@article{liu_tang_2024, title={Multi-objective bi-level programs for optimal microgrid planning considering actual BESS lifetime based on WGAN-GP and info-gap decision theory}, volume={89}, ISSN={["2352-1538"]}, DOI={10.1016/j.est.2024.111510}, abstractNote={With the rapid development of society and economy, random and intermittent renewable energy such as wind and photovoltaic (PV) generation is connected to the grid on a large scale. At the same time, forecasts of renewable energy output and loads are imprecise. These factors together lead to the uncertainty of power systems increasingly showing the characteristics of Knightian uncertainty, which makes the optimal microgrid planning and operation very challenging. Firstly, to overcome the shortcoming of the Monte Carlo method and the Latin hypercube method that require prior knowledge of the probability distributions of renewables and loads, this paper proposes a typical scenario generation methodology for renewables and loads based on Wasserstein generative adversarial networks with gradient penalty (WGAN-GP) and K-medoids. Secondly, optimal multi-objective bi-level microgrid planning models considering the actual battery energy storage system (BESS) lifetime based on WGAN-GP and info-gap decision theory under opportuneness and robustness strategies are established in this paper to effectively resolve the Knightian uncertainty of optimal microgrid planning and operation caused by the uncertain nature of wind, PV generation, and loads. Then, the multi-objective bi-level models are converted into multi-objective single level models. The Pareto-optimal front of these multi-objective problems are obtained by the ϵ-constraint method, and the compromised solution of the Pareto-optimal set is determined by fuzzy decision making. Finally, the proposed models are analyzed on the Banshee microgrid and verified by the Monte Carlo simulation. A bunch of results based on cases studies are obtained. For example, under the opportuneness strategy, when the opportunistic level factor equals 0.20 and the radii of the uncertainties of wind, PV generation, and loads are 0.0625, 0, and 0.2298, respectively, the planning cost of the microgrid does not exceed $2048k. This case reduces the cost by 20% compared to deterministic planning. All results of case studies prove the reliability, feasibility, and effectiveness of the proposed models.}, journal={JOURNAL OF ENERGY STORAGE}, author={Liu, Hualong and Tang, Wenyuan}, year={2024}, month={Jun} }
 @misc{liu_tang_2023, title={Quantum computing for power systems: Tutorial, review, challenges, and prospects}, volume={223}, ISSN={["1873-2046"]}, DOI={10.1016/j.epsr.2023.109530}, abstractNote={As a large number of renewable energy resources are connected to power systems, the operation, planning, and optimization of power systems have been becoming more and more complex. Power flow calculation, unit commitment, economic dispatch, energy pricing, and power system planning are essentially computation problems. A lot of computing resources are required for these problems, which are non-trivial, especially for large-scale power systems with the high penetration of renewable energy. Traditionally, the calculation and optimization of power systems are completed by classical computers based on the classical computing theory and the von Neumann architecture. However, with Moore's law getting closer and closer to the limit, the importance of quantum computing has become increasingly prominent. Quantum computing has been applied to some fields to a certain extent, yet the applications of quantum computing in power systems are rare. As the power industry is the foundation of the national economy, introducing quantum computing into the power system has far-reaching and crucial significance, such as improving the penetration of renewable energy, enhancing the computing efficiency, and helping in achieving the goal of net zero and climate neutrality by 2050. This paper first introduces the core concepts, essential ideas and theories of quantum computing, and then reviews the existing literature on the applications of quantum computing in power systems, and puts forward our critical thinking about the applications of quantum computing in power systems. In brief, this paper is dedicated to a tutorial on quantum computing targeting power system professionals and a review of its applications in power systems. The main contributions of this paper are: (1) introduce quantum computing into the field of power engineering in a thoroughly detailed way and delineate the analysis methodologies of quantum circuits systematically without losing mathematical rigor; (2) based on Dirac's notation, the related formulae are derived meticulously with sophisticated schematic diagrams; (3) elaborate and derive some critical quantum algorithms in depth, which play an important role in the applications of quantum computing in power systems; (4) critically summarize and comment on the existing literature on the applications of quantum computing in power systems; (5) the future applications and challenges of quantum computing in power systems are prospected and remarked.}, journal={ELECTRIC POWER SYSTEMS RESEARCH}, author={Liu, Hualong and Tang, Wenyuan}, year={2023}, month={Oct} }