Abstract:Multi-Area Multi-Fuel Economic Dispatch (MAMFED) aims to allocate the best generation schedule in each area and to offer the best power transfers between different areas by minimizing the objective functions among the available fuel alternatives for each unit while satisfying various constraints in power systems. In this paper, a Fuzzified Squirrel Search Algorithm (FSSA) algorithm is proposed to solve the single-area multi-fuel economic dispatch (SAMFED) and MAMFED problems. Squirrel Search Algorithm (SSA) mimics the foraging behavior of squirrels based on the dynamic jumping and gliding strategies. In the SSA approach, predator presence behavior and a seasonal monitoring condition are employed to increase the search ability of the algorithm, and to balance the exploitation and exploration. The suggested approach considers the line losses, valve point loading impacts, multi-fuel alternatives, and tie-line limits of the power system. Because of the contradicting nature of fuel cost and pollutant emission objectives, weighted sum approach and price penalty factor are used to transfer the bi-objective function into a single objective function. Furthermore, a fuzzy decision strategy is introduced to find one of the Pareto optimal fronts as the best compromised solution. The feasibility of the FSSA is tested on a three-area test system for both the SAMFED and MAMFED problems. The results of FSSA approach are compared with other heuristic approaches in the literature. Multi-objective performance indicators such as generational distance, spacing metric and ratio of non-dominated individuals are evaluated to validate the effectiveness of FSSA. The results divulge that the FSSA is a promising approach to solve the SAMFED and MAMFED problems while providing a better compromise solution in comparison with other heuristic approaches.

Abstract:Globally abundant wave energy for power generation attracts ever increasing attention. Because of non-linear dynamics and potential uncertainties in ocean energy conversion systems, generation productivity needs to be increased by applying robust control algorithms. This paper focuses on control strategies for a small ocean energy conversion system based on a direct driven permanent magnet synchronous generator (PMSG). It evaluates the performance of two kinds of control strategies, i.e., traditional field-oriented control (FOC) and robust adaptive control. The proposed adaptive control successfully achieves maximum velocity and stable power production, with reduced speed tracking error and system response time. The adaptive control also guarantees global system stability and its superiority over FOC by using a non-linear back-stepping control technique offering a better optimization solution. The robustness of the ocean energy conversion system is further enhanced by investigating the Lyapunov method and the use of a DC-DC boost converter. To overcome system complexity, turbine-generator based power take-off (PTO) is considered. A Matlab/Simulink study verifies the advantages of a non-linear control strategy for an Oscillating Water Column (OWC) based power generation system.

Abstract:In the light of user-side energy power control requirements, a power control strategy for a household-level EPR based on HES droop control is proposed, focusing on the on-grid, off-grid and seamless switching process. The system operating states are divided based on the DC bus voltage information with one converter used as a slack terminal to stabilize the DC bus voltage and the other converters as power terminals. In the on-grid mode, the GCC and the HES are used as the main control unit to achieve on-grid stable operation, whereas in the off-grid mode, the PV, HES and LC are used as the main control unit at different voltages to achieve stable operation of the island network. Finally, a DC MG system based on a household-level EPR is developed using the PSCAD / EMTDC simulation platform and the results show that the control strategy can effectively adjust the output of each subunit and maintain the stability of the DC bus voltage.

Abstract:This paper describes the integration of a photovoltaic (PV) renewable energy source with a superconducting magnetic energy storage (SMES) system. The integrated system can improve the voltage stability of the utility grid and achieve power leveling. The control schemes employ model predictive control (MPC), which has gained significant attention in recent years because of its advantages such as fast response and simple implementation. The PV system provides maximum power at various irradiation levels using the incremental conductance technique (INC). The interfaced grid side converter of the SMES can control the grid voltage by regulating its injected reactive power to the grid, while the charge and discharge operation of the SMES coil can be managed by the system operator to inject/absorb active power to/from the grid to achieve the power leveling strategy. Simulation results based on MATLAB/Simulink® software prove the fast response of the system control objectives in tracking the setpoints at different loading scenarios and PV irradiance levels, while the SMES injects/absorbs active and reactive power to/from the grid during various events to improve the voltage response and achieve power leveling strategy.

