Research article

Adaptive and predictive controllers applied to onshore wind energy conversion system

  • This paper presents a simulation of onshore energy conversion system connected to the electric grid and under an event-based supervisor control based on deterministic version of a finite state machine. The onshore energy conversion system is composed by a variable speed wind turbine, a mechanical transmission system described by a two-mass drive train, a gearbox, a doubly fed induction generator rotor and by a two-level converter. First, mathematical models of a variable speed wind turbine with pitch control are studied, followed by the study of different controller types such as adaptive controllers and predictive controllers. The study of an event-based supervisor based on finite state machines is also studied. The control and supervision strategy proposed for the onshore energy conversion system is based on a hierarchical structure with two levels, execution level where the adaptive and predictive controllers are included, and the supervision level where the event-based supervisor is included. The objective is to control the electric output power around the reference power and also to analyze the operational states according to the wind speed. The studied mathematical models are integrated into computer simulations for the onshore energy conversion system and the obtained numerical results allow for the performance assessment of the system connected to the electric grid. A comparison of the onshore energy conversion system performance without or with the supervisor is carried out to access the influence of the control and supervision strategy on the performance.

    Citation: Carla Viveiros, Rui Melicio, Victor Mendes, Jose Igreja. Adaptive and predictive controllers applied to onshore wind energy conversion system[J]. AIMS Energy, 2018, 6(4): 615-631. doi: 10.3934/energy.2018.4.615

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  • This paper presents a simulation of onshore energy conversion system connected to the electric grid and under an event-based supervisor control based on deterministic version of a finite state machine. The onshore energy conversion system is composed by a variable speed wind turbine, a mechanical transmission system described by a two-mass drive train, a gearbox, a doubly fed induction generator rotor and by a two-level converter. First, mathematical models of a variable speed wind turbine with pitch control are studied, followed by the study of different controller types such as adaptive controllers and predictive controllers. The study of an event-based supervisor based on finite state machines is also studied. The control and supervision strategy proposed for the onshore energy conversion system is based on a hierarchical structure with two levels, execution level where the adaptive and predictive controllers are included, and the supervision level where the event-based supervisor is included. The objective is to control the electric output power around the reference power and also to analyze the operational states according to the wind speed. The studied mathematical models are integrated into computer simulations for the onshore energy conversion system and the obtained numerical results allow for the performance assessment of the system connected to the electric grid. A comparison of the onshore energy conversion system performance without or with the supervisor is carried out to access the influence of the control and supervision strategy on the performance.


    Symbols: Am: Module area; C: Cost (IQD); CAh: Battery ampere capacity (A/h); Cwh: Battery watt capacity (W/h); d: Interest rate (%); E/m2: Energy received by PV (kW/m2); EL: Energy consumed by the load (kW); IC: Controller current (A); i: inflation rate (%); Nc: Number of controller; Npv: Number of solar cell; Vb: Battery voltage (V)

    Abbreviations: MPW: Maintenance present worth; DOD: Permissible depth of discharge rate of a cell; IOP: Inverter output power; IQD: Iraqi Dinar; LCC: life cycle cost; ML: Maximum load; NC: Number of continuous cloudy days; PR: Performance ratio; SF: Safety factor

    Greek letters: η module: PV module efficiency; ηb: Battery efficiency

    Subscripts: n-g: Neighborhood generator; h-g: Household generator; ins: Installation; O&M: Operation and maintenance; b: Battery; c: Controller; inv: Inverter

