cost estimates.

Planting method and seeding rate effect on whole and partitioned soybean yield

AbstractSoybean [Glycine max (L.) Merr.] seeding rate is one of the most important management decisions. Although seeding rate effect on yield is one of the most examined management practices, its interactive effect with seeding method is often ignored. Two field trials were conducted in Arlington, WI, between 2019 and 2020. In the first trial, the interactive effect of seeding rate with seeding method (precision vs. random) and two cultivars was examined. Precision method used a vacuum seed meter and soybean seed plate, whereas the random method used a cone seed distribution system. The second trial was hand planted to mimic precision planting (exact seeding rates and within row spacings), and the effect of seeding rate on total and partitioned (branch and stem) soybean yield was assessed. The effect of seeding rate on yield varied due to seeding method and cultivar. Precision seeding increased yield for the lowest seeding rate (99,000 seeds ha–1) and was associated with increased canopy closure and more uniform within‐row plant‐to‐plant spacing compared with the random seeding method. When soybean was hand planted (precision planting), total yield was greater only in the highest seeding rate. In the lowest rates, branch‐ and stem‐derived yields were similar. Overall results show that precision planting can mitigate yield loss at suboptimal seeding rates. Results from these studies reveal the complexity of seeding rate optimization for maximizing soybean yield and resulting profit and highlight the need for farm‐specific economic analysis for different management‐related costs and soybean price scenarios.

Model-based production optimization under geological and economic uncertainties using multi-objective particle swarm method

Optimization of the water-flooding process in the oilfields is inherently subject to several uncertainties arising from the imperfect reservoir subsurface model and inadequate data. On the other hand, the uncertainty of economic conditions due to oil price fluctuations puts the decision-making process at risk. It is essential to handle optimization problems under both geological and economic uncertainties. In this study, a Pareto-based Multi-Objective Particle Swarm Optimization (MOPSO) method has been utilized to maximize the short-term and long-term production goals, robust to uncertainties. Some modifications, including applying a variable in the procedure of leader determination, namely crowding distance, a corrected archive controller, and a changing boundary exploration, are performed on the MOPSO algorithm. These corrections led to a complete Pareto front with enough diversity on the investigated model, covering the entire solution space. Net Present Value (NPV) is considered the first goal that represents the long-term gains, while a highly discounted NPV (with a discount rate of 25%) has been considered short-term gains since economic uncertainty risk grows with time. The proposed optimization method has been used to optimize water flooding on the Egg benchmark model. Geological uncertainty is represented with ensembles, including 100 model realizations. The k-means clustering method is utilized to reduce the realizations to 10 to reduce the computing cost. The Pareto front is obtained from Robust Optimization (RO) by maximizing average NPV over the ensembles, as the conservative production plan. Results show that optimization over the ensemble of a reduced number of realizations by the k-means technique is consistent with all realizations’ ensembles results, comparing their cumulative density functions. Furthermore, 10 oil price functions have been considered to form the economic uncertainty space. When SNPV and LNPV are optimized, considering uncertainty in oil price scenarios, the Pareto front’s production scenarios are robust to oil price fluctuations. Using the robust Pareto front of LNPV versus SNPV in both cases, one can optimize production strategy conservatively and update it according to the current reservoir and economic conditions. This approach can help a decision-maker to handle unexpected situations in reservoir management.

Optimal offering strategy of virtual power plant with hybrid renewable ocean energy portfolio

This paper proposes a hybrid ocean energy system to form a virtual power plant (VPP) for participating in electricity markets in order to promote the renewable ocean energy utilization and accommodation. In the proposed system, solar thermal energy is integrated with the closed-cycle ocean thermal energy conversion (OTEC) to boost the temperature difference between surface and deep seawater for efficiency and flexibility improvements, and the thermodynamic effects of seawater mass flow rates on the output of solar-boosted OTEC (SOTEC) are exploited for deploying SOTEC as a renewable dispatchable unit. An optimal tidal-storage operation model is also developed to make use of the subsea pumped storage (SPS) with hydrostatic pressures at ocean depth for mitigating the intermittent tidal range energy in order to make the arbitrage in the electricity market. Furthermore, a two-stage coordinated scheduling strategy is presented to optimally control seawater mass flow rates of SOTEC and hydraulic reversible pump-turbines of SPS for enhancing the daily VPP profit. Comparative studies have been investigated to confirm the superiority of the developed methodology in various renewable ocean energy and electricity market price scenarios.

