Wholesale Market Research Articles

Active Surveillance of Avian Influenza in the Southwestern Poyang Lake Area, China: Analyzing Changes in Wholesale and Frozen Fresh Retail Markets Post-Policy Implementation

This study aims to conduct active surveillance of avian influenza in the southwestern Poyang Lake area of China and to analyze the changes in avian influenza prevalence in wholesale poultry markets and frozen fresh retail markets following the implementation of policies regulating frozen fresh poultry products. The type A avian influenza virus nucleic acids were detected using real-time reverse transcription polymerase chain reaction (real-time RT-PCR), and a triplex real-time RT-PCR assay kit specific for H5/H7/H9 RNA was utilized on the influenza A-positive samples to differentiate among the avian influenza virus subtypes. From October 2020 to June 2024, the positivity rate of the live poultry wholesale market was 59.2%. The positivity rate of frozen fresh retail markets was 45.4%. In August 2023, the H9 subtype had the highest positivity rate in both markets. However, after that, the rate of untyped positives began to rise, particularly in the live poultry wholesale market where the positivity rate of the H5 subtype also showed an increasing trend. Implementing a frozen fresh poultry products policy has effectively reduced the avian influenza positivity rate in frozen fresh retail markets over the first two years. However, the positivity rate showed a rebound trend in the last two years. The live poultry wholesale market may be the source of the spread of avian influenza in frozen fresh retail markets, so managing the live poultry wholesale market and surveillance avian influenza should be strengthened. Recent surveillance indicates a significant uptick in the positivity rates of the H5 subtype and untyped strains of avian influenza, underscoring the importance of continued vigilance and strengthened prevention and control measures.

Innovative system to maximize methane production from fruit and vegetable waste.

Anaerobic digestion of fruit and vegetable waste (FVW) offers an environmentally friendly alternative for waste disposal, converting it into methane for energy recovery. Typically, FVW digestion is conducted in a continuously stirred tank reactor (CSTR) due to its ease of use and stability with solid concentrations between 5 and 10%. However, CSTRs are limited to organic loading rates (OLRs) of about 3kg COD/m3.day, resulting in large reactor volumes, low methane productivity, and costly wet digestate handling. This work introduces a novel method for methane production from FVW using a high-rate reactor system. The proposed approach involves grinding, centrifuging, and/or pressing the FVW to separate it into liquid and solid phases. The liquid phase is then digested in an up-flow anaerobic sludge blanket (UASB) reactor, while the solid phase undergoes digestion in a dry methanization reactor. A model incorporating all biological reactors was implemented in the Anaerobic Digestion Model 1 (ADM1) to provide a theoretical basis for the experimental development of this system. The current simulation scenarios offer initial references for operating the experimental system, which will, in turn, generate data for further model refinement. For instance, constrained liquid-gas mass transfer was considered for dry fermentation, with additional potential biochemical kinetic limitations to be incorporated following on experimental evidence. The success of this system could enable energy recovery in 72 Central Wholesale Markets across Brazil, offering a critical tool for planning, operating, and optimizing such systems.

Buildings as Batteries

Aggregators are increasingly using portfolios of various end-user resources such as local renewable generation, batteries, EVs, and demand-side management to participate in the electricity markets as virtual power plants. Whilst the smart control of energy within buildings is well established for cost optimization, the prospect of an aggregator collaborating with the energy managers of buildings to trade electricity in the wholesale markets is under researched. This paper uses a state-of-the-art architectural simulator to model the thermal inertia of a typical high-rise building in London and represent the thermodynamics of its hourly occupancy and weather responses. The building is simulated as a virtual battery by manipulating the HVAC settings. Price arbitrage on the electricity wholesale market and contracting with the local distribution network for flexible reserve services are both feasible and profitable. It is concluded that aggregators can apparently use buildings as additional assets within their trading portfolios. JEL Classification: L85 and L94.

Contamination of Hepatitis E Virus in Pig Livers of Different Market Types Collected from Seven Provinces of China.

