Operation and evaluation of digitalized retail electricity markets under low-carbon transition: recent advances and challenges

With the growth of electricity consumers purchasing green energy and the development of digital energy trading platforms, the role of digitalized retail electricity markets in the low-carbon transition of electric energy systems is becoming increasingly crucial. In this circumstance, the research work on retail electricity markets needs to be further analyzed and expanded, which would facilitate the efficient decision-making of both market players and policymakers. First, this paper introduces the latest developments in the retail electricity market under low-carbon energy transition and analyzes the limitations of the existing research works. Second, from three aspects of power trading strategy, retail pricing methodology, and market risk management, it provides an overview of the existing operation and mechanism design strategies of the retail electricity market; then, it provides a systematic introduction to the evaluation system and monitoring methodology of electricity markets, which is not sufficient for the current digitalized retail electricity markets. Finally, the issues regarding operation evaluation and platform optimization of the current digitalized retail electricity market are summarized, and the research topics worth further investigations are recommended

A hybrid adaptive-prediction maximum power point tracking method for the smart city with massive photovoltaic

The partial shadow condition seriously affects the efficiency of the photovoltaic system in the modern city with dense built and other occlusions. From this, the characteristic curve of the photovoltage system shows multi-peak, which further increases the difficulty of getting photovoltaic systems to operate at maximum efficiency. As an efficient technique, the intelligent optimized maximum power point tracking method relies on initialization information and is difficult to balance the tracking performance. Therefore, a hybrid adaptive-prediction maximum power tracking method is proposed in this paper. Firstly, the neighborhood range of the maximum power points is located by the fuzzy predicted mechanism at the upper layer. Secondly, on the bottom layer, based on improving the Cuckoo search algorithm, the proposed method uses an interpolation function fitting curve to guide the particles to converge accurately on the bottom layer. At the same time, the output voltage of the system under an open loop is directly controlled by the duty cycle of the control signal, which improves the universality of the method. Finally, the simulation results show that the proposed method is superior to other advanced methods in tracking speed and with smaller power oscillations and comparable tracking accuracy, for which the proposed method is suitable for the city with complex environments and dense buildings

Construction of Near-Zero-Carbon Manufacturing System under the Carbon Border Adjustment Mechanism

The carbon peaking and carbon neutralization goals as well as the carbon trading system reforms of the European Union (EU) necessitate the synergy of energy conservation, pollution control, and carbon reduction in China to achieve low- and zero-carbon transformation of its manufacturing industry. This study focuses on the impact of the EU Carbon Border Adjustment Mechanism on China’s manufacturing industry, clarifies the concept of a near-zero-carbon manufacturing system, and elaborates on its core content from the major dimensions of key technologies, measurement basis, and market driving force. It also proposes the technical development directions of the near-zero-carbon manufacturing system from the aspects of product manufacturing and power supply and suggests the establishment of a source-grid-load carbon measurement system to clarify carbon emission responsibilities. Moreover, the future development path for China’s carbon market is explored after reviewing the carbon markets both in China and abroad. The practical solutions proposed by the study is expected to provide a basic reference for promoting the high-quality development and low-carbon transformation of China’s manufacturing industry

An optimal scheduling of renewable energy in flexible interconnected distribution networks considering extreme scenarios

Abstract As renewable power penetration gradually increases in hierarchical distribution networks, certain regions have started to lack the ability to consume. How to improve the consumption capacity of a hierarchical distribution network through optimal dispatching has become a hot topic in the current research on distribution system operation. Firstly, the article makes an accurate and rapid assessment of the consumption capacity of the station area through the limit scenario analysis method; secondly, based on the assessment results, the main network renewable power sources are prioritized for consumption, while the main network and the station area; thirdly, the main network renewable power sources are prioritized for consumption, considering the assessment results while the main network and the station area reach the optimal power flow simultaneously through a multi‐layer dispatching model. Then, through the flexible interconnection system, load balancing and energy optimization are performed for unconsumed distributed generation (DG) and incomplete energy storage system (ESS) in the station area to further improve the efficiency of renewable energy. Finally, the effectiveness of the proposed model is verified by simulation tests