Wholesale Market Research Articles

What opportunities opens up for industrial enterprises the purchase of natural gas on the commodity exchange

Over the past 15 years, the fuel and energy complex of the Russian Federation has undergone significant systemic and structural changes. The need to implement changes is dictated by external challenges from the global energy markets, in the functioning of which the Russian economy plays a key role, as well as internal challenges, emerging in the form of requests from all sectors of the economy for the need to reduce the cost of consumed energy resources, and the need to increase the efficiency of the economy. Since 2006, a wholesale electricity (capacity) market has been operating in Russia, the mechanisms of which are based on the principle of competitive pricing for electricity supplied to consumers. Participation in the wholesale market for industrial enterprises opens up the possibility of reducing the cost of purchasing electricity, in the form of excluding the payment for the services of regional guaranteeing suppliers, whose share can range from 3% to 8% of the final electricity tariffs. Positive experience in creating competitive relations in the electric power industry determined the possibility for introducing energy market mechanisms into the Russian gas supply industry. In 2014, competitive natural gas trading was launched in Russia as part of the Commodity Exchange, in which large consumers and independent suppliers can participate.

Impact of monoterpenes in the stability of the anaerobic digestion of Mediterranean Wholesale Market Waste

The stability and robustness of long-term anaerobic digestion process of fruit and vegetable waste (FVW) generated in Mediterranean wholesale markets were assessed, monitoring potential inhibitory volatile organic compounds (VOCs) such as volatile fatty acids (VFAs) and/or monoterpenes. Particle size (4 and 10 mm) and organic loading rate (OLR) were evaluated during the experimentation. Anaerobic digestion remained stable at OLR of 1.0 g VS L−1 d−1 (VS, total volatile solids) regardless of the feedstock particle size. At this OLR, methane yield was 254 ± 8 and 229 ± 11 mL CH4 g VS−1 for 4 and 10 mm, respectively. As the OLR increased above 1.0 g VS L−1 d−1, the system rapidly destabilized, and a high accumulation of VFAs was observed. In parallel of to the VFAs accumulation, other VOCs such as fenchone also reached concentrations that contributes to the destabilisation of the process. The destabilization process at an OLR of 3.0 g VS L−1 d−1 also resulted in a drastic reduction in the relative abundance and species diversity of methanogenic archaea in all digesters.

Risk-based Offering strategy for a retailer in a wholesale and local electricity market considering demand response

Risk-based Offering strategy for a retailer in a wholesale and local electricity market considering demand response

The impacts of pandemic on urban housing prices: evidence from the outbreak of COVID-19 in Beijing, 2020

PurposeThe COVID-19 pandemic has significantly raised economic risk and uncertainty worldwide. How does COVID-19 affect urban housing markets? Is there any difference when different areas encounter COVID-19? This study aims to investigate the impacts of the pandemic on housing prices by using Beijing’s housing markets data in 2020.Design/methodology/approachThe authors use transaction-level data from April to September in 2020 to conduct a hedonic price analysis of the housing markets in Beijing. The data included 70,843 transactions scraped from a real estate agent’s website. The authors use the difference-in-differences approach to evaluate the impacts of the COVID-19 outbreak from the Beijing Xinfadi market (the largest and most important food wholesale market in Beijing) in 2020.FindingsThis outbreak of COVID-19 caused a 6.3% drop in housing prices in Beijing from April to September in 2020. However, the impacts of COVID-19 on housing prices in different urban neighbourhoods were spatially heterogeneous. Housing prices in neighbourhoods with industries that rely on face-to-face communication were more affected by the pandemic, while those that can work remotely were less affected.Originality/valueBy investigating the impacts of COVID-19 on housing prices in Beijing, this study illustrates that urban housing prices would be impacted by the pandemic, at least in the short term. While the rise and fall of housing prices were found spatially heterogeneous in Beijing, it suggests that urban neighbourhoods with specific socioeconomic characteristics and geographic locations would unfold different resilience when encountering pandemic. By using data scraping and rigorous statistical tools, the study is probably one of the first ones examining the consequences of COVID-19 in intra-urban housing markets.

