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In recent years, algorithmic-based market manipulation in stock and power markets has considerably increased, and it is difficult to identify all such manipulation cases. This causes serious challenges for market regulators. This work highlights and lists various aspects of the monitoring of stock and power markets, using as test cases the regulatory agencies and regulatory policies in diverse regions, including Hong Kong, the United Kingdom, the United States and the European Union. Reported cases of market manipulations in the regions are examined. In order to help establish a relevant digital regulatory system, this work reviews and categorizes the indicators used to monitor the stock and power markets, and provides an in-depth analysis of the relationship between the indicators and market manipulation. This study specifically compiles a set of 10 indicators for detecting manipulation in the stock market, utilizing the perspectives of return rate, liquidity, volatility, market sentiment, closing price and firm governance. Additionally, 15 indicators are identified for detecting manipulation in the power market, utilizing the perspectives of market power (also known as pricing power or market structure), market conduct and market performance. Finally, the study elaborates on the current challenges in the regulation of stock and power markets in terms of parameter performance, data availability and technical requirements.

Product market power provides firms with comparative advantages through more persistent profitability and insulation from competitive threats. These advantages likely provide firms with the ability to engage in greater tax avoidance. We present evidence consistent with this hypothesis. We also show that firms mimic the tax outcomes of their product market leaders. Among firms with greater product market power and comparatively high cash tax avoidance, we find stock prices to be less informative and that investors require additional compensation for the risks associated with comparatively high cash tax avoidance. Our results survive numerous robustness tests. Overall, our results suggest that industry dynamics, particularly related to a firm's competitive position, play a meaningful role in corporate tax policy.

Thermal power generation technologies are widely used for electricity production, for heat provision in district or process heating systems, and for combined heat and power generation. In most cases, thermal technologies are heat driven and electricity is produced as a by‐product, thus resulting in a non‐flexible behaviour of the electricity production. Modern power grids are characterised by an increasing share of renewable leading to a need for enhanced and flexible ways of controlling the power flow. To provide services to the power grid, thermal generating technologies may be used in a more efficient way, coupled to gas and heat storage systems or aggregated in virtual power plants. Several technical factors determine which technologies are suitable for flexibility provision, including power ranges, start up times and ramp rates. In this work, carried out in the frame of the MAGNITUDE H2020 project, the technical characteristics of thermal sector‐coupling technologies were analysed using data from the seven real‐life project's case studies. The technical suitability was determined based on the product requirements in selected European power markets for the provision of identified system services. Expected future developments and trends were highlighted well.

Energy storage and virtual power plant technologies have been developed and become important technical means to enhance power system stability and reduce real‐time dispatching costs. In this study, the dispatching capability and dispatching cost characteristics of the virtual power plants are analysed firstly in detail, as well as the dispatching difficulties under the traditional market modes. Hence, virtual power plant real‐time bidding package model and virtual auction‐based real‐time power market mechanism are proposed. Data‐driven virtual power plant real‐time packing method and bidding package model integrated virtual Vickrey–Clarke–Groves auction model are put forward. Finally, the feasibility and validity of the proposed mechanism and method are verified by case studies and result in analyses of the IEEE‐30 bus test system with multiple virtual power plants, providing a scientific foundation and a practical solution to the real‐time power market.

The burden of excess energy from the high renewable energy sources (RES) share creates a significant reduction of residual load for the future, resulting in reduced market prices. The higher the share of stochastic RES, the more often the price will be 0 €/MWh. The power market needs new methods to solve these problems. The development of virtual power plants (VPPs) is aimed at solving techno-economic problems with an increasing share of RES in the power market. This study analyses a possible implementation of stochastic and deterministic RES in a VPP to generate secured power, which can be implemented in the European Power Exchange (EPEX)/European Energy Exchange (EEX) power market using existing market products. In this study, the optimal economic VPP configuration for an RES-based power plant is investigated and implemented into standard power market products. The results show that the optimal economic VPP configuration for different market products varies, depending on the energy availability and the marginal costs of the VPP components. The size of the VPP components is positively correlated to the components’ share of the energy generated. It was also found that projecting or implementing VPPs in Germany at current market prices (EPEX/EEX prices) is not yet economically feasible for a small share of market products. However, the secured power can be marketed on the SPOT and in the futures market with higher and more stable prices compared with the status quo.

