Wholesale Market Research Articles

Financial Risk Control of Hydro Generation Systems through Market Intelligence and Stochastic Optimization

In the competitive electricity wholesale market, decisions regarding hydro generators are generally made under uncertain conditions, such as pool price, hydrological affluence, and other players’ strategies. From this perspective, this work presents a computational model formulation with associated market intelligence and game theory tools to support a decision-making process in a competitive environment. The idea behind using a market intelligence tool is to apply a stochastic optimization model with an associated conditional value at risk metric defining a utility function, which calculates the weight that the agents attribute to each stochastic variable associated with the problem to be faced. Subsequently, this utility function is used to emulate the other agents’ strategies based on their previous decisions. The final step finds the Nash equilibrium solution between a player and their competitors. The methodology is applied to the monthly allocation of firm energy by hydro generators under the current Brazilian regulatory framework. The results show a change in the generators’ behavior over the years, from risk-neutral agents seeking to maximize their return with 88% of decisions based on spot price forecasts in 2015, to risk-averse agents with 100% of decisions following a factor that is directly impacted by the hydrological affluence forecasts in 2018.

Synergy of solar photovoltaics-wind-battery systems in Australia

Intermittent weather conditions affect solar and wind generated electricity with storage that require optimisation. Solar Photovoltaics-Wind-Battery Hybrid Systems (PV–W–B) are ideal for optimising the synergy of solar and wind resources with storage for consistent production of renewable energy. This study assesses the synergy of solar and wind power under favorable battery operating conditions using the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) data spanning a period of 10 years over Australia. Key metrics describing the variability, reliability and intermittency of extractable solar power (based on Global Horizontal Irradiance - GHI), wind power density (WPD) and favorable battery operating temperature (T2) were computed separately for all available grid-points in Australia. Similarly, synergy and antergy (negative synergy) of solar-wind under favorable lithium-ion battery operating conditions were also computed. Results showed that the variability of GHI, WPD and T2 were lower in the southeastern regions of Australia whilst the intermittency period ranged from a few hours to a number of days. The wind-solar synergy under favorable battery operating conditions also peaked in the eastern regions (32% of the times with episodes of 12–48 h of battery charging). Additionally, for a site in southeastern region, the hybrid PV-W-B system generated extra profits in the wholesale market not only from the wind-solar synergy, but also from the battery optimisation mechanism. Hence, the intermittent solar and wind generation risks can be significantly mitigated by a hybrid PV-W-B system despite the market dynamic being an equally important factor for the profitability.

Quasi-Stochastic Electricity Markets

With wind and solar becoming major contributors to electricity production in many systems, wholesale market operators have become increasingly aware of the need to address uncertainty when forming prices. Although implementing theoretically ideal stochastic market clearing to address uncertainty may be impossible, the use of operating reserve demand curves allows market designers to inject an element of stochasticity into deterministic market clearing formulations. The construction of these curves, which alter the procurement of reserves and therefore the pricing of both reserves and energy, relies on contentious administrative parameters that lack strong theoretical justification. This paper proposes instead to link their construction to outcomes that would be expected in efficient stochastic markets. The analysis considers the potential of these “quasi-stochastic” market clearing approaches to improve efficiency relative to the deterministic status quo as well as ways in which they are unable to fully replicate the stochastic ideal. Further, the paper argues that efficiently managing uncertainty entails a reexamination of the discriminatory uplift payments and enhanced pricing schemes currently employed to address nonconvexity.

A robust decision framework for strategic behaviour of integrated energy service provider with embedded natural gas and power systems in day‐ahead wholesale market

The rampant growth in penetration of gas-fired distributed units (GFDUs) is recasting the role of the integrated energy service provider (IESP) as a price-maker player. Nevertheless, it is threatening the well-being and reliability of the natural gas networks (NGNs). In this regard, this paper investigates the strategic participation of integrated 20-node NGN and an 33-bus active distribution system (ADS) in the day-ahead wholesale market (WM), which consists of a six-bus transmission network (TN), through a bi-level optimization framework. The upper-level objective is to minimize the operational costs of the IESP as well as the cost of energy that is purchased/sold in day-ahead WM. The lower-level problem models the optimal response of the wholesale market operator (WMO) that has the objective of maximizing social well-fare by clearing the day-ahead wholesale market. To alleviate the NGN's pipeline congestion, the linepack capability of the pipelines is deployed, while demand response program (DRP) and interruptible loads (IL) are integrated into the ADS side. As a computationally efficient method, robust optimization (RO) is utilized to handle the uncertainties. The results emphasize the necessity of integrating NGN into this problem. Eventually, different case studies illustrate the impact of line pack and DRP in reducing market-clearing price.

