Contract Scenarios Research Articles

RETRACTION: Machine learning based load prediction in smart‐grid under different contract scenario

AbstractRETRACTION: P. K. Yadav, R. Bhasker, A. A. Stonier, G. Peter, A. Vijayakumar, and V. Ganji: Machine learning based load prediction in smart‐grid under different contract scenario. IET Generation, Transmission & Distribution 17, no. 8, 1918‐1931 (2023). https://doi.org/10.1049/gtd2.12828The above article, published online on 27th March 2023 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal's Editors‐in‐Chief; Christian Rehtanz and Federico Milano; the Institution of Engineering and Technology; and John Wiley & Sons Ltd.Concerns were raised regarding the article, including the presence of tortured phrases, and duplication of images with the following article:L. Wang, S. Mao, B. M. Wilamowski and R. M. Nelms, “Ensemble Learning for Load Forecasting,” in IEEE Transactions on Green Communications and Networking, 4, no. 2, pp. 616–628 (2020), https://doi.org/10.1109/TGCN.2020.2987304.When the authors were contacted for an explanation, they did not address the concerns adequately. Accordingly, we cannot vouch for the integrity or reliability of the content and have taken the decision to retract the article. The authors have been informed and they disagree with the retraction.

Supply chain coordination and decision-making under revenue sharing and cost-revenue sharing contracts with returns

The increasing prevalence of product returns poses challenges for businesses, the environment, and society. Efficient returns systems need to be developed. This article addresses the issue by presenting a game-theoretical modeling approach to optimize pricing and ordering decisions in supply chain contracts between manufacturers and retailers. Revenue-sharing and cost-revenue-sharing contracts are investigated in conjunction with two returns-handling strategies: one performed by the manufacturer and the other by the retailer. As a result, four distinct contract scenarios are derived. In each scenario, the manufacturer-leader and the retailer-follower engage in a Stackelberg game. Optimal solutions are obtained for the models. In addition, it has been shown that the supply chain can be coordinated if the manufacturer shares the revenue and returns handling costs with the retailer. Numerical analyses are conducted to illustrate the theoretical results.

RETRACTED: Machine learning based load prediction in smart‐grid under different contract scenario

AbstractMany progressed information scientific strategies, particularly Artificial Intelligence (AI) and profound learning methods, have been proposed and tracked down wide applications in our general public. This proposition creates information driven arrangements by utilizing the most recent profound learning and AI innovation, including outfit learning, meta‐learning and move learning, for energy the executives framework issues. Genuine world datasets are tried on proposed models contrasted and best in class plans, which exhibit the predominant presentation of the proposed model. In this proposition, the engineering of the Smart Grid testbed is additionally planned and created by using ML calculations and true remote correspondence frameworks to such an extent that constant plan necessities of Smart Grid testbed is met by this reconfigurable system with stacking of full convention in medium access control (MAC) and physical layers (PHY). The proposed engineering has the reconfiguration property in view of the organization of remote correspondence and trend setting innovations of Information and communication technologies (ICT) which incorporates Artificial Intelligence (AI) calculation. The fundamental plan objectives of the Smart Grid testbed is to make it simple to construct, reconfigure and scale to address the framework level prerequisites and to address the ongoing necessities.

Call option contract in a supply chain with random yield and random demand using downconversion approach