Managing Pharmaceutical Expenditures: Estimating the Effect of Internal Reference Pricing for Three Pharmacological Categories

Background: Internal reference pricing (IRP) is one of the pharmaceutical pricing approaches, which is widely favored by health policymakers in different countries as a cost-containment tool for managing medicine expenditure. Evidence related to the implementation of this method confirms its usefulness in reducing pharmaceutical costs. Accordingly, the purpose of this study was to calculate potential changes in pharmaceutical expenditure using the IRP method for products belonging to three pharmaceutical categories in the pharmaceutical system of Iran. Methods: This routine data study assessed the potential effect of IRP in three pharmaceutical categories including statins, non-steroidal anti-inflammatory drugs, and proton pump inhibitors (PPIs). Two scenarios for reference groups (levels 4 and 5 of the ATC code) and four scenarios for the reference price (i.e., the minimum, median, mean, and the mean of three minimum prices in the reference group) were considered in this regard, and the price and sales data source was the report published by the Iranian Food and Drug Administration. Then, cost changes were calculated with each hypothetical scenario. It was assumed that other intervening factors remain unchanged, including consumers and prescribers’ behavior. Results: Based on the results, the two largest potential saving effects belonged to the minimum price scenario and the mean of the scenario of the three minimum prices, respectively. However, the results showed that the consequence of using a price scenario other than the minimum price as the reference price is highly related to the details of the distribution of prices in the related reference group. In addition, appropriate decisions regarding outlier products (e.g., imported products) might have extremely important effects on the result, especially for the mean price scenario. The minimum price scenario concomitant with a premium for superior products can also be considered, but part of it is outside the scope of this study and requires independent research. Conclusion: Thus if an appropriate scenario is selected for the reference price and group, the IRP method has the potential to reduce the costs of medicines. Therefore, pharmaceutical policymakers must pay enough attention to the details of planning this system and the needed procedure for updating the details of this system.

Optimal Virtual Power Plant Management for Multiple Grid Support Services

A hierarchical control architecture is proposed for the optimal day-ahead commitment of multiple grid support services within a virtual power plant (VPP). The day-ahead optimization considers pricing and cost data to determine the commitment schedule, and a robust Model Predictive Control (MPC) approach is included to minimize the unbalance fees during real-time operations. The multi-level control has been demonstrated experimentally using a hybrid test system, where the VPP is formed of a commercial 240 kW, 180 kWh battery energy storage system (BESS), while the additional assets are modelled in a real-time digital simulator (RTDS). Two case studies are analyzed: the first assumes a purely-electrical VPP, with a single connection to the public network; the second involves a multi-energy approach, with the introduction of a gas-supplied Combined Heat and Power unit (CHP). Both winter and summer price scenarios are tested. The results show the superiority of the multiple-service operation compared to providing a single grid support service. For example, the net revenue is increased by 30% (winter) and 7% (summer) when compared to just frequency regulation, and by +99% (winter) and 30% (summer) when compared to only energy arbitrage.

Development of a framework for the assessment of the market penetration of novel in situ bitumen extraction technologies

Greenhouse gas (GHG) mitigation opportunities from emerging in situ mining technologies in oil sands production can play a role in reducing global warming. There is limited research on quantitative assessments of the penetration of emerging oil sands technology in the energy sector. This study addresses this gap by developing a novel framework (MAPL-OET) to assess the market penetration of emerging oil sands extraction technologies. The framework is robust and data-intensive as it combines diffusion models, econometrics models, cost models, and energy-economy equilibrium models. The combined model evaluates the adoption of new energy technologies resulting from carbon price measures and other economic factors, as well as the GHG mitigation potential in the oil sands sector. The accumulated GHG mitigation potential from high carbon and BAU scenarios (i.e., a carbon price of $30/tonne of CO2 in 2030, increasing at a rate of 4%/yr to reach about $105/tonne of CO2) was estimated to be 192.8 Mt of CO2 eq between 2018 and 2050. New extraction technologies also improve average energy intensities by 1.3% annually in the high carbon price scenarios. The developed new framework can help public and private organizations to achieve energy or environmental targets.