Foodborne transmission of the Hepatitis E virus (HEV) is becoming an important public health problem in China, but the food associated with the HEV transmission route remains unclear. Pig liver is among the suspected food products involved in HEV transmission. Our research aimed to survey the contamination rate and genotype identification of HEV in pig livers from different types of markets in selected provinces of China. reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to screen for HEV in pig livers, nest RT-PCR was used for partial amplification of opren reading frame (ORF) 2, followed by sequencing, and phylogenetic analysis to determine the genotype of positive samples. A total of 787 pig liver samples from 7 provinces were collected. The average positive rate of HEV was 8.13% (64/787), Inner Mongolia (14.29%, 1/7) and Hebei province (14.29%, 23/161) showed the highest positive rate. There was a significant difference among the provinces (p < 0.01). Three major market types (wholesale market, supermarket, and butcher's shop) were included in this study, and the positive rates were 5.28% (21/398), 15.86% (23/145), and 8.20% (20/244), respectively. There was no significant difference among the three market types. Eleven of the positive samples were partially sequenced and identified genotypes 4a, 4d, and 3a.

Challenges in the Consumer‐Side of the Energy Transition

AbstractThe decarbonisation of the Australian economy relies on the transition of the electricity grid from fossil fuel to renewable sources. In this paper, we briefly summarise the logic behind the design of the National Electricity Market, the market servicing 88% of the Australian population. We then explore the challenges facing the National Electricity Market during its transition and emphasise key proposals aimed at reforming the consumer, or demand‐side, of the market. We highlight four challenges ‐ whether consumers will be active, whether retail markets can deliver contracts that facilitate efficient transition, whether the wholesale market will operate effectively and whether regulatory barriers can be quickly addressed.

The accounting challenges for indigenous businesses: a Pacific Islands case study

Purpose This paper aims to examine the accounting challenges faced by indigenous businesses in the wholesale and retail market in Tonga. Design/methodology/approach The data were collected through semi-structured interviews with 24 participants, from a mix of individuals from the wholesale and retail market in Tonga. This paper uses institutional logics framework to inform the study. Findings The research findings suggest an inability of indigenous businesses to adapt to significant changes in the market and overcome the economic and social challenges faced in the business environment involving accounting values. A lack of business skills and accounting knowledge, restrictive traditions and religious obligations and a poor business investment climate are key factors behind the inability of the indigenous Tongan businesses to succeed. Research limitations/implications The paper is limited to a study on Tonga only. The paper suggests better accountability from government sector on their effort to encourage inclusion of indigenous businesses. Practical implications The paper suggests better accountability from government sector on their effort to encourage inclusion of indigenous businesses. As a way forward, participants suggest that an inclusive approach for the government, businesses and stakeholders in policy formulation and consultation would create a better business environment that would foster the development and growth of the wholesale and retail business sector in Tonga. There is a dearth of cultural studies in accounting in countries within the developing world, particularly in the Oceania region. Social implications There are many accounting challenges faced by the indigenous Tongan business people in the market, which indicate specific areas where the attention of the policymakers should be directed. A better accountability from the government is needed on their efforts to encourage inclusion of indigenous businesses. Originality/value This paper extends the literature by considering inclusivity challenges for ethnically marginalised collectives of individuals in small business. The research findings suggest a gap in knowledge in the current business environment with respect to the Western accounting practices in the indigenous society.

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. This paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

A decentralized energy management scheme for a DC microgrid with correlated uncertainties and integrated demand response

Secure operation of a DC microgrid with high penetration of renewables and electric vehicle load is challenging. This paper proposes a decentralized energy management scheme for a grid-connected renewable integrated community DC microgrid considering the water-energy nexus. Uncertainties of renewable generation, plug-in electric vehicle load, electricity demand, electricity price in the day-ahead wholesale market, ambient temperature, and water demand are modelled using a probabilistic approach. Correlation between the input random variables is modelled using Copula theory. Flexibilities on the consumer side across multiple entities (temperature-dependent loads, electric vehicles, and water supply system storage) are coordinated to form an “integrated demand response entity”, which is further coordinated with the DC microgrid operator side flexibility (electrochemical storage) to support system operation. A distributed dynamic pricing scheme is used to implement the integrated demand response program. The objectives of the energy management scheme are to minimize the DC microgrid operator’s operating cost and consumers’ electricity cost. The decentralized algorithm is solved by the “alternating direction method of multipliers”. Simulation studies on a six-bus DC microgrid test system demonstrate that the proposed strategy reduces the operating cost of the DC microgrid operator by ∼19.28% and the electricity cost of the consumers by ∼13.82%.