PurposeThis study aims to examine the value of the call option contract in hedging the risks in the supply chain. The decentralized supply chain without call option contract is first studied as the criterion model for evaluations. This paper addresses several questions: What will be the optimal manufacturer’s production quantity, retailer’s ordering and pricing policies in the presence of random demand and random yield by applying the downconversion approach? How will the call option contract influence the optimal decisions for the members of the supply chain? Can the risk from randomness be divided among the members in the supply chain through the call option contract?Design/methodology/approachThis paper considers a two-level decentralized supply chain under random yield and random demand in which the manufacturer takes advantage of the downconversion approach with two scenarios, with and without option contract. To the best of the authors’ knowledge, no article or study uses the downconversion approach in a supply chain regarding random yield and random demand. Furthermore, the paper considers pricing with option contract in the supply chain, which makes this article stands out significantly from other articles in the literature.FindingsThis study shows that the downconversion approach would reduce the risk caused by the random yield, which appears to be the appropriate method for the environmental goal of the supply chains. Moreover, adopting a call option contract can increase flexibility and mitigate risks, resulting in more expected members’ profits.Research limitations/implicationsTo simplify the model, the authors assume one manufacturer and one retailer, so extending the model to consider multiple retailers instead of one retailer and inventory sharing between them would be interesting. Considering the option and exercise prices as decision variables would be important future research topics. Put option and bidirectional option contracts could be investigated in the future. Another extension is modeling asymmetry of information in supply chain.Originality/valueThis paper provides managerial insights on dealing with both demand and yield risks in a manufacturer–retailer supply chain. The manufacturer has a random yield production and produces two types of vertical products: low-end and high-end. To reduce waste caused by the random yield, the manufacturer uses a downconversion approach in which low-end products are made by converting the defective high-end products. The manufacturer purchased a shortage of high-end products from the secondary market (i.e. emergency sourcing). High-end products are sold through the retailer, and low-end products are sold directly by the manufacturer. The customer demand for high-end products in the end market is random and depends on the selling price, and the customer demand for the low-end products in the secondary market is independent and random. The retailer contracts the manufacturer with the call option to obtain high-end products to meet a random demand; in fact, by using the call option contract, the authors try to balance the risks between two members. Two scenarios of with and without call option contract are proposed. After the high-end product demand is observed, the retailer would exercise the option order quantity in the call option contract scenario and then place an instant order with the manufacturer if necessary. In each scenario, the manufacturer and the retailer make their decisions simultaneously (static game) to determine the retailer’s optimal ordering and pricing policies and the optimal production quantity of the manufacturer (Nash equilibrium) by maximizing their expected profits. Finally, the impact of the model parameters on the supply chain is expressed through numerical examples. The numerical analysis shows that the call option contract provides greater profit than the wholesale price contract.

Simultaneous controllers for stabilizing the frequency changes in deregulated power system using moth flame optimization

This paper introduces a stochastic idea for two-area automatic generation control (AGC) of the restructured system for enhancing the system dynamic performance. In this work, a new 2-degree of freedom of proportional-integral derivative-fractional order proportional derivative with filter (2DOF PID-FOPDN) approach is proposed for the AGC two area system. To ensure realization of optimal gains of the controller, a novel nature-inspired moth-flame optimization (MFO) is suggested using integral of time multiplied absolute error (ITAE) model. The performance of MFO-based 2DOF PID-FOPDN is evaluated against Cuckoo search (CS), Bat algorithm (BA), and Teaching learning-based optimization (TLBO) approaches in different contract scenarios of deregulated system. Further work to reduce the changes in tie-line has been applied through different FACTS controllers, such as Distributed power flow controller (DPFC), Thyristor-controlled series capacitor (TCSC), Unified power flow controller (UPFC), and Static synchronous series compensator (SSSC); integrated into the AGC system with the co-ordination of Ultra-capacitor (UC). The results indicate that the MFO-based 2DOF PID-FOPDN shows superior performance with DPFC-UC over other approaches in all contract scenarios of liberalized system. A sensitivity analysis is examined to recognize the robustness of the suggested approach under ± 25% deviation in loading and system parameters.

