2. Key performance indicators for power plant operation

The main objectives of assessing the technical performance of power plants based on renewable sources are


Technical performance indicators allow the following comparisons:

the climatic conditions, design and exposure point of view, etc. The objective entails identifying errors related to layout in case of renewables (especially photovoltaic power plants), incorrect

In order to provide a real time and complete analysis of KPIs, it is necessary to develop informatics systems that monitor and report the operational activity of the power plant and offers decision support for stakeholders. Various informatics solutions and applications are currently proposed and used, especially for renewable power plants' management: decision support systems (DSS) for wind power plants with (GIS) Geographic Information Systems capabilities [1], DSS for off-shore wind power plants [2] or GIS DSS for photovoltaic power plants [3]. Also, there are well-known software solutions for power plants' complete management provided by Siemens or Emerson that can be set up and customized depending on the equipment's configura-

In this chapter, we will present the main key performance indicators for wind and photovoltaic power plants, identify new indicators for maintenance activities and propose an informatics solution that monitors and analyzes these KPIs through an interactive dashboard developed as a business intelligence portal accessed as a cloud computing service. The proposed solution is developed as part of the research project—intelligent system for predicting, analyzing and monitoring performance indicators and business processes in the field of renewable energies (SIPAMER), funded by National Authority for Scientific Research and Innovation, Romania,

The main objectives of assessing the technical performance of power plants based on renew-

• Monitoring the operation of generating units or groups, identifying decline in their performance and also the need to perform maintenance/repairs on the affected groups. In this case, we recommend the use of energy performance index (EPI) and compensated perfor-

• Commissioning, recommissioning or evaluation after repairs, benchmarks for measuring and comparing further performance. We recommend using energy performance index

• Calculating specific parameters such as yield, performance ratio (PR) to enable comparisons between power plants operation in different geographical areas and assisting decisions regarding investment in new groups or extending existing ones. In some cases, depending on the objectives, it is recommended to use several indicators (yield, PR, CPR, and/or EPI, depending on the level of effort and the level of uncertainty), so that the

2. Key performance indicators for power plant operation

installation, equipment failure, damage, premature aging, etc.

10 Recent Improvements of Power Plants Management and Technology

tion, location and size.

during 2014–2017.

able sources are

mance ratio (CPR);

(EPI) and power performance index (PPI);

comparison to be more efficient.


The main objective of the technical performance evaluation consists in detecting the decrease of power plant performance, investigating issues and completion of the maintenance operations, so that the involved costs are minimal.

In this section, we will present a series of key performance indicators for monitoring the operation of the wind power plants (WPP) and photovoltaic power plants (PPP). For a better analysis, we grouped KPIs in four categories: operational KPIs, indicators for photovoltaic power plants, indicators for wind power plants, and maintenance KPIs.

### 2.1. Performance indicator techniques based on operational data

	- onshore WPP, t = 1900 hours/year;
	- offshore WPP, t = 3500 hours/year;
	- solar, t = 1100 hours/year.

$$P\_{avg} = \frac{W}{t} \text{ [kW]} \tag{1}$$

The average power calculated at different time intervals is necessary to determine the installed power load factor. Pavg allows comparisons between monthly/quarterly or annual results of the same power plant, or it can be used to compare the generating units' performance within the same power plant.

2. Installed power load factor (Ku) is calculated as the ratio of average power (Pavg) and installed power (Pi):

$$K\_u = \frac{P\_{avg}}{P\_i} \tag{2}$$

This coefficient can be calculated on monthly, quarterly or annually basis and indicates the availability of renewable resource and production capacity of the power plant. Also, it can indicate the degree of generating units or equipment's aging but must be correlated with meteorological factors that influence the production. For example, for wind power plants, the installed power load factor can range between 0.15 and 0.39.

