Recently, power companies apply optimal algorithms for short-term load forecasting, especially the daily load. However, in Vietnam, the load forecasting of the power system has not focused on this solution. Optimal algorithms and can help experts improve forecasting results including accuracy and the time required for forecasting. To achieve both goals, the combinations of different algorithms are still being studied. This article describes research using a new combination of two optimal algorithms: Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). This combination limits the weakness of the convergence speed of GA as well as the weakness of PSO that it easily falls into local optima (thereby reducing accuracy). This new hybrid algorithm was applied to the Southern Power Corporation’s (SPC—a large Power company in Vietnam) daily load forecasting. The results show the algorithm’s potential to provide a solution. The most accurate result was for the forecasting of a normal working day with an average error of 1.15% while the largest error was 3.74% and the smallest was 0.02%. For holidays and weekends, the average error always approximated the allowable limit of 3%. On the other hand, some poor results also provide an opportunity to re-check the real data provided by SPC.

Photovoltaic and wind systems have been used for a few years to bring a new power supply to many applications, while preserving the environment. This chapter is interested in this work at low and medium power, a few 100 W, for applications to housing and buildings. The works consider a system in which the various sources of renewable energies are connected to each other in a parallel structure which supposes the use of specialized converters accepting at the input voltages of the order of a few tens of volts, and giving out several hundred of volts. The DC-DC converters with magnetic coupling will be analyzed more particularly to show the technological limits. In particular, the influence of the magnetic circuit and the leakage flows will be studied in more detail.

A lot of systems are basically developed on DC-DC or DC-AC converters including electronic switches such as MOS or bipolar transistors. The limits of efficiency are quickly reached when high output voltages and high input currents are needed. This work presents a new high-efficiency-high-step-up based on push-pull DC-DC converter integrating recovery stages dedicated to smart HVDC distributed architecture in PV solar energy production systems. Appropriate duty cycle ratio assumes that the recovery stage work with parallel charge and discharge to achieve high step-up voltage gain. Besides, the voltage stress on the main switch is reduced with a passive clamp circuit and thus, low on-state resistance R_dson of the main switch can be adopted to reduce conduction losses. Thus, the efficiency of a basic DC-HVDC converter dedicated to renewable energy production can be further improved with such topology. A prototype converter is developed, and experimentally tested for validation.

This paper presents a new high-efficiency-high-step-up based converter integrating two stype DC-DC Boost and Flyback coupled magnetic converter with recovery stage dedicated to smart HVDC distributed architecture in renewable energy production systems. Appropriate duty cycle ratio assumes that the recovery stage work with parallel charge and discharge to achieve high step-up voltage gain. Besides, the voltage stress on the main switch is reduced with a passive clamp circuit and thus, low on-state resistance Rdson of the main switch can be adopted to reduce conduction losses. The circuit is simple to control. As a final point of this research, the simulation and the prototype investigational results are presented to demonstrate the effectiveness of this proposed converter.

This chapter present one possible evolution is the parallel topology on the high-voltage bus for the renewable energy system. The system is not connected to a chain of photovoltaic (PV) modules and the different sources renewable. This evolution retains all the advantages of this system, while increasing the level of discretization of the Maximum Power Point Tracker (MPPT). So it is no longer a chain of PV modules that works at its MPPT but each PV module. In addition, this greater discretization allows a finer control and monitoring of operation and a faster detection of defects. The main interest of parallel step-up voltage systems, in this case, lies in the fact that the use of relatively high DC voltages is possible in these architectures distributed.