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Cost Effective Wind Solar Power Hybrid Systems

  • Contents

Overview: This article proposes a wind-solar hybrid power system that combines solar and a wind turbine power dispatching system that uses a battery and supercapacitor hybrid energy storage subsystem in the process of cost minimization.

The proposed wind solar hybrid power system (WSHPS) architecture, which combines a wind energy system (WES) and a photovoltaic energy system (PVES), is shown in Fig. 1.

Architecture of Wind Solar Hybrid Power System

The PVES has a 1 MW PV array, a maximum power point tracking (MPPT) controller, and a unidirectional DC/DC boost converter. An AC/DC rectifier, a pitch angle controller, and a 1.5 MW direct-drive three-phase permanent magnet synchronous generator (PMSG) linked to a wind turbine make up the WES.

A wind-solar hybrid power system with HESS

Fig. 1. A wind-solar hybrid power system with HESS Source: IEEE Access

Photovoltaic Energy System

The output of the PV array is very sensitive to two environmental factors: PV irradiation and PV cell temperature. MPPT with incremental conductance (IC) controls the duty ratio of the unidirectional boost converter to draw the maximum amount of power from the PV array.

 

In contrast to the more traditional methods used to extract maximum power from PV systems, an IC MPPT is easy to implement and very effective. As a result, IC MPPT has seen widespread application despite the fact that it can cause slight fluctuations in the maximum power point.

 

One nonlinear device that can be modeled as a current source is a photovoltaic cell. The PV output power and capacity factor are both negatively affected when the PV cell temperature is higher than the ambient temperature.

Wind Energy System

The WES consists of a wind turbine (WT), permanent magnet synchronous generator (PMSG), pitch angle control, drivetrain, and power converter. Without a gearbox, the WES-based PMSG can connect to the WT. PMSG, based on WES, utilizes a two-step process for energy conversion.

 

The WT blades first convert the kinetic energy into mechanical energy. The second step is for the shaft to transmit the mechanical energy to the PMSG, which then uses the energy to generate electricity.

LCL Filter

To satisfy smart grid regulations, an inverter's interaction with the grid additionally necessitates a small output harmonic filter. Because of its superior efficiency and ability to dampen harmonics, an LCL filter has been developed.

Calculating the Dispatched Power

Furthermore, the WT's output is proportional to the wind speed passing through the rotor. The real solar irradiance, temperature, and wind speed data recorded at NREL to forecast the dispatched power hour by hour for a full day is expressed as PGrid,ref.

 

Therefore, the WSHPS and HESS will continue to contribute the required amount of power to the utility grid throughout each hourly dispatching period.

 

The WSHPS relies on both the PV array and the WT system to generate an average output power throughout each dispatching period.

Dispatchable Power from Photovoltaic Energy System

The average output power of the PV array is calculated for each dispatching period using the average irradiance and temperature from the NREL solar statistics inputs.

 

Input factors, including solar cell type, number of parallel cells, and number of series cells, as well as environmental circumstances, are used by the PV array module in Matlab/Simulink to generate power-voltage characteristic curves.

 

NREL's solar data has a resolution of one sample per minute. To generate solar data with a resolution of 120 samples/minute, the cubic spline interpolation method is used. After that, the mean operation method is used to get the average irradiance and temperature for each dispatching time.

 

PPVES,est is the estimated power of the PVES derived from the average irradiation, whereas ηPVES,est is the estimated efficiency of the PVES derived from the average temperature. The ultimate estimated power dispatchable by PVES (PPVES) can be written as follows:

 

PPVES = PPVES,est * ηPVES,est    (1)

Dispatchable Power from Wind Energy System

Similarly, the estimated WES dispatchable power (PWES) is determined. Based on user input parameters such as base wind speed, base rotational speed, blade pitch angle, and maximum power at base wind speed, the WT model in MATLAB/Simulink gives the WT power characteristic curve.

 

Then, the average wind speed is obtained using the mean operation and cubic spline interpolation methods. The PWES is an estimated power output based on the average wind speed.

 

Finally, Equation (2) is used to determine the typical power output of the wind solar hybrid power system, which is expressed as PWSHPS.

 

PWSHPS = PPVES + PWES    (2)

Hybrid Energy Storage System

Each ESS is connected to a bidirectional DC/DC converter, and the HESS is paired in parallel with the WSHPS. Parallel connections between the WSHPS and HESS and the DC-link capacitor bank that functions as the DC bus lead to a three-level T-type inverter that provides clean, stable DC power.

 

By regulating the current through the power converters, it is possible to regulate the output power from the WSHPS and HESS in this architecture. Because of its great efficiency, low total harmonic distortion (THD), and lower common-mode voltage, a three-level T-type inverter is used.

