An Advanced FMRL Controller for FACTS Devices to Enhance Dynamic Performance of Power Systems

The parameters of power system slowly change with time due to environmental effects or may change rapidly due to faults. It is preferable that the control technique in this system possesses robustness for various fault conditions and disturbances. The used flexible alternating current transmission system （FACTS） in this paper is an advanced super-conducting magnetic energy storage （ASMES）. Many control techniques that use ASMES to improve power system stability have been proposed. While fuzzy controller has proven its value in some applications, the researches applying fuzzy controller with ASMES have been actively reported. However, it is sometimes very difficult to specify the rule base for some plants, when the parameters change. To solve this problem, a fuzzy model reference learning controller （FMRLC） is proposed in this paper, which investigates multi-input multi-output FMRLC for time-variant nonlinear system. This control method provides the motivation for adaptive fuzzy control, where the focus is on the automatic online synthesis and tuning of fuzzy controller parameters （i.e., using online data to continually learn the fuzzy controller that will ensure that the performance objectives are met）. Simulation results show that the proposed robust controller is able to work with nonlinear and nonstationary power system （i.e., single machine-infinite bus （SMIB） system）, under various fault conditions and disturbances.

Computational Tools for the Integrated Design of Advanced Nuclear Reactors

Advanced nuclear reactors offer safe, clean, and reliable energy at the global scale. The development of such devices relies heavily upon computational models, from the pre-conceptual stages through detailed design, licensing, and operation. An integrated reactor modeling framework that enables seamless communication, coupling, automation, and continuous development brings significant new capabilities and efficiencies to the practice of reactor design. In such a system, key performance metrics （e.g., optimal fuel management, peak cladding temperature in design-basis accidents, levelized cost of electricity） can be explicitly linked to design inputs （e.g., assembly duct thickness, tolerances）, enabling an exceptional level of design consistency. Coupled with high-performance computing, thousands of integrated cases can be executed simultaneously to analyze the full system, perform complete sensitivity studies, and efficiently and robustly evaluate various design tradeoffs. TerraPower has developed such a tool-the Advanced Reactor Modeling Interface （ARMI） code system-and has deployed it to support the TerraPower Traveling Wave Reactor design and other innovative energy products currently under development. The ARMI code system employs pre-existing tools with strong pedigrees alongside many new physics and data management modules necessary for innovative design. Verification and validation against previous and new physical measurements, which remain an essential element of any sound design, are being carried out. This paper summarizes the integrated core engineering tools and practices in production at TerraPower.

Special Issue on New Concepts and Advances in Photocatalytic Materials for Sustainable Energy

The use of solar energy to drive the chemical and energy processes,and the chemical storage of solar energy are the key elements to move to a low-carbon economy,sustainable society and to foster energy transition.For this reason,there is a fast-growing scientific interest on this subject,which is part of the general effort for a solar-driven chemistry and energy,the chemistry of the future.To realize this

Advanced ocean wave energy harvesting:current progress and future trends

With a transition towards clean and low-carbon renewable energy,against the backdrop of the fossil-energy crisis and rising pollution,ocean energy has been proposed as a significant possibility for mitigating climate change and energy shortages for its characteristics of clean,renewable,and abundant.The rapid development of energy harvesting technology has led to extensive applications of ocean wave energy,which,however,has faced certain challenges due to the low-frequency and unstable nature of ocean waves.This paper overviews the debut and development of ocean wave energy harvesting technology,and discusses the potential and application paradigm for energy harvesting in the“intelligent ocean.”We first describe for readers the mechanisms and applications of traditional wave energy converters,and then discuss current challenges in energy harvesting performance connected to the characteristics of ocean waves.Next,we summarize the progress in wave energy harvesting with a focus on advanced technologies(e.g.,data-driven design and optimization)and multifunctional energy materials(e.g.,triboelectric metamaterials),and finally propose recommendations for future development.

Optimization of Operation Strategies for a Combined Cooling, Heating and Power System based on Adiabatic Compressed Air Energy Storage

The fluctuations of renewable energy and various energy demands are crucial issues for the optimal design and operation of combined cooling,heating and power(CCHP)system.In this paper,a novel CCHP system is simulated with advanced adiabatic compressed air energy storage(AA-CAES)technology as a join to connect with wind energy generation and an internal-combustion engine(ICE).The capital cost of utilities,energy cost,environmental protection cost and primary energy savings ratio(P E S R)are used as system performance indicators.To fulfill the cooling,heating and power requirements of a district and consider the thermal-electric coupling of ICE and AA-CAES in CCHP system,three operation strategies are established to schedule the dispatch of AA-CAES and ICE:ICE priority operation strategy,CAES priority operation strategy and simultaneous operation strategy.Each strategy leads the operation load of AA-CAES or ICE to improve the energy supply efficiency of the system.Moreover,to minimize comprehensive costs and maximize the P E S R,a novel optimization algorithm based on intelligent updating multi-objective differential evolution(MODE)is proposed to solve the optimization model.Considering the multi-interface characteristic and active management ability of the ICE and AA-CAES,the economic benefits and energy efficiency of the three operation strategies are compared by the simulation with the same system configuration.On a typical summer day,the simultaneous strategy is the best solution as the total cost is 3643 USD and the P E S R is 66.1%,while on a typical winter day,the ICE priority strategy is the best solution as the total cost is 4529 USD and the P E S R is 64.4%.The proposed methodology provides the CCHP based AA-CAES system with a better optimized operation.

Delphi Survey on China's Advanced Energy Technology towards 2035

Facing the multiple challenges of low-carbon transformation,China urgently needs to adopt a new energy development path.This study used the Delphi method combined with vision analysis to analyze the advanced energy fields and gain insights into the development trends of energy technology towards 2035.The Delphi survey convened 762 domestic experts to predict the development demands and trends of advanced energy technology,and to identify important technology topics.A key list,including 91 technology topics in 9 sub-fields,was analyzed with respect to promoting economic growth,improving quality of life,and safeguarding national security.Furthermore,we conducted a research on these technology topics in context of technology research and development(R&D)level,leading countries,technology realization possibility,and constraints.The results from the Delphi survey show that the R&D level of China’s advanced energy technology is still at an elementary stage,and China,significantly,lags behind the US and the EU in the fields of advanced energy.These results reveal that insufficient R&D investment is the primary factor restricting the technology development in China’s advanced energy,though human resources,infrastructure,regulations,policies and standards also play significant roles in restricting technology development.The results from the Delphi survey may serve as a reference and help in exploring the development path of low-carbon transformation and achieving goals for addressing climate change in China.

Risk Constrained Self-scheduling of AA-CAES Facilities in Electricity and Heat Markets:A Distributionally Robust Optimization Approach

Advanced adiabatic compressed air energy storage(AA-CAES)has the advantages of large capacity,long service time,combined heat and power generation(CHP),and does not consume fossil fuels,making it a promising storage technology in a low-carbon society.An appropriate self-scheduling model can guarantee AA-CAES’s profit and attract investments.However,very few studies refer to the cogeneration ability of AA-CAES,which enables the possibility to trade in the electricity and heat markets at the same time.In this paper,we propose a multimarket self-scheduling model to make full use of heat produced in compressors.The volatile market price is modeled by a set of inexact distributions based on historical data through-divergence.Then,the self-scheduling model is cast as a robust risk constrained program by introducing Stackelberg game theory,and equivalently reformulated as a mixed-integer linear program(MILP).The numerical simulation results validate the proposed method and demonstrate that participating in multienergy markets increases overall profits.The impact of uncertainty parameters is also discussed in the sensibility analysis.