    The Electrical energy that produced from Photovoltaic solar system has become an excellant option to offset the growing demand of electricity around the world [1], reliable and has the potential to reduce the CO2 emissions [2]. Many countries have effectively turned on this type of energy due to the availability of the solar radiation over a wide range of the year. This led many researchers to focus their attention on developing and increasing the efficiency of photovoltaic solar systems to achieve an economic feasibility. In the last years, some of studies in literatures have examined the performance evaluation of photovoltaic solar systems. The evaluation was based on some main indicators that reported in these studies including: the total energy production, performance ratio (PR), and the system efficiency. Renu S. and Sonali G. [3] examined the annual performance of 11.2 kWp in India. The experimental examination showed that the total energy, efficiency and PR were 14.96 MWh, 13.42% and 0.78 respectively. In Italy, the performance analysis of two systems 395.61 kWp and 1042.29 kWp showed that the PR of the two systems was 0.872 and 0.832 respectively [4]. In Morocco, Charaf H. et al. [5] examined experimentally different modules and sizes of PV systems and showed that the Twidell was the best module with PR = 0.8 and an average efficiency of 16%. The performance assessment of 4.5 kWp in Nigeria showed that the energy production of the system was 14.52% from the size of the system [6]. In addition, the performance analysis of 1.72 kWp system in Ireland was presented experimentally by Ayompe L.M. et al. [7]. The analysis showed that the annual total energy of the system was 885.1 kW h/kWp and system efficiency was 14.9%. On the other side, some of studies were focused on an economic feasibility of the PV solar systems depending on two main important indicators include life cycle and pay-back period. In Ireland, the experimental feasibility of 53.625 kWp PV system showed that the life cycle was 5.23 years [8]. In Japan, Yanxue L. et al. [9] simulated Techno economic performances of 5.0 kWp and showed that the net present value of system was over 20 years. As reported in Rodrigues S. et al. [10] study, the investment of 5 kWp system during 25 years in Germany and Italy was 13% higher than the most European countries. The payback period of 67.27 kWp system was recorded 11 years in United Kingdom [11]. In Palestine, the economic evaluation of 24.614 kWp system showed that dynamic pay-back period of system was 10.4 years [12]. The main goal of this work is to study the necessary of using the PV system to provide the required electricity for Iraqi houses. An economic feasibility investigation of 3 kWp PV solar system by calculating the life cycle cost was analyzed and compared with the two alternative sources represented in neighborhood and household generators.

    The electricity sector in Iraq suffered from deterioration since 1991 till now due to:

    1. Old power generation plants, distribution and transmision networks;

    2. Economic embargo in 1991;

    3. American invasion in 2003;

    4. Vandalism and neglecting from Iraqi goverment.

    These factors led to severe power shortages to households, with power being available for less than 12 hours per day. To meet these power shortages, Iraqi families were forced to use other alternative sources such as the diesel neighborhood generators together with small gasoline portable generators (household), both of which have added a considerable financial burden on people. The financial burden includes the prices of generators, fuel and maintenance costs. In view of this phenomenon, the main goal of this work was to suggest and analyze the feasibility economic of a 3 kW PV solar system and compare it with the financial burden of the two generators (neighborhood and household). The study was conducted for a period of five years from (2014 to 2019) according to the current Iraqi market price. Questionnaire form was prepared to facilitate the calculation cost of neighborhood and household generators as shown in Table 1. The information of a questionnaire form was taken in the region where the neighborhood generator installed. Numbers of parameters were included in the questionnaire form, some of these parameters were related to the neighborhood generator (number and price of ambers) and other parameters were related to household generator (purchase cost, operation hours and maintenance cost).

    Table 1.  Questionnaire form of generators information.
    Neighborhood generator Household generator
    Family No. No. of persons No. of required amperes Price (IQD/amperes*month) Purchase cost (IQD) No. of operating hours Cost of fuel (IQD/day) Period of oil change (hours) Oil cost (IQD/year) Maintenance cost (IQD/year)
    1 3 4 8000 180000 4 1350 30–35 48000 80000
    2 4 4 8000 210000 4 1350 25–30 58000 90000
    3 5 4 8000 200000 4 1350 30–40 41000 90000
    4 6 4 8000 225000 3 1013 30–40 31000 85000
    5 4 4 8000 230000 4 1350 30–40 41000 90000
    6 5 4 8000 230000 4 1350 25–30 58000 95000
    7 5 4 8000 220000 4 1350 30–40 41000 85000
    8 7 4 8000 240000 3 1013 30–35 36000 80000
    9 5 4 8000 220000 4 1350 30–35 48000 85000
    10 4 4 8000 240000 4 1350 30–35 48000 100000

     | Show Table
    DownLoad: CSV

    Neighborhood generator is a private diesel generator widely used in Iraq after 2003 to provide the electricity during the duration of national power outage. It is invested by a person and placed in a small neighborhood. The Iraqi government supplies the fuel to the generators at a reasonable price. So, the price of ampere from the neighborhood generator are controlled at 8000 IQD/ampere. According to the questionnaire form, the average of amperes demand of Iraqi family is equal to 4 amperes (equivalent to 1 kWh at 250 V supply). Therefore, the cost to be paid to the neighborhood generators for four amperes in one month is 32,000 IQD with total cost (Cn-g) in five years is 1,920,000 IQD (Cn-g = 4 amperes × 8,000 (IQD/amperes×month) × 60 month = 1,920,000 IQD).