Price transmission relationships in Taiwan seafood supply chain: Tilapia (Oreochromis niloticus) and milkfish (Chanos chanos)

Tilapia and milkfish are aquaculture species associated with the highest production volume in Taiwan. With both fish species as the research focus, this study explored their price transmission relationships along the seafood supply chain. Our study results revealed that tilapia and milkfish prices had a long-run equilibrium relationship at different stages of the seafood supply chain and presented inconsistent price transmissions in the short run. There are domestic and foreign market channels for tilapia, enabling producers and wholesalers to transmit prices to retailers. By contrast, milkfish are mostly supplied to domestic markets, there is not perfect price transmission in the milkfish supply chain besides between farmers and wholesalers. An accurate price forecasting model can effectively indicate future price volatility and predict seafood prices, especially following government policy changes or in the face of external impacts. Such model can also serve as a crucial reference for future research of tilapia and milkfish industry, producers, and aquaculture farmers. Finally, seafood prices are a key determinant of fisheries and supply chain sustainability. Therefore, the stability of seafood prices, fish market wholesale pricing, and retail pricing are issues meriting continuous attention for a sustainable seafood supply chain.

The Situation of Cross-Border Transportation of Goods through the 2nd Friendship Bridge Savannakhet-Mukdahan

This study is about the situation of cross-border transportation of goods through the 2nd Friendship Bridge Savannakhet-Mukdahan. The purpose of the study is to 1) study the situation of development of transportation and logistics in the friendship bridge, 2) The condition of transporting goods through the friendship bridge, and 3) Difficulties of entrepreneurs using the 2nd friendship bridge service, the population represented in the study was the driver of a truck that passed through the Savannakhet-Mukdahan International Checkpoint, Specific types of imported goods a total of 138 people were identified. The statistics used for data analysis is descriptive statistics to find frequencies and percentages. The results of the study show that the world bank has determined the logistics performance index: LPI and published the results of the comparative efficiency ranking of 160 countries. In 2018, the Lao PDR was ranked 82nd in the world with a score of 2,8 and in which ranked 69th of 160 counties in terms of the ability to trach and trace consignments with an average score of 2,9. Laos can now export and distribute goods to Thailand with other countries in Asia and Europe: China, Hungary, Poland, Belgium, the Netherlands, Singapore, Japan, Italy and France using Road NO 12 and Route 9. This is an important strategic route due to the ability to transport goods to countries in the region, which is a wholesale market and a channel to import cheap machinery, equipment, or inputs, making locally produced goods cheaper, which will increase domestic competitiveness and increase domestic competitiveness. Exports and imports across the 2nd Friendship Bridge, a five-year period from 2016-2020, see a year-on-year trade deficit due to the need to use agricultural inputs to boost agricultural production and boost agricultural exports in the future. The problems in transportation of goods in practice, the country has not yet been able to take full advantage of cross-border transport via the 2nd Friendship Bridge. Due to climate change, which is a barrier to delayed transportation, the overall infrastructure is still incomplete as there are still some areas of the road that need to be constructed and improved, along with the problems and obstacles of transport rules and regulations, such as: Problems with one-stop inspection, difficulties in customs clearance procedures and convenience of transport officials.

Electricity contract design and wholesale market outcomes in Australia's National Electricity Market

AbstractThe emergence of variable renewable energy (VRE) technologies has created a range of different energy contracting techniques. Within Australia's National Electricity Market (NEM), Run‐of‐Plant (RoP) Power Purchase Agreements (PPAs) became the most common form of contract with purchasers of wind and solar energy agreeing to pay a fixed price for energy irrespective of when it is produced and, therefore, its actual value to the market. In November 2023, the Commonwealth Government adopted a 32 GW RoP PPA Contract‐for‐Difference (CfD) underwriting policy that aims to effectively shield the generator from market price risk. This article discusses different contract structures and their impact on participant behaviour during periods of material oversupply and negative prices. We find that embedded solar PV exports into the distribution network, which are not required to dynamically participate in the wholesale market, have increased wholesale energy supply, enabling profit maximising vertically integrated renewable firms to drive prices lower in a manner that partially strands the output of RoP PPA CfD generators with a $0/MWh price floor. A key conclusion from our analysis is that requiring embedded solar PV to effectively participate in the wholesale market appears to be a pre‐condition for the efficacy of government‐initiated RoP PPA CfDs.