Distribution Locational Marginal Pricing Under Uncertainty Considering Coordination of Distribution and Wholesale Markets

A rapidly growing amount of small-scale distributed energy resources (DERs) integrated into distribution systems call for an effective distribution electricity market to manage the uncertainty of DERs and remove barriers to the participation of DERs in wholesale electricity markets. To this end, this paper proposes an uncertainty-aware distribution locational marginal pricing (DLMP) mechanism based on robust optimization for day-ahead distribution markets within a transmission-distribution coordinated framework. The transmission-level model clears the wholesale market and forms transmission locational marginal prices (LMPs) to price energy, reserve, and uncertainty. At the distribution level, a robust optimization-based DLMP mechanism is proposed that internalizes uncertainties and coordinates with the wholesale market. Besides active and reactive power DLMPs, the uncertainty DLMP is introduced to reward reserve and charge uncertainties. The novel DLMP mechanism provides transparent and comprehensive price signals for managing voltage, congestion, loss, especially uncertainty. The coordinated model is solved in a decentralized manner by heterogeneous decomposition algorithm. Distribution and wholesale markets are integrated through the coordinated mechanism to fully utilize generation resources. Accordingly, DMLPs are highly correlated and consistent with transmission LMPs, and thus allow DERs to participate in wholesale markets. The effectiveness of the proposed method is verified via numerous case studies.

Special Section on Local and Distributed Electricity Markets

Driven by the goals of clean energy and zero carbon emissions, the power industry is undergoing significant transformations. The rapid growth of diverse distributed energy resources (DERs) at grid edge such as rooftop photovoltaics (PVs) and electric vehicles is transforming the traditional centralized power grid management to a decentralized, bottom-up, and localized control paradigm. Establishing local and distribution-level electricity markets provides an effective solution to managing large amounts of small-scale DERs. New regulations such as the recent FERC Order 2222 in the U.S. open the door to DERs in the wholesale markets. Through coordinating the local and distribution-level markets with the transmission-level wholesale market, the DERs and prosumers can trade energy and flexibility locally with each other and meanwhile provide energy, flexibility and ancillary services to the bulk power grid. During this transition, there are many new technical challenges to address, calling for innovative ideas and interdisciplinary research in this promising direction. Advanced information and communication technologies (ICT) are needed, as a key enabler, for the development and practical implementation of local and distribution electricity markets. Research into local and distribution markets is strongly interdisciplinary, involving the state of the art in power engineering, economics, and digital/information technology. A broad spectrum of contributors from universities, industry, research laboratories and policy makers is sought to develop and present solutions and technologies that will facilitate and advance practical applications and implementations of local and distribution-level electricity markets to uncover the values of DERs.

Exploiting DERs’ Flexibility Provision in Distribution and Transmission Systems Interface

This paper presents a new market-based framework to exploit distributed energy resources’ (DERs) flexibility in distribution and transmission systems. This framework targets intra-hourly flexibility requirements of energy systems. In this regard, a local market is operated in distribution network to exploit DERs’ capabilities. Local market is cleared in coordination with wholesale market to optimize DERs’ flexibility procurement for meeting intra-hourly variability and uncertainty in distribution and transmission systems. In the proposed framework, a technical virtual power plant (TVPP) operates day-ahead (DA) local energy and flexibility markets in which DER aggregators take part. Furthermore, the TVPP participates in DA wholesale energy and flexibility markets which are cleared by the market operator and the transmission system operator, respectively. In this framework, all agents’ preferences and their transactions are addressed using a bilevel model with multiple lower levels. The proposed model is reformulated into a mixed integer linear programming problem by utilizing strong duality theory, Karush-Kuhn-Tucker optimality conditions and primal-dual counterpart. The model is implemented on an IEEE standard test system. The results demonstrate effectiveness of the framework in utilizing DERs’ capabilities to meet flexibility requirements as well as satisfying agents’ preferences.