    Iraqi markets contain different types of portable gasoline generators with different rated power (KVA) and different specifications. Gasoline generator model (Tiger-single phase-3KVA) with fuel capacity 10 liters and 0.5 liters oil were included in this study as shown in Figure 1. Schedule run of portable generator is from 5:00 am until 12:00 pm with an actual operation period 4 hours/day and the operation period depends on the national power outage and neighborhood generator off. The cost of household generator is listed in Table 2 including purchase, operation and maintenance cost. The cost calculation of household generator was investigated based on the data of Table 1.

    Figure 1.  Household generator.
    Table 2.  Cost of household generator.
    Cost type The explanation Cost (IQD) per 5 years
    Purchase Average price in Iraqi market 210,000
    Fuel Consume 0.75 liter /hr (4 hours operation)
    Price of gasoline = 450 IQD/liter
    2,430,000
    Oil Oil capacity (0.5 liter)
    Period of oil change (30 hours operation)
    Price of oil = 1500 IQD/liter
    180,000
    Maintenance Average cost in 1 year = 88,000 IQD 440,000
    Total cost (Ch-g) 3,080,000

     | Show Table
    DownLoad: CSV

    The average maximum load was calculated in the summer and according to the actual need for household appliances as shown in Table 3. The actual operation period of appliances depends on the schedule of power shortages. Based on the table, the maximum energy demand is 1.11 kW then the maximum hourly load consumption should be 17.73 kWh. Figure 2 represents the actual load profile according to the number of operation hours.

    Table 3.  Measured appliances loads in Iraqi house.
    Appliance Watt Number Hours Used/Day Watt Hours/Day
    Refrigerator 350 1 12 4200
    Ceiling Fan 80 4 12 3840
    Light 60 8 8 3840
    Television 250 1 10 2500
    Cooling/heating water 300 1 10 3000
    Laptop 70 1 5 350
    Total power (EL) 1110 17730

     | Show Table
    DownLoad: CSV
    Figure 2.  Actual load profile.

    A 3 kWp system with twelve solar module (Dusol DS60260W Dubi) made from polycrystalline silicon was proposed in this study according to the calculation of the load and sizing of components. The general specifications of the solar system components are summarized in Table 4 and its photograph shown in Figure 3.

    Table 4.  General specifications of the solar system components.
    Component Quantity Model type and manufacture Specification Value
    Solar module 12 Dusol DS60260W Dubi Maximum power (Pmax) 250 W
    Open cicut voltage (Voc) 38 V
    Short circuit current (Isc) 8.79 A
    Peak voltage (Vmpp) 31.4
    Peak current(Impp) 8.28 A
    Area 1.67 m2
    Efficiency 14%
    Solar controller 2 MPPT/China Battery voltage 12/24/48 V
    Charger current 60 A
    Maximum power 840/1680/3360 W
    Maximum voltage 150 V DC
    Inverter and charger 1 SAKO/SKN-S 1.5 kW Input voltage 24 V DC
    Output voltage 220 V AC, 50 Hz
    Battery 2 Fortuner FR12-300D Nominal voltage 12 V
    Power 300 Ah

     | Show Table
    DownLoad: CSV
    Figure 3.  Proposed PV solar system.

    The sizing of the PV solar system components includes: number of solar panel, inverter output power, storage capacity of the battery and MPPT controller.

    The total peak power and the module number of the proposed PV system can be calculated as [13]:

    PPV=ELPSH×ηR×ηin×SF=17.738.7×0.9×0.92×1.2=2,855 Wp (1)
    NPV=PPVPmodule=285525012 cells (2)

    where: EL: Daily Energy consumption (17.73) kWh, PSH: peak sun hours (8.7) hours [14], ηR and ηin: charge regulator and inverter efficiencies (0.9 and 0.92) [13], SF: Safety factor (1.2) [15] and Pmodule: module power is selected (250) W.

    The inverter output power (IOP) calculated according to [16]: IOP = (25−30)% greater than maximum load (ML) = 0.25 × 1.11 + 1.11 = 1.38 ≈ 1.5 kW. Therefore, the inverter specifications is selected as 1500 W, 24 V DC, 220 V AC, and 50 Hz.