A data-driven deep sequence-to-sequence long-short memory method along with a gated recurrent neural network for wind power forecasting

Large amounts of wind power generation have an impact not only on energy markets but also on wholesale and retail market designs. Simultaneously, technological issues arise as a result of the need to ensure the smooth operation of the power grid. In the long run, high-quality wind data series are required to generate model results that lead to robust policy advice. Several techniques are commonly used to forecast short-term, nonstationary, and nonlinear wind speeds. These techniques are lacking in model optimization and data processing abilities. This lack of expertise is posing a significant challenge for reliable and stable wind power forecasting. Furthermore, the medium and long-term forecasting criteria for models (e.g., robustness, accuracy, speed) are higher, making it difficult to obtain reliable results. This study used the extended deep sequence-to-sequence long short-term memory regression (STSR-LSTM) model for time-series wind power forecasting to overcome these challenges for accurate forecasting decisions. The statistical-learning technique is used to improve the dependability of the derived features as well as the expected performance. Three different locations/sites were used and analyzed (e.g., Belgian, DSO-Connected, Elia), three different forecasting classes (e.g., week-ahead forecast, day-ahead forecast, and most recent forecast), three different seasons (e.g., monthly, seasonal, and annual), and three experimental setups. The performance of Deep STSR-LSTM is validated using two existing models and four performance evaluation indexes. Despite the fact that the input wind power load curve had a lot of variation, we were able to achieve higher forecast accuracy. Using different sites and classes, similar forecast accuracy was achieved for each season (e.g., monthly, seasonal, and annual).

Dietary exposure assessment of paralytic shellfish toxins through shellfish consumption in Shenzhen population, China.

Paralytic shellfish toxins (PSTs) produced by certain marine dinoflagellates accumulate in filter-feeding marine bivalves. We used LC-MS/MS to detect and quantify 13 PSTs in 188 shellfish samples of 14 species collected from Shenzhen city's Buji seafood wholesale market from March 2019 to February 2020. Twenty-six of 188 shellfish samples (13.8%) were PSTs detectable. Within 14 species, 10 out of 34 noble clam Chlamys nobilis samples contain detectable PSTs with the highest detection rate 29.4%. Seven out of 17 samples from Nan'ao island contained detectable PSTs with the highest detection rate 41.2% among 11 origins. Samples containing PSTs were concentrated in spring and winter, with the highest levels in March>December>January. Among PSTs detected, C1 was dominant. Acute dietary exposure assessment for Shenzhen residents were based on mean adult body weight, 99th percentile daily shellfish consumption of Shenzhen food consumption survey 2008 and maximum PSTs concentration for each shellfish species. The outcome for Chlamys nobilis was 2.4~3.7-fold higher than recommended ARfDs. Mean PSTs concentration, P99, and mean shellfish consumption were used to assess chronic dietary exposure. The results were lower than recommended ARfDs. In conclusion, residents in Shenzhen are at risk for acute PSTs poisoning, while relatively safe from chronic PSTs exposure.

Role of Government Institutions in National Energy Policy1

As readers of this column are aware, the Federal Energy Regulatory Commission (FERC), is an independent agency organized within the US Department of Energy (DOE) and critically important in articulating and implementing federal energy policy. FERC provides the leadership necessary in establishing wholesale power market rules and supporting private sector investment in infrastructure development, and in market valuation and pricing of assets in energy markets. The impetus introducing competition in electricity markets began in 1978 with enactment of the Public Utility Regulatory Policies Act (PURPA). PURPA required that vertically integrated utilities—owning generation, transmission and distribution—purchase power from generators/producers that could produce electricity at a cost that was less than the utility's avoided cost (the cost at which the utility itself could have generated electricity). PURPA provided the opportunity for competition in generation where non‐utility independent power producers could build, operate, and compete with existing utility power generation.