Vertical Channel Conflict Coordination Strategy of e-Commerce Supply Chain under Platform Brand Empowerment

We develop a game model for a supply chain consisting of one e-commerce platform, one supplier from other channels, and one retailer. The platform has a well-known brand that can influence consumers’ purchase decisions, and it provides good-quality products with high prices, while supplier from other channels provides cheaper products but possibly with low quality, and there may even be some serious quality problems, sometimes leading to serious problems such as “free-riding” behavior by the retailer and reducing the profits of the supply chain members. First, we study the decisions of platform and retailer under centralized decision (CD) scenario, decentralized decision (DD) scenario, cost sharing contract (CS) scenario, and minimum order quantity contract (QC) scenario. Second, we found that channel conflicts have a negative impact on supply chain members under DD scenario; however, CS and QC scenarios can make the optimal empowerment level of platform the same as CD scenario and encourage retailer to order more products from platform. Finally, the improvement effect in QC and CS scenarios is affected by the substitutability of the two products, the coefficient of empowerment cost, and the reaction coefficient of product price on goodwill. Furthermore, we found that under QC scenario, only within an appropriate range can the platform and the retailer achieve a win-win situation.

Carbon emission reduction decisions of supply chain members under cap-and-trade regulations: A differential game analysis

A global consensus has been reached that carbon emission reduction is now an inevitable social trend. A manufacturer can reduce its direct carbon emission by itself and indirect carbon emission by cooperating with suppliers. In a low-carbon context, we investigate a detailed model that combines cap-and-trade regulations with the low-carbon preferences of consumers. In this research, differential game models are developed to study the emission reduction decisions of two supply chain members under three scenarios: (1) a non-cooperation (coop) scenario where the manufacturer makes a decision on its level of effort in carbon emission reduction and the supplier is followed; (2) a coop program scenario in which the supplier’s emission reduction efforts are supported by the manufacturer; and (3) a two-way coop contract scenario in which both supply chain members support each other’s emission reduction efforts. A comparative study is conducted on supply chain members’ carbon emission reduction efforts and optimal profits obtained under the above scenarios. The results indicate that under the two-way coop contract scenario, both supply chain profits and emission reduction levels are the largest, with the greatest efforts made by channel members. In contrast to the non-coop scenario, both firms make more emission reduction efforts and earn more profits under the coop program scenario.

Preferences for curtailable electricity contracts: Can curtailment benefit consumers and the electricity system?

Growth in energy demand together with the increased volatility from growing intermittent electricity production requires new sources of demand flexibility to maintain power system balance. End-use specific curtailable electricity contracts are one incentive-based Demand Response (DR) instrument that could help increase flexibility. This paper employs a choice experiment on a representative sample of electricity consumers in Ireland to elicit their preferences for these types of contracts on household appliances during peak load hours. A welfare analysis is then conducted to determine the compensating variation for different contract scenarios and examine the potential savings associated with a selection of scenarios from the perspective of the power system. The results suggest that there could be potential for flexibility from curtailable electricity contracts. On average, consumers are found to be mostly indifferent to curtailable contracts compared to their status quo contract. More specifically, the type of household appliance in these contracts has the most influence on preferences, while contracts at low event frequencies that include advance notice and an opt out are most preferred. In general, the net benefits to the system in curtailing the tumble dryer or dishwasher at low monthly frequencies are found to be positive, while net benefits are estimated to be negative for the other appliances.

Reliability improvement incentive strategies in the manufacturing industry

PurposeCompanies face the critical reliability problem of products due to the development of outsourcing. This study intends to provide some feasible solutions for a company to improve the reliability level of products.Design/methodology/approachThe paper considers the reward and reliability decisions regarding a product made with two complementary components from two different suppliers: high-capable and low-capable. Two kinds of reliability improvement incentives (normal incentive and cost-sharing incentive) through which a manufacturer provides a reward and shares the reliability improvement cost with a supplier are discussed. As the Stackelberg leader, the manufacturer determines the strategy, while the suppliers are responsible for determining its reliability. Using a game-theoretic framework, four different contract scenarios are addressed. We develop analytical methods to better understand how the manufacturer decides the incentive mechanism to be used for the suppliers.FindingsThe results show that cost-sharing contracts do not always lead to a higher reliability level and more enormous profits. Setting a target reliability level is better for the manufacturer. The cost-sharing contract is beneficial for a high-capable supplier even though it does not directly participate in that kind of mechanism. A low-capable supplier gains more profit when the manufacturer provides incentive mechanisms that do not specify a target reliability level.Originality/valueThis paper investigates the reliability improvement mechanism used for complementary products and focuses on identifying the optimal decisions when demand is influenced by the gap between the product's failure rate and the standard failure rate.