The economics of public transport electrification: A case study from Victoria, Australia

We investigate the economic, climate and electricity market implications of public bus fleet electrification based on the Melbourne Metropolitan region. We employ a novel fleet-level analysis, under tariff-based least-cost depot charging to compare the total cost of ownership (TCO) over 12 years of battery electric vehicle (BEV) against diesel bus fleets in a transitioning power sector. We also estimate impacts on electricity demand and carbon emissions, across purchase years between 2022 and 2039. We find that while the upfront costs of BEV bus fleets are considerably higher than diesel, they are more economical to operate in the long run, although our calculations are sensitive to diesel price assumptions. Electricity prices only have a minor impact on the TCO of BEV buses. Using a power sector transition scenario that mirrors Australia's Glasgow (COP26) commitments of net-zero economy wide emissions by 2050, we find that purchasing a BEV fleet in 2022 (0.42 MtCO2e) results in 74% less operational greenhouse gas (GHG) emissions than an equivalent diesel fleet (1.6 MtCO2e). If grid decarbonisation beyond 2022 would not proceed, BEV bus fleet emissions (at 2.03 MtCO2e) would be 27% higher than diesel. This suggests that an average 27% reduction of night-time grid emissions (over the next 12 years) is required for BEV buses to have lower emissions than diesel. One of our key policy recommendations is to co-optimise power and transport sector transitions by ensuring greater pass through of wholesale market pricing signals.

Price Dynamics and Integration in India’s Staple Food Commodities—Evidence from Wholesale and Retail Rice and Wheat Markets

Uncertain price movement in staple food commodities puts agrarian economies at risk if not monitored and managed consistently. Hence, an attempt has been made to analyze the price behavior and integration across major wholesale and retail markets for rice and wheat in India. Monthly data (July 2000 to June 2022) on prices viz. wholesale and retail were sourced from the Food and Agriculture Organization and analyzed using growth rate, instability index, seasonal price index, Bai-Perron’s test for structural breaks, Johansen’s test on cointegration, Granger causality test, and impulse response function. Findings indicated strong evidence of price dynamics in the selected markets in terms of spatial and temporal variation, clear-cut seasonality linking to production, and price divergence between wholesale and retail markets. Johansen’s test indicated a strong cointegration between wholesale and retail prices after accounting for structural breaks, exhibiting unidirectional-, bidirectional- and no causality. Impulse response analysis revealed that the selected wheat and rice markets are efficient in terms of ‘price discovery’ which takes place initially in the wholesale market, and is then transmitted to the retail market. The study advocates decision-making information to the producers, traders, and consumers who are interested in taking advantage of the price movement. It is concluded that strengthening the market intelligence and reducing the distortion in markets will improve the existing overall performance.

COVID-19 pandemic 3 years in: We are NOT ready for the next pandemic!

On December 29, 2019, four workers from the Huanan Seafood Wholesale Market, in Wuhan, China were admitted to hospital with pneumonia. By January 7, 2020, the National Institute of Communicable Disease Control and Prevention (Chinese Center for Disease Control and Prevention) had announced that they had isolated a novel coronavirus (CoV) from patients in Wuhan. Little did the world know that Wuhan would become ground zero for what would become one of the most significant health crises to affect the globe in recent memory. On January 30, 2020, the World Health Organization (WHO) declared a Public Health Emergency (PHE) of International Concern. The first United States (US) case of the CoV occurred in Washington State on January 21, 2020. In late January 2020, the US declared a PHE due to the coronavirus outbreak. The announcement came days after the WHO declared a Global Health Emergency as more than 9,800 cases of the virus and more than 200 deaths had been confirmed worldwide.3 On March 11, 2020, the WHO announced to the world that SARSCoV- 2 (COVID-19) was a global pandemic.

Exploring the pattern of price interdependence in rice market in Indonesia in the presence of quality differential

Being the main food commodity, the dynamics of rice prices is one of the most important issues for Indonesian economy. The prices at the retail level and at the farm level are influenced not only by the demand and supply in each of these markets but also by price behavior at the wholesale market. This study aims to analyse the dynamics of the relationship and behaviour of the prices of various varieties and qualities of rice in the wholesale market. The dynamics of rice prices are investigated by employing multivariate vector error correction model (VECM) and using daily price series at wholesale level during the period of 1 October 2014 until 12 February 2018. The results show a strong price relationship between premium-quality rice and medium-quality rice and between medium-quality rice and low-quality rice. Changes in the price of premium-quality rice and changes in the price of low-quality rice will have a large influence on the price of medium quality rice, but not vice versa. Furthermore, regarding the price stabilization policy, the results suggested that the policies aimed at regulating medium-quality rice prices are estimated to have relatively weak effects on the prices of premium-quality rice and low-quality rice.

