会议速递 | IEEE出版+EI检索+珠海旅游！第8届国际能源互联网大会（ICEI 2024）诚邀全球同行投稿参会

With the increasing penetrations of renewable energy generations, the sustainable development of power systems around the global are facing new challenges in term of planning and operations. Wind and solar energy are the major driving force for the development, but also introduced uncertainties, changed the system dynamics, and revised the operation principles. These impacts are on all voltage levels in power systems and at multiple side, including the large-scale renewable generations in bulk grid and distributed generations in distribution system before and behind the meters. In the foreseeable future, the sustainable development of power system will fundamentally change how the power engineering approach the system and how the people use the electricity.

In recent years, the fascinating progress in artificial intelligence research has attracted wide attentions. This also provides a potential solution direction for the power systems development. Numerous studies have been published in scientific journals in terms of the applications of artificial intelligence in power systems planning and operations considering renewable energy penetrations. However, there is still a gap between the theoretical research in academia and the challenges faced by engineers in power industry. The majority of current machine learning algorithms are originally designed for the tasks in computer science and engineering field. As a result, the performance, efficiency, reliability, interpretability of the machine learning algorithms is not optimized for power system applications. In this special session, we are aiming to bridge this gap with new advances in the applications of artificial intelligence in power systems planning and operations.

Topics of interest include, but are not limited to:

1. Knowledge-Data complementary framework in power system planning and operations

2. Model-Data combined driven technology in power system planning and operations

3. Physical informed Neural networks in power system planning and operations

4. Human-in-the-loop artificial intelligence framework for power system planning and operations

5. Deep learning-based renewable energy generation estimations and available power analysis

6. Deep reinforcement learning-based power system operations

7. Meta learning in power system planning and operations

8. Artificial intelligence-based power system market and multi-agent games

9. Artificial intelligence-based power system stability analysis and control

10. Explainable machine learning in power systems planning and operations

11. Other advances in sustainable development of power systems with artificial intelligence

The transformation of the energy supply and demand pattern profoundly changes the form and structure of the power system, and the characteristics of ‘high proportion of renewable energy’ and ‘high proportion of power electronic equipment’ in the power system are becoming increasingly prominent, bringing new challenges to the security and stable operation. The operating characteristics of the system are mainly influenced by the control of power electronic equipment, significant changes have occurred in the stability mechanism, operating characteristics, and control methods. Renewable power sources, high-voltage direct-current transmission stations, and other power electronics equipment make it more difficult to acquire proper modelling and efficient methods for stability analysis. Power systems worldwide frequently encountered stability problems introduced by renewable power generators that have not encountered nor noticed before. Quantitatively estimating and enlarging the stability region of the power system is becoming a key challenge in the planning, operation, and control, which is of great significance for accelerating the low-carbon and clean transformation of the national energy system. Therefore, it is timely demanded for stability analysis and control of hybrid AC/DC power systems with high penetration of renewable energy. In this special session, the major objective is to share novel research results and interesting ideas in fields of security and stability analysis, active support control, and fault ride-through strategy for hybrid AC/DC power systems with high penetration of renewable energy.

Topics of interest include, but are not limited to:

1. Modeling and Simulation of hybrid AC/DC power systems with high penetration of renewable energy；

2. Analysis method for security and stability of hybrid AC/DC power systems with high penetration of renewable energy

3. Active support control method for renewable energy power generation and HVDC transmission;

4. Fault characteristic analysis and ride through control of hybrid AC/DC power systems with high penetration of renewable energy;

5. Interaction between converter control modes and power system transient stability.

With the continuous increase of the proportion of new energy connected to the grid, the frequency response ability of power systems is seriously lacking, and the spatial and temporal distribution characteristics are significant, which make the frequency security situation increasingly severe. The traditional single-unit power system frequency response analysis model is no longer able to satisfy the frequency analysis requirements of new power system development trend due to numerous limiting factors. Therefore, it is necessary to explore more accurate and efficient frequency response analysis models in frequency response analysis methods, as well as to explore resources that can improve the frequency response ability of power systems in regulation methods.

This Special Session is based on this to conduct extensive studies, aiming to gather experts and scholars in related fields to exchange ideas and jointly improve the frequency security and stability levels of new power systems.