SECURITY OF UKRAINE’S ELECTRICITY MARKET: IMPLEMENTATION AND CONTINUED HOLDING

The emergence of state-owned enterprises, Market Operator and Guaranteed Buyer, which are responsible for the operation of the day-ahead and intraday market and form the price policy for payment of electricity services to producers and suppliers that use renewable energy sources, i.e., work according to "green tariff" and "regulated tariff" for the needs of the population. It was noted that energy is distributed within the UES by energy supply companies licensed to provide electric energy at regulated and non-regulated tariffs. It is outlined that the actual results of the processes of reforming the electricity market are: the organization of the electricity market segments, which allows to consider the day-ahead market as the leading indicator of price formation; two trade zones operating at the same time, the United Energy System of Ukraine and the energy center of the Burshtyn TPP, where different prices have been formed due to the generation structure; the possibility of using the export potential of electricity according to the principles of ENSTO-S has been launched, which promotes general agreement between supplier countries, increases competition, forms a system of balanced results with the minimization of losses, accelerates the processes of integration of the electricity market of Ukraine into the European energy system. At the same time, the electricity market of Ukraine faces many challenges and threats, among which the countdown to the implementation of the free electricity market model was not accompanied by objective reasons by changes in regulated electricity prices for specific categories of consumers (population) and cross-subsidization, which ultimately caused significant financial stress to the state-owned enterprises Energoatom and UkrHydroEnergo, which are subject to the imposition of special duties; the practice of operating auctions for renewable energy sources in order to optimize their value is not implemented correctly. In this area, only the construction of such objects took place under the conditions of fixing the "green tariff"; led to a drop in economic development, significant consumer debt, and a decrease in electricity consumption, as a result of a drop in prices, an increase in the deficit and debt coverage for select categories of consumers; the significant accumulation of the debt burden of SE Energorynok in front of a significant number of generating companies, requires immediate state regulation and the adoption of a particular law regarding the further resolution of this problem; replacement of old capacities with new ones with a quick start for balancing and functioning of gas piston units and energy storage systems. It became known that in terms of its actual content, the electric power industry has several specific features that characterize its energy orientation: the change of parameters depending on the field of application, the simultaneity of the processes of production and consumption as an energy resource; constancy and identity of volumes of produced and consumed electrical energy; lack of possibilities for reservations in the form of goods; the impossibility of a predictable assessment of resource generation and consumption; complete dependence of the production component on consumer demand. In addition to the circumstances of the economic direction, specific properties are also characteristic of electric energy, which is related to its essential purpose as an energy resource: power; time; terms and conditions of consumption; quality; distance; variability. Today, the already existing positive and negative consequences of the effectiveness of state economic regulation of the electricity market should be noted. As for the negative consequences, it should be noted the versatile and non-uniform nature of the application of various forms and methods of pricing to electricity producers; tax imbalance due to the lack of necessary tax and budget levers for regulating the electricity industry; the practice of the cross-subsidization system of some consumers at the expense of others through the wholesale market price (ORC) for electric energy. A review of safety criteria in the country's electric power sector shows the imperfection of the electricity market and the need to strengthen the relevant safety tools. Keywords: electric energy, electric power industry, energy, electric power safety, energy market of Ukraine.

Reconfiguration of Uganda's bulk network to accommodate a wholesale electricity market

Countries that have restructured their electricity markets to wholesale markets have had significant benefits, including reduced generation costs, lower transmission losses and better consumer prices. In these markets, generators are dispatched in such a way that the financial benefits of both generator owners (producer surplus) and consumers (consumer surplus) are maximized. Retailers and large-scale consumers transact directly with power producers in a spot market or through contracts at wholesale level. Uganda's current single-buyer market (in which generation companies sell their power to a single entity that in turn transmits and sells it to distribution companies) was introduced in 2001 after the transition from a vertically integrated monopoly model. The market is expected to evolve into a wholesale market as the next restructuring step. This paper investigates the performance of the Uganda bulk network in a wholesale electricity market environment as modelled in Power World simulator. It considers different operation scenarios and possible infrastructure enhancements required for improved performance. Results showed that in the wholesale market model, transmission energy losses fell from an average of 4.3% to 3.8% compared to the single-buyer model due to more efficient network utilization. The economic analysis showed that off-peak and peak prices in the wholesale market system were 68.6% and 13.5% lower than in the current market respectively. However, old high loss transmission lines contributed to higher energy prices at receiving nodes. Transmission congestion, whose cost is embedded in a Location Marginal Price, caused sharp increases in the market's prices; this was addressed by using the network reconfiguration technique.