Volatility in the Turkish wholesale electricity market: an assessment

ABSTRACT Electricity prices are determined in wholesale markets. A major issue in determining prices is the distortive effect of high volatility of supply. This paper investigates the volatility of electricity supply in the Turkish energy exchange for the period between 2017 and 2020, by using hourly data. We find that volatility increased substantially during this period and uncertainty became a major issue. High volatility brings non-price variables such as institutional and political preferences to the forefront in terms of the decision-making of suppliers. We also discuss the dominance of bilateral contracts, the design of the renewable support mechanism, and the disappearance of independent traders in the wholesale market as some of the major issues that correlate with high volatility.

Research on Profit Allocation of Agricultural Products Co-Delivery Based on Modified Interval Shapley Value

Most of the domestic wholesale markets have many operating entities, and the level of organization and scale is not high; therefore, at this stage, building a shared business platform and carrying out common distribution is an important way to improve the overall efficiency of the wholesale market distribution operations and the level of the intensive utilization of key resources such as vehicles. Carrying out common distribution requires the formation of a good synergy mechanism among the participating subjects, in which the design of a scientific and reasonable benefit distribution scheme, especially in balancing the relationship between government resources and social resources, is particularly important. As the benefit distribution of cooperation is affected by the dynamic changes of the resource input ratio, the distribution operation scale, the risk taking, and other factors, this paper establishes a multi-weight interval Shapley value method benefit distribution model, which reflects the effect of the key parameter variables. Through the empirical analysis of Beijing’s wholesale markets for agricultural products, the results show that the revised benefit distribution is more in line with the interest demands among multiple subjects and is positively correlated with the contribution degree among the participating subjects, which can better mobilize the cooperation enthusiasm of the participating enterprises and provide a new methodological path to solve the problem of common distribution in wholesale markets. The distribution model constructed in this paper further enriches the relevant research content in the field of common distribution and is of reference value for the benefit distribution problem that requires comprehensive consideration of the dynamic change in the multiple parameters affecting the relationship.

Mind the gap: Comparing the net value of geothermal, wind, solar, and solar+storage in the Western United States

Studies show that a diverse portfolio of zero-carbon resources will be needed to decarbonize the U.S. electricity sector, and that high capacity factor resources like geothermal will become particularly important in later stages of decarbonization as the capacity contribution of variable, weather-dependent resources like wind and solar declines with increasing market penetration. Yet while wind, solar, and—more recently—storage have all seen significant U.S. deployment in recent years, deployment of new geothermal plants has barely budged over the same period. We explain this disparity in historical deployment by analyzing empirical price data from power purchase agreements (PPAs) and wholesale energy and capacity markets, which demonstrate that geothermal has historically offered a lower “net value” (i.e., wholesale market value minus PPA price) than these other resources. Looking ahead through 2026, continued growth in the market share of wind, solar, and storage should improve geothermal's relative market value, yet likely not by enough to overcome the persistent cost gap between geothermal and these other, lower-cost resources. In the face of this challenging market outlook, policy intervention and continued R&D investments may be warranted to sustain a vibrant geothermal industry that stands ready to contribute to the late stages of decarbonization.

Marketmaking Middlemen

AbstractThis article develops a model in which market structure is determined endogenously by the choice of intermediation mode. There are two representative modes of intermediation that are widely used in real‐life markets: one is a middleman mode where an intermediary purchases inventory from the wholesale market and resells to buyers; the other is a market‐making mode where an intermediary offers a platform for buyers and sellers to meet and trade. We show that a marketmaking middleman, who adopts a mixture of these two intermediation modes, can emerge in a directed search equilibrium and discuss implications for the market structure.