The future of coal supply in China based on non-fossil energy development and carbon price strategies

To realize China’s low-carbon development, coal needs to be produced and consumed in a clean and efficient way. In this paper, a multi-regional coal supply model is developed to gain insights into China’s coal supply system up to 2050. Regional disparity, coal classification, and the development of clean coal technologies are specified in the model. Based on MESSAGEix, this model takes full consideration of coal mining, preparation, transformation, and transportation processes. Moreover, the effects of non-fossil energy development and carbon price are discussed. With the above framework, the future of China’s coal supply system is optimized. Results indicate that: 1) China’s national raw coal production will peak in 2030 under the business-as-usual scenario, while it has already peaked under the GREEN and carbon price scenarios, 2) The amount of coal used in final consumption and transformed into coke decreases, while coal transformed into liquids and SNG increases from 11 Mt in 2015 to 221 Mt in 2050 under the business-as-usual scenario, 3) both non-fossil fuel development and carbon price strategies have a positive effect on coal supply regulation and coal-related GHG emission reduction, 4) carbon price could facilitate the adoption of CCS technology and can effectively reduce coal-related GHG emissions.

Can Road Toll Convince Car Travelers to Adjust Their Departure Times? Accounting for the Effect of Choice Behavior under Long and Short Holidays

The adjustment of road toll is an important measure that can alleviate road traffic congestion by convincing car travelers to travel during off-peak times. In order to reduce congestion on the expressway on the first day of a holiday, factors that affect the departure times of holiday travelers must be comprehensively understood to determine the best strategy to persuade car travelers to avoid peak travel times. This paper takes holiday car travelers as the research object and explores the characteristics and rules of departure time choice behavior for different holiday lengths. Based on Utility Maximization Theory, a multinomial logit (MNL) model of departure time choice for a three-day short holiday and a seven-day long holiday was established. Model calibration and elastic analysis were carried out using Revealed Preference/Stated Preference (RP/SP) survey data. Additionally, the influence of the highway toll policy on departure times for long and short holidays was analyzed. The results show that the rate of first-day departures is much higher than that of other departure times for both short and long vacations under the current policy of free holiday passage on highways. Factors such as trip duration, size of the tourist group, the number of visits, travel range, travel time, monthly income, occupation, age and road toll have a significant influence on the departure time decisions of holiday car travelers, and the effect and degree of influence are markedly different for different holiday lengths. The effects of tolls for each departure time and different pricing scenarios on the choice behavior of travelers are different between long and short holidays. Furthermore, the effectiveness of the road toll policy also varies for travelers with different travel distances. This study can provide useful information for the guidance of holiday travelers, the management of holiday tolls on expressways and the formulation of holiday leave time.

Empowering Farmers through Future Price Information: A Case Study of Price Forecasting of Brinjal in Eastern Uttar Pradesh

The study developed ARIMA forecasting model for brinjal prices for the markets of Eastern Uttar Pradesh. It was observed that the ARIMA (1,0,1) with non-zero mean was suitable for both Lucknow and Allahabad markets. ARIMA (2,0,0) (0,1,0) (52), ARIMA (1,1,0) (1,1,0) (52), ARIMA (1,1,2), ARIMA (2,0,0) (1,0,0) (52), ARIMA (3,1,1) were suitable for Delhi, Varanasi, Kolkata, Gorakhpur, and Kanpur markets, respectively, based on lowest AIC values. The farmers and other supply chain actors of Eastern Uttar Pradesh could plan their production and marketing activities looking into the price scenario projected for major markets in the study. The highest price of brinjal was likely to prevail in the Kolkata market. To exploit distant markets, the farmers need to organize themselves into groups to exploit economies of scale.

The economic costs of planting, preserving, and managing the world\u2019s forests to mitigate climate change

Forests are critical for stabilizing our climate, but costs of mitigation over space, time, and stakeholder group remain uncertain. Using the Global Timber Model, we project mitigation potential and costs for four abatement activities across 16 regions for carbon price scenarios of $5–$100/tCO2. We project 0.6–6.0 GtCO2 yr−1 in global mitigation by 2055 at costs of 2–393 billion USD yr−1, with avoided tropical deforestation comprising 30–54% of total mitigation. Higher prices incentivize larger mitigation proportions via rotation and forest management activities in temperate and boreal biomes. Forest area increases 415–875 Mha relative to the baseline by 2055 at prices $35–$100/tCO2, with intensive plantations comprising <7% of this increase. Mitigation costs borne by private land managers comprise less than one-quarter of total costs. For forests to contribute ~10% of mitigation needed to limit global warming to 1.5 °C, carbon prices will need to reach $281/tCO2 in 2055.