    As reported in [12], the watt hour capacity of pattery can be calculated as:

    Watt hour capacity(Cwh)=NC×ELDOD×ηb=0.5×177300.75×0.8513,906  Wh (4)

    NC: Number of continuous cloudy days of the interested area = 0.5, DOD: Permissible depth of discharge rate of a cell = 0.75 [12], ηb: Battery efficiency = 0.85 [12].

    The selected DC bus voltage is 24, therefore:

    Ampere hour capacity (CAh) = Cwh/24  579.5 Ah (5)

    Number of batteries = 2 batteries of 12 V and 300 Ah connected in series to give 12 hours operation.

    Total maximum power of PV (Pmax-tot) = Pmax × NPV  = 250  ×  12 = 3000 watts (6)

    The maximum power of controller (Pmax-C) and number of controller (NC) can be calculated as [15]:

    Pmax-C  = Battery voltage (Vb ×  Controller current (IC) = 24  ×  60 = 1440 watts (7)
    NC =Pmax-tot/Pmax-C= 3000/1440  2 controllers (8)

    The LCC of the PV solar system can be classified into three parts: (ⅰ) components cost (ⅱ) installation cost (ⅲ) operation and maintenance cost. The details of calculating the components cost of the proposed PV solar system are represented in Table 5.

    Table 5.  Cost calculations of proposed PV solar system.
    Components Quantity Cost (IQD) Total cost (IQD)
    Solar cell 12 cells/250 W 700/W CPV = 2,100,000
    Solar controller 2 80000 Cc = 160,000
    Inverter 1 650000 Cinv = 650,000
    Battery 2 batteries/300 A 1600 / A Cb = 960,000
    Wiring, base and installation Total 100000 Cins = 100,000
    Operation and Maintenance
    (O&M/yr)
    Total 2% PV cost CO&M = 79,400

     | Show Table
    DownLoad: CSV

    The present worth of the maintenance cost for the proposed PV solar system in 5 years can be calculated as [16,17]:

    CMPW=Myr(1+i1+d)[1(1+i1+d)N1(1+i1+d)]= 336,966 IQD (9)

    where: i is the inflation rate and assumed to be 3% and d is the interest rate assumed to be 9%. Therefore, the total life cycle of the PV system can be calculated as [18]:

    LCC=CPV+CC+Cinv+Cb+Cins+CMPW= 4,386,366 IQD (10)

    The Iraqi government has not given much attention to use of PV solar energy for solving the problems in the electric power sector. In this paper, the cost and an economic feasibility investigation of proposed PV solar system was analyzed by calculating the life cycle cost. A comparison between the proposed system and two alternative sources (generators) that used together in Iraqi house was investigated. According to the results analysis, the total cost of the financial burden in five years for neighborhood generator was found to be (1,920,000 IQD ≈ 1600 USA$) while the cost of household generator was found to be (3,080,000 IQD ≈ 2566.6 USA$). Totally, the cost of the two generators was recorded about (5,000,000 IQD ≈ 4166.6 USA$) in five years. As shown in Figure 4, the cost of household generator represents 61.6% from the total cost of the two generators. The cost of neighborhood generator increases with an increasing in number of amperes that the Iraqi family needed. While, the cost of household generator depend on two parameters (operations hours and maintenance cost). The operation hours of household generator increase in the event of breakdowns of the neighborhood generator causing an increase in the cost of fuel and oil consumption and maintenance. On the other side, the life cycle cost LCC of the proposed PV solar system is found to be (4,386,366 IQD ≈ 3655 USA$). As shown in Figure 5, the cost of PV system is less than the cost of two generators by (613,634 IQD ≈ 511.3 USA$). In the other words, the LCC of two generators is greatly higher than PV solar cost with 12.27%.

    Figure 4.  Total cost of generators.
    Figure 5.  Costs of three sources.

    According to the economic feasibility analysis of the PV solar system comparing with the two types of generators, the following conclusions can be made:

    1. The cost of household generator is greater than the neighborhood generator about 42.6%;

    2. The breakdowns in the neighborhood generator increase the operation hours of the household generator then increase the fuel, oil and maintenance costs;

    3. According to LCC, the cost of two generators is greatly higher than PV solar cost with 12.27%;

    4. The PV solar system is more economic in Iraqi houses under the deterioration in the electricity sector. Furthermore, the PV solar not pollutes the environment as the case of using household and neighborhood generators.

    The authors would like to thank the staff of Baqubah Technical Institute and Technical Engineering collage for their help.

    All authors appear no conflicts of interest.

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