Wholesale and retail energy markets model for the energy networks in the presence of the energy hubs

In this paper, the formulation of the energy market in two wholesale and retail models for different energy networks such as electric, gas and thermal networks in the presence of energy hubs according to the two-layer energy management system is presented. In the first layer of EMS, the coordination of resources and ALs with the operator of EHs is considered, and in the second layer of EMS, the coordination of the operator of EHs with ENOs is considered. In the proposed design, the mentioned networks have participated in the wholesale market as private distribution companies or DisCo and then buy energy from it. These companies have shared the purchased energy in the retail energy market environment between consumers and EHs connected to itself. This design is expressed in the form of two-level optimization, the upper level of which is the minimization of the expected energy cost of ENs in the mentioned markets, and the other level is the minimization of the expected energy losses of ENs in the retail market. In the following, the Karush–Kuhn–Tucker (KKT) method and Pareto optimization technique based on epsilon constraint method were used to derive the single-level and single-objective problem. Then, the unscented transformation (UT) method was used to model the uncertainties of load, energy price, renewable power and EV energy demand. Finally, based on the numerical results, it was observed that the proposed plan achieves the highest profit for EHs in proportion to the time-varying energy price. Also, with the optimal energy management of EHs, it has been able to reduce the energy cost of ENs by about 12% compared to load flow studies.

Strategic Bidding of Retailers in Wholesale Markets: Continuous Intraday Markets and Hybrid Forecast Methods.

The deregulation process of the electricity sector has led to competition in wholesale and retail markets. In particular, retailers submit bids to wholesale markets to satisfy the energy needs associated with portfolios of end-use customers. This paper describes a strategic process for retailers bidding in a wholesale market composed of a day-ahead market, an intraday market, and a balancing market. It considers a market design that involves a hybrid model for the intraday market, based on daily auctions and a continuous procedure. The paper also presents a computational study to illustrate and test both the market design and the strategic bidding process of retailers. The results confirm the advantages of considering a continuous intraday market, show that bidding in short-term markets is more beneficial than bidding in medium-term markets, and indicate important aspects to consider when selecting customers to add to the portfolios of retailers.

Research on Electric Load Forecasting and User Benefit Maximization Under Demand-Side Response

In this paper, the real-time changes of demand-side response factors are accurately considered. First, CNN is combined with BiLSTM network to extract the spatio-temporal features of load data; then an attention mechanism is introduced to automatically assign the corresponding weights to the hidden layer states of BiLSTM. In the optimization part of the network parameters, the PSO algorithm is combined to obtain better model parameters. Then, considering the average reduction rate of various users under energy efficiency resources and the average load rate under load resources on the original forecast load and the original forecast load, the original load is superimposed with the response load considering demand-side resources to achieve accurate load forecast. Finally, “price-based” time-of-use tariff and “incentive-based” emergency demand response are selected to build a load response model based on the principle of maximizing customer benefits. The results show that demand-side response can reduce the frequency and magnitude of price fluctuations in the wholesale market.

Risk-based optimal decision-making by the retailer in a mixed local and wholesale market environment considering demand response solution

This paper proposes a comprehensive model to determine the retailer strategy for purchasing electrical power from the wholesale and/or local market in an active distribution network. The uncertainties associated with the load and distributed generation resources in the active distribution network, the wholesale market price and the behavior of the local market players, are all considered in the presented model. A retailer in the demand response program is employed as retailers’ ability to govern the risks. A risk-based decision-making scheme is provided in this paper which takes into account every instrument that is accessible for retailers along with their associated uncertainties. The major target of this paper is to maximize the retailer benefit concerning a tolerable risk. In order to model risks, the scenario theories are exploited and for solving the optimization problem, particle swarm optimization (PSO) has been utilized. The proposed scheme has been simulated on an actual network and the obtained results confirm the effectiveness and computability of this method.

MRL-Based Model for Diverse Bidding Decision-Makings of Power Retail Company in the Wholesale Electricity Market of China

Power retail companies in the electricity market make profits through buying and selling power energy in the wholesale and retail markets, respectively. Traditionally, they are assumed to bid in the wholesale market with the same objective, i.e., maximize the profit. This paper proposes a multiagent reinforcement learning (MRL)-based model to simulate the diverse bidding decision-making concerning various operation objectives and the profit-sharing modes of power retail companies in China’s wholesale electricity market, which contributes to a more realistic modeling and simulation of the retail companies. Specifically, three types of operation objectives and five types of profit-sharing modes are mathematically formulated. After that, a complete electricity market optimization model is established, and a case study with 30 retail companies is carried out. The simulation results show that the proposed method can effectively model the diverse bidding decision-making of the power retail companies, which can further assist their decision-making and further contribute to the analysis and simulations of the electricity market.