Search Results (15)

With the continuous expansion of new energy installed capacity, the flexible regulation role of energy storage in the electricity spot market is becoming more and more prominent. However, traditional trading models often ignore the multiple trading preferences of energy storage. In this paper, we propose an electricity spot market trading model that considers the trading preferences of energy storage to incentivize energy storage to participate more actively in the market. First, the trading preferences of energy storage are modeled with a utility function in which the time preference coefficient and price elasticity are introduced. Then, the utility function is embedded into the spot market clearing model to establish a two-tier model of the spot market, which maximizes social welfare in the upper tier and maximizes energy storage benefits in the lower tier. Finally, the model is solved using KKT and large M methods, and its effectiveness is evaluated on the IEEE39 node system and on a real grid in a specific region. Full article

Building the regional electricity spot market (RESM) in a representative area is an important move to promote the electricity market reform and new power system construction in China. In this paper, the RESM operation model and optimization method are established, which take into account the special power grid operation mechanism and market construction achievements in the provincial electricity spot market. Firstly, the influencing factors, core elements, market structure, and operation model of RESM construction in China are analyzed. Secondly, a bi-level optimization model of the RESM is established. The lower layer is the pre-clearing model of the provincial electricity spot market, which is used to optimize the unit combination strategy, considering unit operation constraints and power grid security constraints in the province. The upper layer is the optimization clearing model of the RESM, which is used to optimize the clearing price and adjust the unit operation strategy and inter-provincial electricity trading strategy, considering the security constraints of regional power grid tie lines. Finally, the RESM composed of power grids in the Yangtze River Delta region of China is simulated as an example. The analysis focuses on the operational state of the power grid after the operation of the RESM, considering its safety benefits, economic benefits, and environmental benefits. The optimization of the RESM can effectively solve the serious regional power grid congestion problem, which is achieved through the superposition and printing of pre-clearing results in various provinces, and the average daily cost of electricity purchasing in the region has been reduced by about CNY 11 million, while the annual cost has been reduced by about CNY 4 billion. In addition, the total carbon emissions have been reduced by 11,000 tons per day and 0.18 kg per kilowatt hour on average, and scenes without power abandonment account for more than 95% of the total scenes. Full article

Motivated by the projected solar and wind capacity additions around the world, we model the energy procurement decision of a load serving entity (LSE) faced with alternatives of solar power purchase agreements (PPAs), wind PPAs, non-renewable energy forward contracts, and spot energy purchases in a wholesale electricity market with uncertain prices. Using a pseudo-data sample of over one million observations, we estimate a translog cost function to find that the LSE’s own-price elasticity estimates range from −1.87 for nighttime spot MWh demands to −13.1 for forward MWh demands. MWh demands are influenced by solar and wind capacity factors, daytime and nighttime retail sales, and spot energy price forecasts. The LSE’s optimal procurement of solar capacity is roughly twice the wind capacity, corroborating the ratios of projected solar and wind capacity additions in regions around the world. If the LSE’s existing energy mix is nearly all renewable, it becomes carbon-free when solar and wind power purchase agreements have declining energy prices or when forward energy price and spot energy price forecasts increase over time. These results imply that piecemeal policy measures can have conflicting outcomes, calling for integrated resource planning under wholesale market competition and price uncertainty. Full article

Security checks are essential for ensuring the safe operation of the regional power grid (RPG) and the smooth functioning of the electricity spot market (ESM). Currently, China’s RPG operating environment encompasses a complex mix of centralized ESM, decentralized ESM, and planned power generation. This complexity has led to increasingly severe RPG congestion issues. To address this, this paper introduces a security check mechanism design and operational optimization approach tailored for RPGs in complex markets, with a focus on congestion management. Firstly, the paper elaborates on the practical foundations, unique constraints, and requirements for security checks and congestion management during the RPG’s operational mode transitions. Secondly, it outlines the principles underlying the security check mechanism and presents a framework for RPG security checks and congestion management. Through a comparative analysis of three different programs, including their advantages, disadvantages, and applicable scenarios, the paper provides an optimal program recommendation. Building on this, the paper develops an operational optimization method that incorporates congestion management for each of the three security check and congestion management programs. Lastly, an IEEE-39 node test system is simulated to validate the effectiveness of the proposed programs. The mechanism and simulation analysis results show that Program 3, based on market mechanisms, has theoretical and practical advantages over Program 1 (based on multiple adjustments) and Program 2 (based on dispatch plans) for congestion management. Under the same line congestion situation, Program 1 requires two adjustments to relieve the line congestion, while Program 2 and Program 3 can solve the problem with just one optimization adjustment, and the congestion management effect of Program 3 is more obvious and superior. Full article