Topics of interest include, but are not limited to:

1. Modeling, evaluation, mechanism analysis, and optimization control of frequency security in new power systems;

2. Optimization control and configuration strategies of new power systems considering frequency dynamic characteristics;

3. Optimization configuration, dispatch, and control strategies for flexible resources such as energy storage and virtual power plants to participate in frequency response;

4. Coordination control of multi-type resources for providing frequency regulation in new power systems;

5. Multi-temporal and -spatial couplings and wide-area control technology for inertia-power-frequency in new power systems;

6. Power-electricity balancing and inter provincial mutual aid coordination dispatch for multi-level power grids;

7. Market mechanism for frequency security in new power systems.

With the continuous growth in energy demand and the rapid development of renewable energy, load regulation has become a crucial means of balancing supply and demand and enhancing power grid reliability. Energy-intensive industries, due to their large power consumption and flexible production processes, have significant advantages in load regulation. Through intelligent control methods, these industrial loads can dynamically adjust according to the needs of the power system, thereby reducing peak loads and increasing the utilization of off-peak loads. This not only helps improve energy efficiency and reduce energy costs but also facilitates the integration of renewable energy, contributing to global energy transition and low-carbon development goals.

In recent years, achieving energy conservation, carbon reduction, and coordinated supply-demand interaction in energy-intensive industries is important. During process design and energy-saving retrofits, insufficient consideration is given to variable operating conditions triggered by supply-demand interactions, which can lead to issues such as safety risks and reduced energy efficiency. Furthermore, the lack of fully coordinated grid-load interaction technology limits the full release of their significant regulation potential. Additionally, the absence of effective market mechanisms and incentive measures results in low participation willingness from enterprises in supply-demand interactions. To effectively resolve these conflicts, breakthroughs are urgently needed in four areas: modeling and adjustable capacity prediction for energy-intensive industries, energy-carbon efficiency co-optimization, multi-timescale supply-demand interaction, and electricity-carbon collaborative incentive mechanisms. In this special session, our main objective is to share the latest research findings and innovative ideas in areas such as grid-load interaction technology and market transaction strategies for energy-intensive industrial loads.

Topics of interest include, but are not limited to:

1. Modeling of electricity-carbon characteristics for energy-intensive industrial loads

2. Multi-energy load modeling for energy-intensive industries considering production processes

3. Assessment and prediction of reliable regulation capacity for energy-intensive industrial loads

4. Multi-energy coordinated optimization of energy-intensive industrial load operations

5. Multi-timescale interaction technologies for energy-intensive industrial loads participating in grid operations

6. Electricity-carbon collaborative market trading decision-making technology for energy-intensive industrial users

7. Incentive mechanisms for energy-intensive industrial users participating in grid interactions

This Special Session is concerned with the research on the key fundamental issues of low-carbon integrated energy systems (LCIESs) planning and operation under uncertainties, which consist of four parts: (1) Modeling of LCIESs, in inclusion of modeling the dynamic behaviors of various energy devices as well as their connections to form an IES model; (2) development of high-dimensional multi-objective stochastic optimization algorithms; (3) development of decision-making support for determination of the final optimal solution for the planning and operation of LCIESs under uncertainties, selected from the Pareto sets of the multi-objective optimization computation, and (4) mechanism design for distributed LCIES to participate in the electricity market under various interest entities.

The referred methods could be applied to plan a power network based LCIESs and investigate the economy and reliability of LCIESs under uncertainties, which could be achieved using distributed CHP and CCHP, heat storages, cool storages and hydrogen storages, and investigate the smooth peaks and valleys of power generation and loads, respectively.

This Special Session aims to publish high-quality, original research papers in the overlapping fields of:

1. Advanced Simulation Models of LCIESs: Leveraging big data and machine learning to develop next-generation simulation models that accurately represent the dynamics of low-carbon technologies within integrated systems,

2. Uncertainty Modeling: Focusing on characterizing the uncertainties of massive new energy sources like solar and wind power, and their impact on the stability and reliability of LCIES.

3. Optimization Techniques for Energy Efficiency: Exploring cutting-edge optimization algorithms that aim to maximize energy efficiency and minimize carbon emissions. 

4. Data-Enhanced Decision-Making Support: Covers the incorporation of data analytics into decision support tools to facilitate informed decision-making under uncertainty.

5. Coupling of Heterogeneous Energy Sources: Analyzing and optimizing the synergistic operations of various energy types within an IES to enhance overall system performance and energy efficiency.

6. Multi-Market Mechanism Design: Designing coupling mechanisms between different markets (e.g., electricity and carbon markets) to enhance the consumption rate of new energy sources and align with low-carbon goals.