In the medium- and long-term market, the power generation side and the power purchase side ensure to avoid the fluctuation of delivery prices through the medium- and long-term power contract, to avoid some market risks. This paper combines virtual power plants to aggregate distributed renewable energy to participate in market transactions. Firstly, this paper analyzes the two operation modes of power markets and combs the transaction varieties and modes in the medium- and long-term market. Secondly, the common contract power decomposition methods in the medium- and long-term market are analyzed, and the revenue model of virtual power plants is established. Then, combined with the renewable energy quota system and the green certificate trading mechanism, this paper constructs an optimization model of medium- and long-term contract trading of virtual power plants considering renewable energy derivatives. Finally, different renewable energy output scenarios are designed to analyze the benefits of virtual power plants in centralized and decentralized power markets. The example analysis shows the effectiveness of price difference contract for virtual power plants to ensure the renewable power revenue, which provides a certain reference for virtual power plants to participate in the power market.

Under the background of “double carbon” goal and accelerating the construction of national unified power market system, new energy consumption and regional power market construction have become a research hotspot. Based on the trend of new energy development in China, this paper constructs a new energy consumption impact analysis model based on system dynamics. Based on the key factors affecting new energy consumption, we introduce the model of inter-regional contact line trend dispatchability to optimize the trading framework of the two-level power market, and finally put forward a two-layer optimization model of the market to promote new energy consumption. Based on the actual data, we investigate the changes of new energy consumption capacity after adopting the two-tier market optimization model. The final result is that the demand for purchased power decreases, the maximum load day decreases by 10.70%, the minimum load day decreases by 6.86%, and the new energy consumption increases from 81.79% to 95.39%, which proves that the two-tier optimization model is better than the traditional model to promote new energy consumption, and provides a reference for realizing the goal of “double carbon” and accelerating the construction of the nationwide unified power market system. It provides reference for realizing the goal of “double carbon” and accelerating the construction of national unified power market system.

We study the strategic utilization of storage in imperfect electricity markets. We apply a game-theoretic Cournot model to the German power market and analyze different counterfactual and realistic cases of pumped hydro storage. Our main finding is that both storage utilization and storage-related welfare effects depend on storage ownership and the operator's involvement in conventional generation. Strategic operators generally under-utilize owned storage capacity. Strategic storage operation may also lead to welfare losses, in particular if the total storage capacity is controlled by an oligopolistic generator that also owns conventional generation capacity. Yet in the current German situation, pumped hydro storage is not a relevant source of market power.

Market power is a multidisciplinary concept, bringing together aspects from law and economics, which are necessary to be understood in order to assess market situations with a global dimension. Globalization is an economic and social phenomenon which comes together with enhanced market power for global actors. Factors influencing or limiting market power, such as corporate social responsibility, are important to understand in order to assess market power situations. According to European Union Law, the concept of market power is reflected in abuse of dominance, which is an anti-competitive behavior prohibited in the Common Market of the EU, as defined in Article—102 of the Treaty on the Functioning of the EU. An interdisciplinary approach based on elements of law and economics is thus necessary when assessing market power of global actors.

In April 2003 the U.S. Federal Energy Regulatory Commission proposed a complicated market design--the Wholesale Power Market Platform ( WPMP )--for common adoption by all US wholesale power markets. Versions of the WPMP have been implemented in New England, New York, the mid-Atlantic states, the Midwest, the Southwest, and California. Strong opposition to the WPMP persists among some industry stakeholders, however, due largely to a perceived lack of adequate performance testing. This study reports on the model development and open-source implementation (in Java) of a computational wholesale power market organized in accordance with core WPMP features and operating over a realistically rendered transmission grid. The traders within this market model are strategic profit-seeking agents whose learning behaviors are based on data from human-subject experiments. Our key experimental focus is the complex interplay among structural conditions, market protocols, and learning behaviors in relation to short-term and longer-term market performance. Findings for a dynamic 5-node transmission grid test case are presented for concrete illustration. [PUBLICATION ABSTRACT]