For several stakeholders, including market players, customers, grid operators, policy-makers, investors, and energy efficiency initiatives, having a precise estimate of power pricing is crucial. It is easier for traders to plan, purchase, and sell power transactions with access to accurate electricity price forecasting (EPF). Although energy production and consumption topics are widely discussed in the literature, EPF and renewable energy trading studies receive less attention, especially for intraday market modeling and forecasting. Considering the rapid development of renewable energy sources, the article highlights the significance of integrating the deep learning model, long short-term memory (LSTM), with the proper trading strategy for short-term hourly renewable energy trading by utilizing two different spot markets. Day-ahead and intraday markets are taken into account for the West Denmark grid region (DK1). The time series analysis indicates that LSTM yields superior results compared to other benchmark machine learning algorithms. Using the predictions obtained by LSTM and the recommended trading strategy, promising profit values are achieved for the DK1 wind and solar energy use case, which ensures future motivation to develop a general and flexible model for global data. Full article

Under the current power trading model, especially in the context of the large-scale penetration of renewable energy and the rapid integration of renewable energy into the power system, reasonable medium- and long-term decomposition can reduce the fluctuation in the energy price when the integrated energy service provider (IESP) participates in the spot market. It helps to avoid the price risk of the spot market. Additionally, it promotes the optimization of the operation of the regional energy day-ahead scheduling. At the present stage, most of the medium- and long-term contract decomposition methods focus on the decomposition of a single power and take less consideration of the bidding space in the spot market. This limitation makes it challenging to achieve efficient interaction and interconnection among multi-energy resources and smooth integration between the medium- and long-term market and the spot market. To address these issues, this paper proposes an optimal monthly contract decomposition method for IESPs that takes into account the equilibrium of spot bidding. First, the linking process and rolling framework of multi-energy transactions between the medium- and long-term market and the spot market are designed. Second, an optimal decomposition model for monthly contracts is constructed, and a daily decomposition method for monthly medium- and long-term contracts that accounts for the spot bidding equilibrium is proposed. Then, the daily preliminary decomposition result of medium- and long-term multi-energy contracts is used as the boundary condition of the day-ahead scheduling model, and the coupling characteristics of the multi-energy networks of electricity, gas, and heat are taken into account, as well as the operational characteristics. Then, considering the coupling characteristics and operating characteristics of electricity, gas, and heat networks, the optimal scheduling model of a multi-energy network is constructed to minimize the sum of cumulative daily operating costs, and the monthly final contract decomposition value and daily spot bidding space are derived. Finally, examples are calculated to verify the validity of the decomposition model, and the examples show that the proposed method can reduce the variance in spot energy purchase by about 4.64%, and, at the same time, reduce the cost of contract decomposition by about USD 0.33 million. Full article

China has made significant progress in developing renewable energy, but challenges in integrating variable sources like wind, solar, and hydro power persist. Existing research has a regional focus and lacks a comprehensive understanding of integration challenges in specific regions. Moreover, research concentrates on individual energy types rather than multiple sources. Addressing these challenges requires a deeper analysis of market rules, incentives, and mechanisms for integrating numerous renewable energy types. The existing research also overlooks crucial aspects like energy consumption, grid planning, and power market mechanisms. To promote renewable energy integration effectively, policymakers must address these interconnected factors through comprehensive investigations and research efforts. This study proposes tailored solutions to encourage integration in China based on international experiences, such as Brazil’s contract markets and electricity redistribution mechanism, the Nordic spot market, and California’s negative pricing mechanism. The strategies derived from global practices for China’s renewable energy integration include diverse trading mechanisms, expanded contract markets, optimized local consumption, fortified grid infrastructure, and improved market mechanisms. Full article