Cost Optimization of a Zero-Emission Office Building

The cost-effectiveness of energy efficiency measures meant to achieve a zero-emission office building is investigated and compared to business as usual energy efficiency measures. The laboratory for zero emission buildings, the ZEB Lab, located in Trondheim, Norway, is an office building designed and built to compensate its lifecycle emissions with the use of a large array of building-integrated photovoltaic panels, pursuing a zero-emissions ambition level. Three design alternatives are investigated by downgrading the building insulation level to the values recommended by the currently enforced Norwegian building code, the byggteknisk forskrift TEK17. A sensitivity analysis of the variation of the installed area of the photovoltaic panels is performed to evaluate if smaller areas give better cost performances. Net present values are calculated by using three scenarios of future increase of electricity price for a time horizon of 20 years. Results show that business as usual solutions give higher net present values. Optimized areas of the photovoltaic panels further increase the net present values of the business as usual solutions in the highest electricity price scenario. The zero-emission ambition level shows a higher net present value than that of the business as usual solutions for a time horizon of at least 36 years.

Theoretical comparison between post-combustion carbon capture technology and the use of blue and green H2 in existing natural gas combined cycles as CO2 mitigation strategies: A study under the context of mexican clean energy regulation

The objective of this work is to compare the theoretical implementation of three strategies for reducing CO2 emissions in existing natural gas combined cycles (NGCC) under the context of the Mexican clean energy regulation, namely: NGCC with post-combustion carbon capture plant (CCS); NGCC fueled with blends of natural gas and blue H2 (bH2) or green H2 (gH2). These options were analysed from the point of view of the end users in meeting the National goals in clean electricity generation during the period of 2020–2050. A techno-economic analysis was performed by considering different variables, such as clean energy certificate price, fuel costs, capital expenditure, operating cost and capacity factor plant. In general, the CCS shows a better economic performance than bH2 and gH2 cases for reducing carbon emissions in existing NGCCs. In a low natural gas price scenario ($1/MMBTU), the gH2 case is economically attractive from gH2 cost equal to or less than $ 0.9 per kg. Finally, it is found that under the current Mexican regulatory framework is not possible the incorporation of any of the technologies mentioned above, in which case, this regulation needs to be deeply amended in order to define new technical and administrative criteria for promoting the market entry of these technologies in the country.

Cost-effectiveness analysis of adding ramucirumab to the first-line erlotinib treatment for untreated EGFR-mutated metastatic non-small cell lung cancer in China

ObjectiveTo investigate the cost-effectiveness of ramucirumab plus erlotinib compared with placebo plus erlotinib in the first-line setting for patients with EGFR-mutated metastatic non-small cell lung cancer (mNSCLC) from the Chinese...

Vaccine Prices: A Systematic Review of Literature.

Vaccines are among the most vital interventions to control and reduce the morbidity and mortality worldwide. In accessing vaccines, pricing is usually the single most important deciding element. However, there is a scarcity of the literature on the vaccines pricing. The current study aims to review vaccine prices from the published literature and to evaluate factors that impact the pricing of vaccines. The literature (from 2015–2020) was reviewed to identify the original research articles. Systematic searches were conducted across the five databases including, Google Scholar, PubMed, Science Direct, Scopus and Springer Link. Literature search yielded 23,626 articles, of which 7351 were screened and 7310 articles were excluded based on title and abstracts relevance. The 41 studies were selected for full text review and 4 studies were found to meet the inclusion criteria. The included studies discussed vaccine prices for childhood vaccines, for Human Papilloma Virus (HPV) in US, China and in Europe. One study detailed the various scenarios of the HPV vaccines pricing. It was found that recently introduced vaccines have higher prices owing to the involvement of technology and research for their manufacture. However, prices tended to decrease over some maturation in price and by the involvement of Global Alliance for Vaccine Initiative (GAVI) and other allies. The prices of vaccines in China were much lower than the other high-income countries and the prices offered through United Nations Children’s Fund (UNICEF), mainly due to the large scale of demand in China. The affordable prices of vaccines were related to delicate procedures involving multiple stakeholders and a shorter duration of contract. This review systematically evaluated the literature and identified key factors that could impact vaccines pricing. The prices were higher for the newly introduced vaccines into the market. However, with the price maturation, there was a decline in the pricing and affordable prices could be achieved through tender pricing and involvement of GAVI and other allies.