Novel Hybrid Stochastic-Robust Optimal Trading Strategy for a Demand Response Aggregator in the Wholesale Electricity Market

The close interaction between the electricity market and the end-users can assist the demand response (DR) aggregator in handling and managing various uncertain parameters simultaneously to reduce their effect on the aggregator's operation. As the DR aggregator's main responsibility is to aggregate the obtained DR from individual consumers and trade it into the wholesale market. Another responsibility of the aggregator is proposing the DR programs (DRPs) to the end-users. This article proposes a model to handle these uncertainties through the development of a novel hybrid stochastic-robust optimization approach that incorporates the uncertainties around wholesale market prices and the participation rate of consumers. The behavior of the consumers engaging in DRPs is addressed through stochastic programming. Additionally, the volatility of the electricity market prices is modeled through a robust optimization method. Two DRPs are considered in this model to include both time-based and incentive-based DRPs, i.e., time-of-use and incentive-based DR program to study three sectors of consumers, namely industrial, commercial, and residential consumers. An energy storage system is also assumed to be operated by the aggregator to maximize its profit. The proposed mixed-integer linear hybrid stochastic-robust model improves the evaluation of DR aggregator's scheduling for the probable worst-case scenario. Finally, to demonstrate the effectiveness of the proposed approach, the model is thoroughly simulated in a real case study.

Evolution of Fundamental Price Determination within Electricity Market Simulations

Electricity prices are the key instrument for coordinating electricity markets. For long-term market analyses, price determination based on fundamental unit commitment simulations is required. Within the European wholesale market, electricity prices result from a market clearing, which finds a welfare-optimal price–quantity tuple considering a coupling of multiple market areas with limited transmission capacity. With increasing exchange capacities in Europe, the precise modeling of the market coupling is required. Many market simulation models use multi-stage approaches with a separation of market coupling and price determination. In this paper, we analyze a new single-stage approach that combines both steps and theoretically and empirically demonstrate its precision by a backtest. For this purpose, we compare a simulated versus a historical electricity price distribution. Moreover, we explain the necessary adjustments for future regulatory developments of the European electricity market regarding flow-based market coupling and propose a concept for the application of future regulatory developments. We demonstrate further developments using a future scenario.

Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study

ObjectiveTo evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions.DesignDescriptive and modelling study based on surveillance data of...

Impact of the arm’s length regulation on a supply chain with asymmetric retailers

In many supply chains, suppliers that provide a key component to retailers in the wholesale market also have their own retail divisions in the retail market and form vertically integrated producers (VIPs) with these divisions. A VIP’s profit comes from two sources: (i) the wholesale profit from supplying the key component to retailers and (ii) the retail profit from its own retail division. In this situation, the VIP’s intra-company discount is often restricted by the arm’s length regulation (ALR) to induce fair competition in the retail market and improve the consumer benefit. However, the ALR may not always result in the desired outcome, especially when the retailers are asymmetric. Thus motivated, we investigate the impact of the ALR on the supply chain profit and the consumer benefit. Our analysis incorporates two types of asymmetry commonly observed among retailers: (i) retailer-specific selling costs and (ii) private information regarding the intra-company discount. Our results have several important implications. First, the ALR improves the supply chain profit only when the rival retailer is more competitive than the VIP’s retailer. Also, the ALR benefits consumers when the rival retailer is more competitive and the competition intensity is low. Second, under information asymmetry, while the rival retailer would not benefit from the VIP’s private information, the VIP’s gain does not always outweigh the rival retailer’s loss. Hence, the total supply chain profit may increase with the ALR. In addition, the consumer surplus can increase under information asymmetry unless the VIP’s intra-company discount is extremely limited.