Automatic Generation Control Strategies in Conventional and Modern Power Systems: A Comprehensive Overview

Automatic generation control (AGC) is primarily responsible for ensuring the smooth and efficient operation of an electric power system. The main goal of AGC is to keep the operating frequency under prescribed limits and maintain the interchange power at the intended level. Therefore, an AGC system must be supplemented with modern and intelligent control techniques to provide adequate power supply. This paper provides a comprehensive overview of various AGC models in diverse configurations of the power system. Initially, the history of power system AGC models is explored and the basic operation of AGC in a multi-area interconnected power system is presented. An in-depth analysis of various control methods used to mitigate the AGC issues is provided. Application of fast-acting energy storage devices, high voltage direct current (HVDC) interconnections, and flexible AC transmission systems (FACTS) devices in the AGC systems are investigated. Furthermore, AGC systems employed in different renewable energy generation systems are overviewed and are summarized in tabulated form. AGC techniques in different configurations of microgrid and smart grid are also presented in detail. A thorough overview of various AGC issues in a deregulated power system is provided by considering the different contract scenarios. Moreover, AGC systems with an additional objective of economic dispatch is investigated and an overview of worldwide AGC practices is provided. Finally, the paper concludes with an emphasis on the prospective study in the field of AGC.

Supply chain coordination considering e-tailer's promotion effort and logistics provider's service effort

<p style='text-indent:20px;'>Promoting the sale of green agriculture products through online platforms has become the main focus of agricultural industries. In a supply chain consisting of an e-tailer and third-party logistics (TPL), both the promotion effort of the e-tailer and the logistics service effort of TPL can affect the demand. Considering that logistics service contracts may be provided by the e-tailer or TPL, this study defines two different timing sequences. Three types of contracts, i.e., fixed-price, revenue-sharing, and cost-sharing contracts, are used to coordinate the supply chain. The game models under different timing sequences and different contract scenarios are established and solved. The promotion effort and logistics service effort under different scenarios are compared theoretically and numerically. The results indicate that both the promotion effort and logistics service effort change with timing sequences and contract types. The timing sequences depending on the contract provider significantly affect the performance of the supply chain. The cost-sharing contract provided by the TPL can motivate the e-tailer to apply the largest effort, and vice versa. The cost-sharing contract provided by the e-tailer can achieve the largest demand that is optimal for both the e-tailer and supply chain. However, the optimal contract for the TPL is conditional.</p>

Research on the Reform Prospect of Blockchain Applied to Sports Industry

Blockchain technology has caused global technological innovation, and it is bound to bring profound changes in China's sports industry. Sports industry is a new sunrise industry in China. It is of great strategic significance to promote the transformation of sports industry mode and promote the high-quality development of sports industry by means of block chain technology. Based on the transformation and upgrading of China's modern sports industry, this paper explores the advantages of blockchain technology, and takes trust mechanism, sports IP value, intellectual property protection and market vitality development as the breakthrough point to objectively analyze the practical pain points of sports industry. From the three dimensions of technology, policy and market, this paper discusses the feasibility of applying blockchain technology to sports industry, the advantages of solving sports industry problems and the potential threat of future industry development. In addition, this paper first examines the change of sports industry mode brought by blockchain technology, and discusses the specific application scenarios of team salary system under the background of encrypted digital currency technology, product consumption mode under intelligent anti-counterfeiting system, and venue operation process in intelligent contract scenarios, so as to further provide reference for the introduction and development of blockchain technology in China's sports industry.