A Spatially Explicit Decision Support System for Assessment of Tree Stump Harvest Using Biodiversity and Economic Criteria

Stump harvesting is predicted to increase with future increasing demands for renewable energy. This may affect deadwood affiliate biodiversity negatively, given that stumps constitute a large proportion of the coarse deadwood in young managed forests. Spatial decision support for evaluating the integrated effects on biodiversity and production of stump harvesting is needed. We developed a spatially explicit decision support system (called MapStump-DSS), for assessment of tree stump harvesting using biodiversity and economic criteria together with different scenarios for biodiversity conservation and bioenergy market prices. Two novel key aspects of the MAPStump-DSS is that it (1) merges and utilizes georeferenced stump-level data (e.g., tree species and diameter) directly from the harvester with stand data that are increasingly available to forest managers and (2) is flexible toward incorporating both quantitative and qualitative criteria based on emerging knowledge (here biodiversity criteria) or underlying societal drivers and end-user preferences. We tested the MAPStump-DSS on a 45 ha study forest, utilizing harvester data on characteristics and geographical positions for &gt;26,000 stumps. The MAPStump-DSS produced relevant spatially explicit information on the biodiversity and economic values of individual stumps, where amounts of “conflict stumps” (with both high biodiversity and economical value) increased with bioenergy price levels and strengthened biodiversity conservation measures. The MAPStump-DSS can be applied in practice for any forest site, allowing the user to examine the spatial distribution of stumps and to obtain summaries for whole forest stands. Information depicted by the MAPStump-DSS includes amounts, characteristics, biodiversity values and costs of stumps in relation to different scenarios, which also allow the user to explore and optimize biodiversity and economy trade-offs prior to stump harvest.

A stochastic decentralized model for the privately interactive operation of a multi-carrier energy system

Multi-carrier energy systems have received wide attentions due their flexibility and sustainable characteristics. Although these systems show significant efficiency in providing and consuming energy, the performance of the whole system can be degraded owing to uncertainties arising from different sources. This paper presents a stochastic decentralized model for considering the uncertainties of a system including different types of thermal and electrical private loads using a multi-agent framework. In other words, agents have private ownership and seek for social welfare as well as optimized personal profits. In the proposed model, the gradient projection method is used to implement a fully-decentralize energy trading model. Also, various stochastic scenarios of solar irradiance, prices, and loads are considered using the fast-forward selection algorithm to take into account the uncertainties. Then, to assess the proposed stochastic multi-agent model, “AnyLogic” is used for conducting the simulation studies. The numerical results show that the clearing price is directly affected by the renewable agent without any supervisory control. Moreover, the total operating cost of the considered multi-carrier energy system decreases by ∼7 % considering these uncertainties compared with a deterministic one. However, social welfare declines due to the intrinsically beneficial behavior in private cooperation.

Evaluating Cost Trade-Offs between Hydropower and Fish Passage Mitigation

To promote the sustainable management of hydropower, decision makers require information about cost trade-offs between the restoration of fish passage and hydropower production. We provide a systematic overview of the construction, operational, monitoring, and power loss costs associated with upstream and downstream fish passage measures in the European context. When comparing the total costs of upstream measures across different electricity price scenarios, nature-like solutions (67–88 EUR/kW) tend to cost less than technical solutions (201–287 EUR/kW) on average. Furthermore, nature-like fish passes incur fewer power losses and provide habitat in addition to facilitating fish passage, which presents a strong argument for supporting their development. When evaluating different cost categories of fish passage measures across different electricity price scenarios, construction (45–87%) accounts for the largest share compared to operation (0–1.2%) and power losses (11–54%). However, under a high electricity price scenario, power losses exceed construction costs for technical fish passes. Finally, there tends to be limited information on operational, power loss, and monitoring costs associated with passage measures. Thus, we recommend that policy makers standardize monitoring and reporting of hydraulic, structural, and biological parameters as well as costs in a more detailed manner.

Towards the development of a hotel-based e-bike rental service: Results from a stated preference survey and techno-economic analysis

Holiday cycling refers to the occasional use of bicycle during holidays as an alternative mode of transportation for exploring a destination, comprising a promising line of business for rental services of both conventional and electric bicycles (e-bikes), not only in countries with well-established cycling culture, but also in other tourist destinations. This paper advances the notion that a hotel-based e-bike rental service significantly contributes to the guests’ perception on the environmental quality and friendliness of the hotel, particularly if the e-bikes are powered by renewable energy sources, as a tourism product offering in the context of sustainable mobility. To that end, the present work employs a stated preference survey among hotel guests in the city of Mons, Belgium, to capture and analyze the user profile characteristics and preferences. Based on the survey results, it simulates two alternative implementations of the e-bike charging station with a well-established energy systems analysis tool and evaluates the techno-economic feasibility of the proposed service under different usage and pricing scenarios. The findings of this work show that all scenarios lead to positive internal rate of return and return on investment, rendering the proposed e-bike rental service a promising business venture.