Probabilistic Day-Ahead Wholesale Price Forecast: A Case Study in Great Britain

The energy sector is moving towards a low-carbon, decentralised, and smarter network. The increased uptake of distributed renewable energy and cheaper storage devices provide opportunities for new local energy markets. These local energy markets will require probabilistic price forecasting models to better describe the future price uncertainty. This article considers the application of probabilistic electricity price forecasting models to the wholesale market of Great Britain (GB) and compares them to better understand their capabilities and limits. One of the models that this paper considers is a recent novel X-model that predicts the full supply and demand curves from the bid-stack. The advantage of this model is that it better captures price spikes in the data. In this paper, we provide an adjustment to the model to handle data from GB. In addition to this, we then consider and compare two time-series approaches and a simple benchmark. We compare both point forecasts and probabilistic forecasts on real wholesale price data from GB and consider both point and probabilistic measures.

Commercializing Battery Storage for Integration of Renewable Energy in India: An Insight to Business Models

The research study focuses on exploring different business models that can be used for the deployment of battery storage in India. It further provides a perspective on the different business models adopted across the globe. It also focuses on the key market drivers that can be considered to build the country's storage ecosystem. The objective of the study was to bridge the gap between technology and commercialization. A comparative analysis of different business models adopted by other countries for battery storage and their relevance in the Indian Context was done. It also considered the business models that have been used in different sectors and looks feasible for the battery storage sector. The study recommends the model of “Trading stored electricity on Power Exchanges or Whole-Sale Market” and the model of “introducing battery storage as a package” as the most suitable models for implementation in the Indian context. Further the study identifies few critical factors for the success of commercializing battery storage in India which are choosing the right business model, knowing the needs of the customers and the Government's stand on policies.

Fruit and Vegetable Wholesale Market Waste: Safety and Nutritional Characterisation for Their Potential Re-Use in Livestock Nutrition

Compared to other food categories, fruits and vegetables are the most wasted. This leads to the squandering of economic, social, and environmental resources. The reallocation of fruit and vegetable waste (FVW) into animal feed contributes to the sustainability of livestock production, reducing the impact of feed production for land use. In this study, the fruit and vegetable waste from the General Wholesale Market of Milan was considered. FVW samples were collected for one year and were analysed for safety parameters and nutritional, vitamin, and mineral composition. Data showed that dry matter (DM) was on average 10.82 ± 1.21% and neutral detergent fibre (NDF) was on average 22.43 ± 4.52% DM. The presence of soluble sugars (30.51 ± 7.61% DM, on average) was also detected. However, the high moisture content of this waste makes it easily perishable, with detrimental effects on quality, storage, and transportation. A strategy was therefore proposed to reduce the water content of FVW by pressing. Overall, the results highlighted the significant nutritional value of FVW from the wholesale market and the need to develop appropriate technologies to maintain the food chain line safe.

Review of proposed different irradiation methods to inactivate food-processing viruses and microorganisms.

Coronaviruses, which have been enveloped nonsegmented positive‐sense RNA viruses, were first mentioned in the mid‐1960s and can attack people as well as a wide range of animals (including mammals and birds). Three zoonotic coronaviruses have been identified as the cause of large‐scale epidemics over the last two decades: Middle East respiratory syndrome (MERS), severe acute respiratory syndrome (SARS), and swine acute diarrhea syndrome (SADS). Epithelial cells in the respiratory and gastrointestinal tract are the principal targeted cells, and viral shedding occurs via these systems in diverse ways such as through fomites, air, or feces. Patients infected with the novel coronavirus (2019‐nCoV) reported having visited the Wuhan seafood wholesale market shortly before disease onset. The clinical data on established 2019‐nCoV cases reported so far indicate a milder disease course than that described for patients with SARS‐CoV or MERS‐CoV. This study aimed to review radiation inactivation of these viruses in the food industry in three sections: visible light, ionizing radiation (alpha ray, beta ray, X‐ray, gamma ray, neutron, plasma, and ozone), and nonionizing radiation (microwave, ultraviolet, infrared, laser light, and radiofrequency). Due to the obvious possibility of human‐to‐human and animal‐to‐human transmission, using at least one of these three methods in food processing and packaging during coronavirus outbreaks will be critical for preventing further outbreaks at the community level.