Performance contract scenario and socio-economic development of Rwanda

Performance contract scenario and socio-economic development of Rwanda

Performance analysis of distributed power flow controller with ultra-capacitor for regulating the frequency deviations in restructured power system

Abstract This paper presents a novel approach for automatic generation control (AGC) of two-area deregulated system with unequal sources for sustaining the frequency and tie-line power at perturbations. The combination of ultra-capacitor (UC) and various FACTS controllers such as Thyristor-controlled series capacitor (TCSC), Static synchronous series compensator (SSSC), Unified power flow controller (UPFC), and Distributed power flow controller (DPFC) have been investigated in AGC of interconnected system with thermal-wind and hydro-diesel generating units. An innovative metaheuristic method called bat algorithm (BA) is used to ascertain the optimal gain parameters of the two degree of freedom (2DOF) controllers using an integral squared error (ISE) criteria. Furthermore, the productive assessment of the bat tuned 2DOF controllers are also compared with teaching learning-based optimization (TLBO) and cuckoo search (CS) methods optimized 2DOF in distinct contract scenarios of the suggested restructured system. The effect of the coordinated performance of UC and DPFC has been mitigated the oscillatory response of the AGC system at various operating circumstances. The investigations disclose that the bat optimized 2DOF-PID yield the productive outcomes with coordination of DPFC and UC in all contract transactions of the restructured system.

Frugal innovation in supply chain cooperation considering e-retailer’s platform value

E-retailers have recently paid close attention to frugal innovation in their supply chains. However, there are few studies on frugal innovation considering the e-retailer’s platform value raised by the increase in the platform user scale. Motivated by industrial practice, we consider a supply chain consisting of an e-retailer and a manufacturer in the context of frugal innovation, where the platform value of the retailer is characterized by Metcalfe’s law. We use game models to investigate the frugal product price and optimal degree of frugality decisions for the centralized, decentralized, retailer-led revenue-sharing contract and bargaining revenue-sharing contract scenarios. Our results indicate that the bargaining revenue-sharing contract can improve the frugal degree of the development-intensive frugal product (DIFP), while the frugal degree of the marginal cost-intensive frugal product (MIFP) cannot be improved by cooperation in the supply chain. We then compare the supply chain profit, the platform value of the retailer and the profit of the manufacturer in different scenarios. The results show that the centralized scenario is the optimal scenario where the platform retailer implements vertical integration strategy. Otherwise, establishing strategic partnership through the bargaining revenue-sharing contract is suboptimal for both the platform retailer and the manufacturer.

Fractional Order Sliding Mode Controller Fed Load-Frequency Control of Multi-Area Deregulated Power System Network

This paper presents a Fractional Order Sliding Mode Controller (FOSMC) for load frequency control of multi area power system in deregulated environment. In deregulated power system the design of controller is more complicated due to contracted and un-contracted load demands. This proposed controller shall take care of system nonlinearities and uncertainties under bilateral contract scenario for sudden load disturbances. The performance of proposed controller compared to PI controller and without any controller.

Risk assessment of different sourcing contract scenarios in project procurement

Procurement is an overlapping function between engineering and construction phases of engineering procurement and construction (EPC) projects. Due to these overlaps, procurement risks may have cascading effect on project cost and schedule overruns. Thus, management of procurement risk is important to avoid detrimental effect on the success of project. A project requires multiple items from multiple suppliers under multiple contracts, terms and conditions and risks exposure. This study proposes an integrated frame work, of 64 combinations comprising of type of item, type of buyer-supplier relationship, type of pricing regime and six types of procurement risks, to devise an optimal project procurement portfolio. Overall non-critical items pose the lowest and strategic items the highest levels of procurement risks to the project. Amongst types of buyer-supplier relationships, partnership sourcing has the lowest risk exposure. Amongst pricing regimes cost reimbursement has the highest risk exposure and fixed price has the least. For leverage, bottleneck and strategic items partnership sourcing type of buyer-supplier relationship with firm price, cost incentive and cost reimbursement pricing regime, respectively, emerge to be the best combination of procurement strategy. For non-critical items adoption of competitive arm’s length type of buyer-supplier relationship with firm pricing regime is suggested.