Abstract:Power swing is an undesirable variation in power flow. This can be caused by large disturbances in demand load, switching, disconnection or reclosing lines. This phenomenon may enter the zones of distance relays and cause relay malfunction leading to the disconnection of healthy lines and undermining network reliability. Accordingly, this paper presents a new power swing detection method based on the prediction of current signal with a GMDH (Group Method of Data Handling) artificial neural network. The main advantage of the proposed method over its counterparts is the immunity to noise effect in signals. In addition, the proposed method can detect stable, unstable, and multi-mode power swings and is capable of distinguishing them from the variety of permanent faults occurring simultaneously. The method is tested for different types of power swings and simultaneous faults using DIgSILENT and MATLAB, and compared with some latest power swing detection methods. The results demonstrate the superiority of the proposed method in terms of response time, the ability to detect power swings of different varieties, and the ability to detect different faults that may occur simultaneously with power swings.

Abstract:With the rapid growth of China’s construction industry, energy demand and energy saving for building heating and cooling are of great importance [1]. In the year 2019, significant achievements were made in the development and use of geothermal energy in China. By the end of 2019, the construction areas with shallow geothermal energy applied had reached around 841 million square meters in China, ranking first in the world. Among the shallow geothermal energy technologies, ground source heat pumps (GSHPs) have the advantages of energy saving, high efficiency, environmental protection, and cleanliness, and consequently, they are widely used in building HVAC applications. Consuming low electric power, the technology of GSHPs can transfer low-temperature thermal energy to high-temperature thermal energy. With this technology, reservoirs in shallow ground layers, including soil formation, aquifers or lakes, etc., can be used as the heat source for heating in winter, or as the heat sink for cooling in summer. From 2020, the development and use of geothermal energy in China is showing wide application prospects, featured by the large-scale development of shallow geothermal heating (cooling), the promotion of a commercial development mode of medium and deep geothermal heating, and the wide application of “geothermal energy +” [2].

Abstract:To enhance the robustness and dynamic performance of a self-excited induction generator (SEIG) used in a stand-alone wind energy system (WES), a virtual flux oriented control (VFOC) based on nonlinear super-twisting sliding mode control (STSMC) is adopted. STSMC is used to replace the conventional proportional-integral-Fuzzy Logic Controller (PI-FLC) of the inner current control loops. The combination of the proposed control strategy with space vector modulation (SVM) applied to a PWM rectifier brings many advantages such as reduction in harmonics, and precise and rapid tracking of the references. The performance of the proposed control technique (STSMC-VFOC-SVM) is verified through simulations and compared with the traditional technique (PI-FLC-VFOC-SVM). It shows that the proposed method improves the dynamics of the system with reduced current harmonics. In addition, the use of a virtual flux estimator instead of a phase-locked loop (PLL) eliminates the line voltage sensors and thus increases the reliability of the system.

Abstract:With the increase in the proportion of multiple renewable energy sources, power electronics equipment and new loads, power systems are gradually evolving towards the integration of multi-energy, multi-network and multi-subject affected by more stochastic excitation with greater intensity. There is a problem of establishing an effective stochastic dynamic model and algorithm under different stochastic excitation intensities. A Milstein-Euler predictor-corrector method for a nonlinear and linearized stochastic dynamic model of a power system is constructed to numerically discretize the models. The optimal threshold model of stochastic excitation intensity for linearizing the nonlinear stochastic dynamic model is proposed to obtain the corresponding linearization threshold condition. The simulation results of one-machine infinite-bus (OMIB) systems show the correctness and rationality of the predictor-corrector method and the linearization threshold condition for the power system stochastic dynamic model. This study provides a reference for stochastic modelling and efficient simulation of power systems with multiple stochastic excitations and has important application value for stability judgment and security evaluation.

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Abstract:With the continuous expansion of power systems and the application of power electronic equipment, forced oscillation has become one of the key problems in terms of system safety and stability. In this paper, an interline power flow controller (IPFC) is used as a power suppression carrier and its mechanism is analyzed using the linearized state-space method to improve the system damping ratio. It is shown that although the IPFC can suppress forced oscillation with well-designed parameters, its capability of improving the system damping ratio is limited. Thus, combined with the repetitive control method, an additional repetitive controller (ARC) is proposed to further dampen the forced power oscillation. The ARC control scheme is characterized by outstanding tracking performance to a system steady reference value, and the main IPFC controller with the ARC can provide higher damping, and further reduce the amplitude of oscillations to zero compared with a supplementary damping controller (SDC). Simulation results show that the IPFC with an ARC can not only greatly reduce the oscillation amplitude, but also actively output the compensation power according to the reference value of the ARC tracking system.