Optimal two-stage arbitraging and scheduling strategy for distributed energy resource aggregators

Given the rapid development of the distributed energy resources (DER), involving DERs into the wholesale market under the market and renewable uncertainties to achieve economic benefits is necessary but challenging. In this work, an arbitraging strategy is proposed for DER aggregators that bridge DERs with the wholesale market through energy trading. Besides, a novel self-adaptive minimax regret (MMR)-based optimal offering model is proposed for the DER aggregator to handle the uncertainties in both renewable generations and market prices. Additionally, an exact and communication-free solution methodology is proposed to resolve the formulated optimization problem with high computational efficiency. In the numerical results, the proposed methods can achieve near-to-optimal profits. Moreover, the performance of the proposed approach remains satisfactory even if the environment becomes very volatile.

Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-Term Load Forecasting in Electricity Wholesale Markets

Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-Term Load Forecasting in Electricity Wholesale Markets

Original Research Article Analyzing Price Behaviour and Constraints in Marketing of Small Onion in Tamil Nadu, India

This study examines market trends and seasonal patterns in small onion Markets in Tamil Nadu, while also investigating challenges faced by various stakeholders in the onion supply chain. The various analyses have made use of secondary data that has been gathered from different sources. The NHRDF office in Coimbatore, NHB website and AGMARKNET website are the sources of the monthly data on wholesale market prices and arrivals of small onions f markets of Dindigul, Chennai, Coimbatore and Idukki from 2014 to 2023. Primary data also obtained to fulfill the one of the research objectives by surveying the sample of respondents. Two districts were selected purposefully: Perambalur and Trichy districts, based on the top onion producing districts in Tamil Nadu. The sample size constitutes 180 respondents (80 farmers, 40 retailers, 20 wholesalers and 40 consumers) were randomly interviewed with help of pre structured interview schedule. Trend analysis revealed increasing price trends across all markets, with Idukki experiencing the highest rate of increase. Seasonal index analysis indicated that prices in Tamil Nadu markets are influenced by arrivals, with lower prices during peak arrival periods., while Idukki market in Kerala prices less influenced by arrivals. Farmers struggle primarily with high labor costs (78%) and high cost of fertilizers pesticides and machineries (68.7%), while consumers face problems with price fluctuations (68.8%) and quality concerns (68.6%), retailers face problems with lack of storage facilities (76.27%) and absence of facilities for grading (64.85%), and wholesalers struggle with financial risks (79.2%). The study's findings will aid policymakers to focus on improving market infrastructure, regulating intermediaries, and supporting farmers in managing costs. Leveraging existing labor schemes could help alleviate workforce shortages. Furthermore, customers would gain from initiatives to maintain price stability and raise quality standards.

Machine Learning in Cartel Screening—The Case of Parallel Pricing in a Fuel Wholesale Market

Machine Learning in Cartel Screening—The Case of Parallel Pricing in a Fuel Wholesale Market

Two-echelon collaborative many-to-many pickup and delivery problem for agricultural wholesale markets with workload balance

In the context of cooperation distribution among multiple wholesale markets, each customer can place orders with multiple agricultural wholesale markets, and each agricultural wholesale market can supply different products. To improve their distribution efficiency and avoid traffic congestion, cargoes need to be transshipped among collaborative distribution of different agricultural wholesale markets owing to their product heterogeneity. Each agricultural wholesale market undertakes the cost of completing the task for the reassigned customers of finding a balance among them, respectively. Fairness of allocation is achieved through workload balance and individual rationality constraints instead of monetary transfer payments. Aimed at the collaboration problem, a two-echelon collaborative many-to-many pickup and delivery problem with workload balance (2E-MPDP-WB) is presented in this study. A mixed-integer programming model for 2E-MPDP-WB is established, and a two-stage iterative algorithm combining branch-and-bound algorithm and adaptive large neighborhood search algorithm is proposed according to the problem structure. Some valid inequalities are also proposed. Finally, computational experiments show the correctness of the model and effectiveness of the algorithm, and sensitivity analysis is performed from four aspects, namely, costs before and after collaboration, workload balance, market geographical distribution, and demand mixing degree. The findings provide management insights for the collaborative distribution of multiple wholesale markets.