Modelling the energy price in the Australian National Electricity Market (NEM) requires features that are not well reflected in existing models. We present a semi-structural, multi-regional model wherein bidding is not required to be cost-based, renewable fuels and storage technology are structurally integrated, and network constraints are often binding in optimal dispatch. Available fuel capacity then does not necessarily sum to registered bid capacity, as-bid fuel costs do not dependably follow input fuel prices, and cross-regional interconnectedness requires modelling trade. Furthermore, modelling the NEM spot price path must admit price negativity and price spikes. Extending previous work in the literature, the present paper proposes a hyperbolic bid stack approach to price modelling under these conditions. Full article

Distributed energy resources aggregators (DERAs) are permitted to participate in regional wholesale markets in many counties. At present, new market players such as aggregators participate in China’s power market transactions. However, studies related to market trading strategy have mostly focused on centralized wind power and PV generation units. Few studies have been conducted on the decision-making strategies for DERAs in China’s power market. This paper proposes an auxiliary decision-making model for distributed energy systems to participate in the day-ahead market with more reasonable trading strategies. Firstly, the Gaussian mixture model (GMM) is used to deal with the uncertainties of wind power and photovoltaic (PV) output in the distributed energy system. Secondly, the information gap decision theory (IGDT) is used to deal with the uncertainty of price fluctuations in the spot electricity market. Thirdly, according to the different risk preferences of the DERAs facing market price fluctuation, the robust decision model and opportunity decision-making model in the day-ahead market are constructed, respectively. Finally, to deal with the irrational behavior of the DERAs’ perception of “gain” and “loss” with market risks in China’s two-tier market environment, the prospect theory and the marine predator’s algorithm (MPA) are employed to obtain a day-ahead trading decision scheme for DERA. The analyses show that RDES with robust preference can withstand greater price volatility in the day-ahead market; they will reduce the bidding expectations and increase the system operating cost to improve the achievability of the expected revenue. However, DERAs under the opportunity strategy is more inclined to sell electricity to the market and offset system operating costs with revenue. The proposed model can provide strategic reference for DERAs with different risk preferences to bid in day-ahead market and can improve the level of aggregators’ participation in electricity trading. Full article

Pumped-storage plants are the most significant electrical storage component in new power systems and show great potential for scaling up. In this paper, economic costs and benefits have been investigated. Both the costs and benefits can be divided into transmission and distribution tariffs; however, various factors need to be considered to reduce costs in transmission and distribution tariffs. The cost characterization methodology for pumped-storage power plants has been developed. A mathematical model for dispersal through the medium and long-term electricity market, the electricity spot market, the ancillary services market, and the leasing of capacity to scenic power stations has been proposed. A case study has been discussed for a regional grid company and a provincial grid company; also, the effectiveness of dispersal has been analyzed based on the case study. The results indicate that when the spot market and the capacity leasing of new energy sites play the largest role in the diversion, the transmission and distribution prices in Province A can be controlled within 1 cent/kWh by applying various diversion methods. Full article

Due to the intermittent and anti-peak shaving characteristics of the new energy generator sets, the phenomenon of power abandonment hinders direct participation in the electricity market transactions. The hybrid electricity market can use spot market transactions to absorb renewable energy to a large extent. The multi-energy complementary operation coupling of the hybrid electricity market transactions can exploit the complementation and substitution between different energy sources, realize flexible energy production, consumption, storage, and transmission, and optimize the allocation of resources on a larger scale. In this paper, a mid-long-term spot transaction coordination scheduling (MTCS) model for a multi-energy system is constructed by considering the medium- and long-term electricity market uncertainty and the trial operation characteristics of the spot power market in China. A two-stage solution method is introduced to solve the complex multi-agent, multi-period, and multi-energy model. The results of testing this model on the Gansu region, one of the first eight spot pilot areas in China, are presented and discussed in detail. The results showed that this MTCS model could reduce the opening of thermal power units to a more considerable extent, prioritize the consumption of new energy power generation, and reduce the output uncertainty of new energy through the hybrid power market. Full article

