2014 IEEE International Conference on Intelligent Energy and Power Systems (IEPS)
Control and Stabilization of Three-Phase Grid Connected Photovoltaics using PID-Fuzzy Logic Mohamed Louzazni, Elhassan Aroudam Team Modelling and Simulation of Mechanical Systems, Faculty of Sciences, University Abdelmalek Essaadi, Tetouan, Morocco
[email protected] system. This intelligent adaptive PID-fuzzy logic control is based on the combination of PID and fuzzy logic controller, and automatically varies the coefficients Kp, Ki and Kd which load change and uses directly the DC-DC converter duty cycle as a control parameter. This method has a high performance under rapidly changing atmospheric conditions, the effectiveness depended on the experience or knowledge of the right rule, input and output variables and the membership functions.
Abstract— The aims of this paper are to propose an intelligent hybrid control based in two methods of maximum power point tracking (MPPT) using fuzzy logic and classical PID controllers of a photovoltaic system under variable temperature and irradiance conditions, to improve the dynamic response, the efficiency and the stability of single stage three-phase photovoltaic grid-connected inverter. The combination of the intelligent fuzzy logic with the classical PID controller makes the control of nonlinear characteristic of photovoltaic array more feasible. The proposed intelligent hybrid PID-Fuzzy logic controller automatically varies the coefficients Kp, Ki and Kd under variable temperature and irradiation, load change and uses directly the DC-DC converter duty cycle as a control parameter. Finally, the new method gives a good MPPT operation ot any photovoltaic array under different conditions such as changing solar radiation and PV cell temperature. The simulation results and the comparison of results obtained separately from PID controller and hybrid proposed intelligent controller of PID-Fuzzy logic show the advantages of the proposed intelligent algorithm in terms of correctness and the feasibility, overshooting and stability and maintains its response better than the PID controller in many aspects.
Finally the comparison of results, obtained separately from PID controller and hybrid proposed intelligent controller of PID-Fuzzy logic show the advantages of the proposed intelligent algorithm in terms of correctness and the feasibility, overshooting and stability and maintains its response better than the PID controller in many aspects. II.
A. Photovoltaic Array Model and MPPT The output voltage and the voltage-current relationships on the PV depend on various levels of solar radiance and cell temperatures. The I-V characteristic is a complex and non linear function, a various mathematical models have been developed, in this paper we use model of Eduardo Ivan Ortiz Rivera to extract the optimal voltage from a PV cell [8].
Keywords— MPPT; Fuzzy Logic; PID-Fuzzy controller; Photovoltaic; DC-DC converter
I.
DIAGRAM OF A THREE-PHASE GRID-CONNECTED PHOTOVOLTAIC
INTRODUCTION
With industrial development, the use of the power generation technology with renewable energy source is developing rapidly and the application of solar energy focusing photovoltaic system has been increasingly popular. The renewable energy has an advance all over the word in the environment protection. Since, it is clean, silent operation, long life time, low maintenance and absence of fuel cost and inexhaustible [1-2-3].
I pv (V ) =
I x - I xe 1- e
⎛ V pv 1 ⎞ ⎜⎜ bV - b ⎟⎟ ⎝ x ⎠
(1)
⎛ 1⎞ ⎜- ⎟ ⎝ b⎠
⎛ 1⎞ ⎤ ⎡ ⎛ ⎜− ⎟ ⎞ ⎢ I x − ⎜ I − Ie⎝ b ⎠ ⎟ ⎥ ⎜ ⎟⎥ ⎢ ⎝ ⎠ +V Vpv ( I ) = bVx ln ⎢ ⎥ x Ix ⎢ ⎥ ⎢ ⎥ ⎣ ⎦
The intelligent control of output voltage and current of a three-phase photovoltaic grid connected inverter is essential to be considered. The output voltage and the voltage-current relationships on the PV depend on various levels of solar radiance and various cell temperatures. The voltage-current characteristic is a complex and non linear function and difficult to identify the dynamic model [4]. The photovoltaic using the classical PID controller have a various drawbacks in terms of tuning coefficients in different models of grid-connected. In fact, to extract the maximum power point tracking available from a photovoltaic module using the intelligent adaptive fuzzy logic control and PID controller with incremental conductance algorithm, to ensure a high output voltage quality of the
P(Vpv ) = Vpv I =
Vpv I x − Vpv I x e 1− e
⎛ 1⎞ ⎜− ⎟ ⎝ b⎠
(2)
⎛ V pv 1 ⎞ − ⎟⎟ ⎜⎜ ⎝ bVx b ⎠
(3)
where I is the PV panel current, Vpv is the PV panel voltage, Vx is the PV panel open circuit voltage (Voc), Ix is the PV panel short circuit current (Isc ), b is the PV panel characteristic constant and P is the PV panel output power.
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2014 IEEE International Conference on Intelligent Energy and Power Systems (IEPS) The MPPT can extract from the PV, when the partial derivate of the power with respect to voltage is equal to zero equation (4) [6-7], and the dynamic equation of the optimal output voltage is given by solving equation (4), to obtain the maximum power point equation (5). ∂P (V ) = ∂V
⎛ V ⎛ V 1⎞ 1⎞ I x − I x .exp ⎜ − ⎟ I x .exp ⎜ − ⎟ b . V b b . V b ⎝ x ⎠− ⎝ x ⎠ =0 ⎛ −1 ⎞ ⎛ −1 ⎞ 1 − exp ⎜ ⎟ b.Vx − b.Vx .exp ⎜ ⎟ ⎝ b ⎠ ⎝ b ⎠
Fig. 2. Phase diagram with grid voltage (V) and load angle (δ). circuit
(4)
The relationships of inverter and grid voltages are expressed:
1 ⎛ ⎛ ⎛ ⎞ ⎞⎞ Vop = Vx .Re ⎜ b. ⎜ Lambertw ⎜ −0.36787944e b ⎟ + 1⎟ ⎟ ⎟ ⎜ ⎜ ⎝ ⎠ ⎠ ⎟⎠ ⎝ ⎝
E ( t ) = V + ( Ra + jX s ) I
(5)
Where E(t) is the inverter output voltage, V is the grid voltage and the Z = ( Ra + jX s ) is the inverter impedance. The
When the panel works at its optimal voltage Vop, The optimal current Iop can be obtained by substituting (5) in (1).
Pmax = Vop I op =
⎡ ⎛ Vop 1 ⎞ ⎤ - ⎟⎥ ⎢1- exp ⎜⎜ . op b ⎟⎠ ⎥⎦ bV ⎛ -1 ⎞ ⎢⎣ ⎝ 1- exp ⎜ ⎟ ⎝b⎠ Vop I x
(7)
instantaneous voltage of the grid is modeled as:
V = Vm sin ω t
(6)
(8)
if Ra<