MiRNAs: Key Molecules in the Immunopathogenesis of Betacoronaviruses

A series of patients hospitalized with acute respiratory disease was reported in Wuhan, Hubei Province, China, in December 2019. Many patients have had direct or indirect links with the Huanan Seafood Wholesale Market, Wuhan. This is the prologue to the ongoing pandemic of Coronavirus Disease 2019 (COVID-19) that has affected more than 150 countries and over 250,000 people worldwide, killing thousands of people. The pandemic has once again drawn public attention to the coronaviruses that developed epidemics in China (2002) and Saudi Arabia (2012). Given the structural and phylogenetic similarity of the 2019 novel coronavirus (2019-nCoV) with the severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV), the results of recent studies have been combined with new findings to complete one of the strangest pneumonia puzzles in the human history. Coronaviruses establish extremely complex interactions with the immune system, especially in order to evade immune responses. Undoubtedly, increasing our knowledge of the immunopathogenesis of diseases caused by these viruses will eventually lead to more effective treatment and diagnosis. Non-coding RNAs (ncRNAs) are among the leading immune response regulators. MicroRNAs (miRNAs) play an important role in the expression and regulation of both innate and adaptive immune responses and in many immune disorders from autoimmunity to cancer and allergies. Our understanding of the functions of human and viral miRNAs in the pathogenesis of many viruses has increased in recent years. Accordingly, the present review article aims to review studies evaluating the role of miRNAs in the pathogenesis of other Betacoronaviruses. The results of these studies, given the similarity of viruses within the family Coronaviridae, could be helpful for future research on SARS-CoV-2.

Crises in Texas and Australia: Failures of energy-only markets or unforeseen consequences of price caps?

The Australian National Electricity Market (NEM) and the Texas wholesale electricity market (ERCOT) are two of the most prominent examples of energy-only wholesale electricity markets in the world. In early 2021 and mid 2022 these markets suffered from unprecedented crises, prompting some commentators to question the energy-only market design. Both markets are now considering implementing a form of capacity mechanism. Are these crises evidence of a fundamental flaw in the energy-only market design, or something else? We argue that, although the crises were very different in form, both crises arose in part from the effect of price caps in the wholesale market. We set out a model of the optimal mix of generation technologies in a framework in which generators can invest to protect against extreme weather events. We show that a price cap (below VoLL) reduces incentives for investment in hardening generation. Rather than further lowering the price caps – as was done in Texas – we propose a range of reforms to strengthen and enhance the confidence in the wholesale market.

Renewable-battery hybrid power plants in congested electricity markets: Implications for plant configuration

Examining coupled renewable-battery power plants (“hybrids”) in congested areas provides insights into a future of increased wind and solar penetration. Our study focuses on two types of congested regions, Variable Renewable Energy (VRE)-rich Areas and Load Centers, and explores likely plant configuration choices for developers and transmission network planners. This paper examines how hybrid value, comprising energy and capacity value, varies by plant configuration and congested region type considering factors such as storage duration, battery degradation, and ability to charge from the grid. We select plant locations from across the seven main U.S. independent system operators (ISOs). Hybrid value for each configuration is computed based on profit-maximizing plant operation given perfect foresight, according to observed wholesale power market real time prices from 2018 to 2021. In VRE-rich Areas, the median increase in energy value from extending storage duration from one to 4 h is 29.4 % for solar and 26.8 % for wind, assuming low battery degradation costs and storage sized to 100 % of the plant's nameplate generation capacity. Increasing storage duration beyond 4 h does not substantially increase its value from energy markets, even in VRE-rich Areas. We find that solar hybrids reach a 90 % capacity credit with 4 h of storage, while wind hybrids require 8 h of storage, based on the capacity factor of each hybrid during the top 100 net load hours.

Collaborative Planning of Distribution Network, Data Centres and Renewable Energy in the Power Distribution IoT via Interval Optimization

With the development of the power distribution Internet of Things (IoT), the escalating power demand of data centers (DCs) poses a formidable challenge to the operation of distribution networks (DNs). To address this, the present study considers the operational flexibility of DCs and its impact on DNs and constructs a collaborative planning framework of DCs, renewable energy sources (RESs), and DNs. This framework employs the interval optimization method to mitigate uncertainties associated with RES output, wholesale market prices, carbon emission factors, power demand, and workloads, and the collaborative planning model is transformed into an interval optimization problem (IOP). On this basis, a novel hybrid solution method is developed to solve the IOP, where an interval order relation and interval possibility method are employed to transform the IOP into a deterministic optimization problem, and an improved integrated particle swarm optimization algorithm and gravitational search algorithm (IIPSOA-GSA) is presented to solve it. Finally, the proposed planning framework and solution algorithm are directly integrated into an actual integrated system with a distribution network and DC to verify the effectiveness of the proposed method.