Sustainable food security decision-making: An agent-based modelling approach.

Ensuring a consistent and regular availability of food is crucial for food security. Food markets, supplied through both domestic production and international trade, are governed by several risks emerging from unpredictable supply chain disruptions, volatility of commodity prices, along with other unforeseen circumstances such as natural disasters. To mitigate the challenges threatening the stability of food systems, decision-making within the food sector should be enhanced and robust to accommodate any changes that might cause food shortages. Dynamic models, that can predict the behavior of food systems in order to avoid potential future knock-on effects and deficits, are incumbent to ensure the sustainable performance of food systems. This study proposes a dynamic decision-making scheme that simulates strategies of the perishable food market under different circumstances. An agent-based model (ABM) is developed and implemented using python MESA library for a case study in Qatar, illustrating the potential performance of tomato under three different scenarios to be considered, namely: (a) baseline scenario - aiming to reflect current production and market conditions; (b) water resource efficiency scenario - basing decisions on crop water requirement (CWR) depending on weather conditions; and (c) economic risk scenario - applying the concept of forward contracts to hedge against future uncertainties in crop prices. The findings of this study demonstrate that under the baseline conditions, a tomato crop can be supplied through a combination of domestic production and imports depending on the available inventories and prices imposed by exporters. The results obtained for the CWR scenario suggest the need for total reliance on imports in order to meet domestic demand, as there is potentially high-water loss, which amounts to an average of 4.9 Billion m3 per year, if tomato is grown locally. In contrast, the results from the forward contract scenario recommend a 57% dependency on local production in order to mitigate the effects of volatility in global food prices, which contributes to a 63% reduction in environmental emissions. Findings of this research provide insight into the factors that influence strategic decision making by the food sector to enhance its economic and environmental performances under diverse circumstances.

Contract preference for the dominant supplier subject to inventory inaccuracy

Inventory inaccuracy is usually inevitable, and affects decision making. This paper investigates the operational decisions and contract preference in a supply chain with one supplier and two competing retailers that are subject to inventory inaccuracy. The supplier, acting as the Stackelberg leader, first decides the contract format and pricing policy. The two retailers are followers, which make their decisions simultaneously. We establish a newsvendor model to derive the equilibrium solutions analytically under the buyback contract, consignment contract and hybrid contract scenarios. Then we conduct a numerical study to illustrate the impact of inventory inaccuracy on the supplier chain members’ operational policy and the dominant supplier’s contract preference. The results show that inventory inaccuracy plays an important role in determining the retailers’ equilibrium order quantities and retail prices, and the supplier’s wholesale (consignment) price. In particular, one retailer is better off (worse off) if the other who adopts the consignment (buyback) contract improves the inventory availability. Importantly, inventory inaccuracy affects the supplier’s contracting strategy. If the inventory availability changes, then the optimal contract selection may, accordingly, be changed. The conclusions reveal that although inventory inaccuracy is assumed to have occurred on the retailer’s side, both the retailer and the supplier are greatly influenced by the inventory inaccuracy. Therefore, the supplier should fully consider inventory availability and retail competition before determining the contract format. The retailer should improve his inventory availability to enhance competitiveness, to receive a more profitable contract format from the supplier.

Effect of Superconducting Magnetic Energy Storage on Two Agent Deregulated Power System Under Open Market

Abstract This article addresses the impact of SMES (superconducting magnetic energy storage) on two agent restructured power system under open market. In order to have better analysis regarding LFC problems inside restructured power systems, the proposed system has been chosen as a two agent hydro-thermal restructured system. Proposed deregulated power system with different contract scenarios such as unilateral, bilateral & violation have been studied. An UPFC unit is employed along with the SMES unit to lessen several LFC problems. Further a bat optimization technique has been proposed to tune the fractional order PID controller.