 

Controlling the system power that is fed into the utility grid is the responsibility of the HESS. Calculating the HESS reference power (PHESS,ref) is as simple as subtracting the PGrid,ref from the PWSHPS:

 

PHESS,ref =  PGrid,ref - PWSHPS   (3)

 

Rapidly fluctuating power components can severely shorten a battery's service life. To assign high-frequency power reference components for the supercapacitor energy storage system SESS (PSESS,ref) and low-frequency power reference components for the battery energy storage system BESS (PBESS,ref), the PHESS,ref is supplied through the LPF.

 

In addition, when the ideal value of depth of discharge (DOD) is determined, a rule-based state of charge (SOC) control algorithm is used to keep the BESS SOC within the optimal range (DOD optimum). As with the SESS, after the best value of DOD has been determined, a rule-based SOC control algorithm is put into place to govern the SESS SOC.

HESS DOD Optimisation

The DOD and the rate of change of the charging-discharging power are the two most important factors in determining the ESS's useful life. There is an almost exponential link between cycle life and DOD consumption.

 

There are two primary determinants of ESS costs: (i) the ESS's expected service life and (ii) the ESS's minimum capacity. The minimal capacity of the BESS increases as the DOD decreases in use. However, the BESS's service life decreases with increasing discharge depth. Thus, the simulations are run with all possible values of the BESS DOD to find the optimal value of DOD that results in the cheapest BESS for dispatching the WSHPS electricity.

 

Similarly, research into the ideal DOD for the SESS has been conducted. Unlike Li-ion batteries, supercapacitors can be charged and drained indefinitely. Therefore, the total number of charging-discharging cycles for the SESS is taken to be constant.

HESS Cost Minimization

The BESS and SESS use the LPF as their power reference. Minimum SESS capacity is proportional to the LPF time constant, while minimum BESS capacity is inversely related to the LPF time constant. The total cost of the HESS can be reduced by selecting an appropriate value for the filter time constant.

 

The PSO strategy is used to determine the optimal LPF time constant once the suitable cost formula of the HESS as a function of the LPF time constant has been acquired via the curve fitting method.

 

Because of its many benefits, including easy implementation, increased credibility in locating global optimums, the need for the adjustment of only a small number of parameters, and rapid convergence, the PSO method is used.

 

Although genetic algorithms are also commonly used as an optimization approach in renewable energy systems, the PSO typically provides faster evaluation times and higher-quality solutions.

Estimation BESS and SESS Lifespan

The charging-discharging characteristics of the BESS over a period of time are utilized to evaluate its service life due to the fluctuating nature of the WSHPS output power.

 

Because of calendar aging, the BESS's predicted lifetime decreases. Calendar aging and cycling are both taken into account by the SESS aging model.

Estimating the Cost of HESS

The ESS cost is examined while taking into account the costs associated with both cycle and calendar aging. The capital cost, power conversion system cost, and operation and maintenance (O&M) cost of the ESS make up its total expense. Thus, it is possible to estimate the overall cost related to the BESS (CBat,overall) using equation (4):

 

CBat,overall = CCap + Cconv + CO&M     (4)

Summarizing the Key Points

  • The article proposes a wind-solar hybrid power system that combines solar and wind turbine power dispatching systems.
  • The system uses a battery and supercapacitor hybrid energy storage subsystem to minimize costs.
  • The wind energy system consists of a wind turbine, permanent magnet synchronous generator, pitch angle control, drivetrain, and power converter.
  • The photovoltaic energy system has a 1 MW PV array, a maximum power point tracking controller, and a unidirectional DC/DC boost converter.
  • The article aims to optimize energy storage and power dispatching in wind-solar hybrid systems for cost-effective and reliable electricity supply.

Reference

Roy, Pranoy, Jiangbiao He, and Yuan Liao. “Cost Minimization of Battery-Supercapacitor Hybrid Energy Storage for Hourly Dispatching Wind-Solar Hybrid Power System.” IEEE Access 8 (2020): 210099–115. https://doi.org/10.1109/access.2020.3037149.

Rakesh Kumar, Ph.D.

Rakesh Kumar holds a Ph.D. in electrical engineering, specializing in power electronics. He is a Senior Member of the IEEE Power Electronics Society, Class of 2021. He writes high-quality, long-form technical articles for global B2B semiconductor brands. Feel free to reach out to him at rakesh.a@ieee.org! Checkout his complete portfolio @muckrack.com/rakesh-kumar-phd | @linkedin.com/in/rakesh-kumar-phd

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