The shrimp industry in the Philippines plays a vital role in the local and national economy through exports to markets abroad such as South Korea, Japan, the USA, and others. In this study, we aimed to describe the various cultural and operational characteristics of smallholder and commercial shrimp (P. vannamei) farms in the Davao region. We also evaluated the current risks and challenges faced by the shrimp farmers. A semi-structured questionnaire that focused on shrimp farmers and operators in the region was used to collect data from N = 41 farmers and operators. The results showed that respondents who were engaged in smallholder farming activities had an average yield of 10 tons/ha. The commercial farms that operate intensively had an average yield of 24 tons/ha. Most smallholder operators used electric generator machines to conduct aeration in their farms using paddlewheels and blowers. More paddlewheels and blowers were employed per pond in the commercial farms compared to smallholder farms. Generally, the income of a farm was related to their yield or the number of fries rather than social factors or their size. In terms of input costs, feeds were found to have the highest cost, followed by the fry, fuel, labor, and others (fertilizers and water treatment chemicals). Most of the farmers mentioned that their shrimp are affected by diseases such as white spot syndrome (60%), black gills (35%), and red tail (5%). They perceived that the main contamination comes from the water source (31%). The main threats mentioned were declining shrimp prices in the market, source of fry, water disposal, overstocking, and water quality. This study shows that small-holding fish farmers should be supported by the government so that they can make use of the more advanced technology employed by commercial shrimp farmers in order to increase their economic productivity and lower their environmental footprint. Full article

Achieving a fully integrated energy market under the EU electricity target model constitutes an ongoing process. Given that the integration of spot markets is already at a mature stage, the next step forward is the successful integration of the balancing markets across European control areas. An analytical review of all the aspects governing the European balancing market integration is presented in this paper, providing a detailed description on the European regulatory framework on this topic. In addition, the design variables that need to be harmonized among national balancing markets as well as the available balancing market arrangements for the exchange of cross-border balancing services are presented. Numerical examples of the essence of the balancing market integration are provided, and the implementation projects initiated by European transmission system operators (TSOs) towards this direction are described. The review concludes that balancing market integration may indeed lead to a significant reduction in the balancing costs for the participating control areas, but further effort is still required to move from a regional level to a European-wide real-time balancing market, so that the whole potential of such a new landscape is revealed to the benefit of end-consumers. Full article

There is no natural inertia in a photovoltaic (PV) generator and changes in irradiation can be seen immediately at the output power. Moving cloud shadows are the dominant reason for fast PV power fluctuations taking place typically within a minute between 20 to 100% of the clear sky value roughly 100 times a day, on average. Therefore, operating a utility scale grid connected PV power plant is challenging. Currently, in many regions, renewable energy sources such as solar and wind receive feed-in tariffs that ensure a certain price for the energy. On the other hand, electricity markets operate on a supply-demand principle and a typical imbalance settlement period is one hour. This paper presents the energy, power and corresponding requirements for an energy storage system in a solar PV power plant to feed the power to the grid meeting the electricity spot markets practices. An ideal PV energy production forecast is assumed to be available to define reference powers of the system for the studied imbalance settlement periods. The analysis is done for three different PV system sizes using the existing irradiance measurements of the Tampere University of Technology solar PV power station research plant. Full article

The project CROME – cross-border mobility for electric vehicles – is the first European field demonstration introducing a standardised and interoperable cross-border charging infrastructure network in the French- German Upper Rhine region. The main aim of the project, funded by different Ministries on both sides of the border, is to create and test a safe, seamless, user-friendly and reliable mobility with electric vehicles between France and Germany. Fully public interoperable charging stations have been implemented ensuring easy access and charging of EVs all over the French and German CROME area. Solutions are developed and tested about charging services enabling simplified authentication, identification, billing as well as charging spot availability and reservation. The achieved CROME market place enables data exchanges and roaming between different operators ICT back-end systems based on the Bosch service brokering platform. Feedback on customer acceptance of e-mobility and user needs with regard to charging is carried out. Full article