Search

The CLLC converter is often used as an isolated linker between high and low voltage buses where the CLLC converter operates under the open-loop condition at resonant frequency. In such applications, CLLC converters are able to achieve high efficiency usually due to superior performance of soft switching. However, we found that the operating process of a CLLC converter under open-loop control at the resonant frequency will significantly change by the non-ideal parameters of the semiconductor switches and gate driver circuits. These impacts on the converter operation were investigated and defined as the gate drive delay. We present a comprehensive steady-state analysis for the CLLC converter that considers the gate drive delay including its operating process, mathematical model, power loss, and voltage ripple. In some cases, the gate drive delay changes the operating process of the CLLC converter. As a result, the soft switching condition changes or even loses, large circulating current exists on the secondary side, output voltage ripples become larger and so that the efficiency decreases dramatically. Therefore, a hybrid compensation scheme, consisting of an offline design procedure and an online close-loop control algorithm, is proposed to minimize resonant frequency variation due to the gate drive delay. Both the correctness of the steady-state analysis and effectiveness of the proposed hybrid compensation scheme are verified by experiment. Using the proposed compensation scheme can reduce the output voltage ripple to 1/3 of the original value and increase the efficiency of more than 10% within the whole load range.

This paper presents and classifies a state of the art optimal dispatch review of combined heat and power plants (CHP) in integrated energy systems. Comparing the purposes of increasing renewable energy integration and profits of CHP operation, two groups of literatures, cost and market based optimal dispatch of CHP plants are studied. The flexibility in terms of reducing wind power curtailment and increasing revenue by providing ancillary service is discussed. A case study of optimal dispatch of a CHP plant under the heat market in Copenhagen, Denmark is proposed, where the flexibility is compared with different CHP unit types, operation modes and heat accumulators' integration.

In this paper, a state of the art review of model predictive control (MPC) for smart buildings to provide demand side flexibility with the purpose of enhancing a high penetration of renewables into the integrated energy systems is carried, including MPC current development status, pros and cons, implementation feasibility and practice barriers. A two-layer hierarchical MPC-based controller is proposed in a case study for a newly-built multi-family building in Copenhagen. The simulation results show that buildings, as a flexible load to the multi-carrier energy system, whose thermal mass is a heat buffer with a large storage potential, can contribute to the grid ancillary services (load shifting or flexibility), based on the economic incentives that the energy/flexibility market offers to end-users.

Smart energy system has been widely accepted as the key pathway for the application of clean energy towards low carbon society. It is normally considered as a portfolio of technologies integrated with energy generation, storage and application driven by information based control mechanism. From the historical review of technology development, the correlation between Energy and Information is first analyzed via the concept of entropy. A novel theoretical perspective of energy digitization is then proposed from analogous linkage between energy storage and data storage. A smart energy road-map is further derived to show how energy eco-system can be self-organized with energy intelligence that is quantifiable with clear physical meaning. In the end, Fractal structure based evolution is concluded to be the key stage for smart energy system, as it drives the fundamental principal between energy and information from proposed theoretical framework.

High-temperature electrolysis (HTE) is a promising technology for achieving high-efficiency power-to-gas, which mitigates the renewable curtailment by transforming wind or solar energy into fuels. Different from low-temperature electrolysis, a considerable amount of the input energy is consumed by auxiliaries in an HTE system for maintaining the temperature, so the studies on systematic description and parameter optimization of HTE are essentially required. A few published studies investigated HTE's systematic optimization based on simulation, yet there is not a commonly used analytical optimization model which is more suitable for integration with power grid. To fill in this blank, a concise analytical operation model is proposed in this paper to coordinate the necessary power consumptions of auxiliaries under various loading conditions of an HTE system. First, this paper develops a comprehensive energy flow model for an HTE system based on the fundamentals extracted from the existing work, providing a quantitative description of the impacts of condition parameters, including the temperature and the feedstock flow rates. A concise operation model is then analytically proposed to search for the optimal operating states that maximize the hydrogen yield while meeting the desired system loading power by coordinating the temperature, the feedstock flows and the electrolysis current. The evaluation of system performance and the consideration of constraints caused by energy balances and necessary stack requirements are both included. In addition, analytical optimality conditions are obtained to locate the optimal states without performing nonlinear programming by further investigating the optimization method. A numerical case of an HTE system is employed to validate the proposed operation model, which proves to not only improve the conversion efficiency but also enlarge the system load range., Comment: accepted by Applied Energy