Investigation of Pathogenic Escherichia coli Contamination of Vegetables Distributed in a Korean Agricultural Wholesale Market.

The purpose of this study was to investigate the monthly contamination rate of pathogenic Escherichia coli, a major cause of food poisoning, in vegetables sold in agricultural wholesale markets, which distribute vegetables from all over the country, in the Incheon Metropolitan City area, South Korea, and to identify a source of the pathogen. In total, 1739 vegetables of 80 types, along with 109 soil, 67 manure, and 33 livestock feces samples, were tested for pathogenic E. coli using polymerase chain reaction, from September 2016 through August 2017. The average annual prevalence rate of vegetables was 5.8%, and the prevalence rate was above 5% from June through October. The highest prevalence rate (15.7%) was recorded in July. Water dropwort showed the highest prevalence rate (28.6%) among the vegetables examined. Pathogenic E. coli was detected in >20 types of the vegetables that were to be consumed without cooking. Among these, the prevalence rates of ponytail radish (n = 21), crown daisy (n = 86), young radish (n = 68), romaine lettuce (n = 133), perilla leaf (n = 103), Korean leek (n = 43), young Chinese cabbage (n = 68), and Chinese cabbage (n = 30) were 9.5%, 8.1%, 7.4%, 6.8%, 4.9%, 4.7%, 4.4%, and 3.3%, respectively. Among the vegetables cooked before consumption, prevalence rates were 28.6%, 27.3%, and 25.0% in wormwood, sweet potato stalk, and edible mountain vegetables (Saussurea sp., etc.), respectively. In soil, manure, and livestock feces, 36.7%, 26.9%, and 90.6% prevalence rates were confirmed, respectively. This study confirmed the pathogenic E. coli contamination of vegetables to be consumed without cooking. Therefore, to produce agricultural products that do not induce food poisoning and are safe for consumption, it is important to develop a process for killing the pathogenic microorganisms and set up a sanitary environment for effectively managing compost. In addition, it is necessary to establish surveillance systems to monitor the production chain.

Energy trading efficiency in the US Midcontinent electricity markets

Efficient trading under wholesale market competition reduces an electric grid’s energy costs for meeting time- and location-dependent demands. We analyse energy trading efficiency by estimating three newly developed sets of energy price difference regressions interconnected by their common root of energy price level regressions. Using a sample of ~ 0.6 million hourly observations for 01/01/2014 to 10/31/2020, our estimation documents energy trading efficiency of the 10 local resource zones across 15 American states administered by the Midcontinent Independent System Operator (MISO). We find MISO’s zonal energy markets integrated across space (zone j vs. zone k for j ≠ k) and time (day-ahead market vs. real-time market). However, these markets exhibit inter-day energy prices differences that move with the fundamental drivers (e.g., day-ahead forecasts for natural gas price and zonal wind generation) of day-ahead energy prices and their forecast errors. Inter-zonal day-ahead energy price differences move with the fundamental drivers and their zonal variations. Inter-zonal real-time energy price differences increase with inter-zonal day-ahead energy price differences and depend on zonal variations of the fundamental drivers’ forecast errors. Our empirics yield two important policy implications. First, enhancing inter-day trading efficiency requires accuracy improvements in (a) day-ahead forecasts for natural gas price, zonal load levels, and zonal wind generation, and (b) day-ahead scheduling of zonal nuclear and must-run generation. Second, improving inter-zonal trading efficiency requires mitigating inter-zonal transmission congestion via transmission capacity expansion, generation investment and demand reduction in a load pocket, and virtual bidding for inter-zonal energy price differences.

Estimating the degree of market power in the vegetable market in Japan

AbstractTo adequately capture the market structure of vegetables in Japan, it is necessary to develop an oligopolistic model due to the potential market power of producers vs. retailers. We first estimate the market power between producers and retailers by extending the bilateral oligopoly model. Next, we evaluate the role of the wholesale market and its effect on economic welfare. Our results indicate that the wholesale market benefits both producers and consumers through a reduction in retail margins. This study contributes to the industrial organization literature by developing a bilateral oligopoly model and empirically measuring the wholesale market system in Japan.