Analysis, Control and Optimal Operations in Hybrid Power Systems

Hybrid power system (HPS) is an electricity generation system combining renewable energy resources and conventional generators. Several components will be utilized in a hybrid power system namely as: conventional generators (diesel generator, synchronous generator, DC generator for field excitation of synchronous generator), renewable energy resources (such as wind generator, photovoltaic system, etc.), power electronic converter, components’ controller, and also a supervisory control system to control the whole power system. In this chapter, an overview of hybrid power system and a brief description of important possible parts of a hybrid power system is introduce.

A study of the conditions for sustaining signals in a loop shows that loop equations are essentially fixed-point equations over a space of functions, with the loop performing a mapping on that space of functions. When the space of functions is specified, one can derive particular conditions for the loop has a solution. Barkhausen conditions fall in this category. Loops composed of two subsystems are in the first place analyzed. The purpose of the chapter is to put into a general perspective the problems of loops, showings the general conditions that must be satisfied. The analysis aims to clarify several perspectives on and the framework of loops operation.

This chapter deals with a new problem of physical correctness detection in the area of strictly causal system representations. The starting point is energy and the assumption that a system can be represented by a proper interconnection. The interconnection or, better, the interaction between physical systems can be described in terms of power exchange through power ports. The proposed approach to the problem solution is based on generalization of Tellegen’s theorem well known from electrical engineering. Consequently, mathematically as well as physically correct results are obtained. The contribution is mainly concerned with presentation of a new structural approach to analysis and synthesis of linear and nonlinear causal systems. It has been proven that complete analysis of system behavior reduces to two independent tests: the monotonicity test of abstract state space energy and that of complete state observability, eventually of its dual, i.e., complete state controllability property. For comparison, the example of port-Hamiltonian approach is also presented.

This chapter presents a linearized Phillips–Heffron model of a parallel AC/DC power system in order to studying power system stability. In addition, a supplementary controller for a modeling back-to-back voltage source converter (BtB VSC) HVDC to damp low-frequency oscillations in a weakly connected system is proposed. Also, input controllability measurement for BtB VSC HVDC is investigated using relative gain array (RGA), singular value decomposition (SVD) and damping function (DF) and a supplementary controller is designed based on phase compensating method. In addition, a supplementary controller for a novel modeling VSC HVDC to damp low-frequency oscillations in a weakly connected system is proposed. The potential of the VSC HVDC supplementary controllers to enhance the dynamic stability is evaluated by measuring the electromechanical controllability through SVD analysis. The presented control scheme not only performs damping oscillations but also the voltage and power flow control can be achieved. Simulation results obtained by MATLAB verify the effectiveness of the VSC HVDC and its control strategy for enhancing dynamical stability. Moreover, a linearized model of a power system installed with a UPFC has been presented. UPFC has four control loops that, by adding an extra signal to one of them, increases dynamic stability and load angle oscillations are damped. To increase stability, a novel online adaptive controllers have been used analytically to identify power system parameters. Suitable operation of adaptive controllers to decrease rotor speed oscillations against input mechanical torque disturbances is confirmed by the simulation results.

The Unified Power Flow Controller (UPFC) is regarded as one of the most versatile devices in the FACTS device family which has the ability to control the power flow in the transmission line, improve the transient stability, mitigate system oscillation, and provide voltage support. In this book chapter, the problem of UPFC based damping controller is formulated as an optimization problem which is solved using classic and Quantum-behaved Particle Swarm Optimization technique (QPSO). Two different objective functions are proposed in this work for the UPFC based damping controller design problem. The first objective function is the eigenvalues based comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes, while the second is the time domain-based multi-objective function. The performance of the proposed controllers under different disturbances and loading conditions is investigated for a single machine infinite bus and multi-machine power systems. The results of the proposed controllers are demonstrated through eigenvalue analysis and nonlinear time domain simulation.

TNEP is one of the important parts of power system planning which determines the number, time, and location of new lines for adding to transmission network. It is a hard, large-scale and highly nonlinear combinatorial optimization problem that can be solved by classic, nonclassic or heuristic methods. Classic methods like linear programming and Bender decomposition are only based on mathematical principles, but their difficulty is that if the scale of problem is large, it is very difficult to find accurate and reasonable solutions. Contrary to classic methods, nonclassic ones such as evolutionary algorithms like GAs are not based on mathematical rules and simply can be applied for solution of complex problems. GA is a random search method that has demonstrated the ability to deal with nonconvex, nonlinear, integer-mixed optimization problems like the STNEP problem. Although global optimization techniques like GA to be good methods for the solution of TNEP problem, however, when the system has a highly epistatic objective function and number of parameters to be optimized is large, then they have degraded efficiency to obtain global optimum solution and also simulation process use a lot of computing time. Heuristic methods like PSO can improve speed and accuracy of the solution program. PSO is a novel population-based heuristic that is a useful tool for engineering optimization. Unlike the other heuristic techniques, it has a flexible and well-balanced mechanism to enhance the global and local exploration abilities. In this chapter, first we review some research in the field of TNEP. Then, the method of mathematical modeling for TNEP problem is presented. Afterward, GA and PSO algorithms are described completely. Finally, effective parameters on network losses with a few examples are introduced.

This chapter analyses the control of the Hybrid Power Sources (HPS) based on some applications performed. Usually, a HPS combines two or more energy sources that work together with the Energy Storage Devices (ESD) to deliver power continuously to the DC load or to the AC load via the inverter system. In the automotive applications, the ESD stack can be charged from the regenerative braking power flow or from other power sources like the thermoelectric generator or the renewable source. The last may have a daily variable power flow such as the photovoltaic panels integrated into a car’s body or into buildings. In the first section, an efficient fuel cell/battery HPS topology is proposed for high power applications to obtain both performances in energy conversion efficiency and fuel cell ripple mitigation. This topology uses an inverter system directly powered from the appropriate Polymer Electrolyte Membrane Fuel Cell (PEMFC) stack that is the main power source and a buck Controlled Current Source (buck CCS) supplied by a batteries stack, which is the low power auxiliary source. The buck CCS is connected in parallel with the main power source, the PEMFC stack. Usually, the FC HPS supply inverter systems and PMFC current ripple normally appear in operation of the inverter system that is grid connected or supply the AC motors in vehicle applications. The Low Frequency (LF) ripple mitigation is based on the active nonlinear control placed in the tracking control loop of the fuel cell current ripple shape. So the buck CCS will generate an anti-ripple current that tracks the FC current shape. This anti-ripple current is injected into the output node of the HPS to mitigate the inverter current ripple. Consequently, the buck CCS must be designed in order to assure the dynamic requested in the control loop. The ripple mitigation performances are evaluated by some indicators related to the LF harmonics mitigation. It is shown that good performances are also obtained with the hysteretic current—mode control, but the nonlinear control has better performances. The nonlinear control of the buck CCS is implemented based on a piecewise linear control law. This control law is simply designed based on the inverse gain that is computed to give a constant answer for all levels of the LF current ripple. The control performances are shown by the simulations performed. Finally, the designed control law will be validated using a Fuzzy Logic Controller (FLC). In the second and the third section is proposed and analysed a nonlinear control for FC HPS based on bi-buck topology that further improves FC performance and its durability in use in the low and medium power applications. The nonlinear voltage control is analysed and designed in the second section using a systematic approach. The design goal is to stabilise the HPS output voltage. This voltage must have a low voltage ripple. Additionally, the power spectrum of this ripple must be spread in a wide frequencies band using an anti-chaos control. All the results have been validated with several simulations.