3. Installed power load duration (Ti) is determined based on installed power load factor (Ku) multiply by power plant's runtime (t):

$$T\_i = \mathbb{K}\_u \times t \text{ [}h\text{]} \tag{3}$$

For photovoltaic power plants, the number of operating hours can be accordingly reduced, considering only those daytime hours when the PPP is operating. We may consider [4] for reference to operational time.

4. Maximum power load duration (Tmax) is calculated as ratio between generated energy (Wa) and maximum power plant output (Pmax):

$$T\_{\text{max}} = \frac{\mathcal{W}\_a}{P\_{\text{max}}} \,\, [\hbar] \tag{4}$$

Pmax can be calculated on monthly, quarterly or annual basis, and it can be used to compare results between different periods of time and identify the influence factors.

5. Power factor (cos ϕ) can be determined based on active energy (Wa) and reactive energy (Wr):

$$\cos \phi = \frac{1}{\sqrt{1 + \left(\frac{W\_r}{W\_s}\right)^2}} \tag{5}$$

Power factor is monitored for energy quality assurance.

6. Performance index (PI) is the ratio between the generated power/energy and forecasted power/energy:

$$\text{PI} = \frac{\text{W}}{\text{W}\_f} \tag{6}$$

As described in [5], unlike performance ratio, index performance should be very close to 1 for the proper functioning of the PPP, and it should not vary from season to season due to temperature variations. There are several definitions of formal performance index:


Energy or power forecast can be determined using different prediction models (regression model using historical data operation or system advisor model (SAM) which uses current climate data as input), thus the accuracy of performance index depends on the accuracy of the used forecast model. In Section 3, we will present a forecasting model based on artificial neural networks (ANN) for estimating the generated energy for photovoltaic and wind power plant.

## 2.2. Key performance indicators for photovoltaic power plants

Several technical performance indicators for PPP were defined by different organizations, for example, National Renewable Energy Laboratory (NREL) [6], the International Electrotechnical Commission (IEC) [7], associations and companies in the industry. Some of them are described in the following sections:

1. Performance ratio (PR) is defined according to IEC 61724 standard [7], as follows:

$$PR = \frac{Y\_f}{Y\_r} = \frac{\frac{kWh\_{AC}}{kW\_{DC\,\rm{STC}}}}{\frac{kWh\_{\rm{Sun}}}{1 kW}}\tag{7}$$

Where:

This coefficient can be calculated on monthly, quarterly or annually basis and indicates the availability of renewable resource and production capacity of the power plant. Also, it can indicate the degree of generating units or equipment's aging but must be correlated with meteorological factors that influence the production. For example, for wind power plants,

3. Installed power load duration (Ti) is determined based on installed power load factor (Ku)

For photovoltaic power plants, the number of operating hours can be accordingly reduced, considering only those daytime hours when the PPP is operating. We may

Pmax can be calculated on monthly, quarterly or annual basis, and it can be used to compare results between different periods of time and identify the influence factors. 5. Power factor (cos ϕ) can be determined based on active energy (Wa) and reactive energy (Wr):

cos <sup>ϕ</sup> <sup>¼</sup> <sup>1</sup> ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

6. Performance index (PI) is the ratio between the generated power/energy and forecasted

PI <sup>¼</sup> <sup>W</sup> Wf

As described in [5], unlike performance ratio, index performance should be very close to 1 for the proper functioning of the PPP, and it should not vary from season to season due to temperature variations. There are several definitions of formal performance index:


Energy or power forecast can be determined using different prediction models (regression model using historical data operation or system advisor model (SAM) which uses current climate data as input), thus the accuracy of performance index depends on the accuracy of the used forecast

<sup>1</sup> <sup>þ</sup> Wr Wa

4. Maximum power load duration (Tmax) is calculated as ratio between generated energy

Tmax <sup>¼</sup> Wa Pmax

Ti ¼ Ku � t ½h� ð3Þ

½h� ð4Þ

� �<sup>2</sup> <sup>r</sup> <sup>ð</sup>5<sup>Þ</sup>

ð6Þ

the installed power load factor can range between 0.15 and 0.39.

multiply by power plant's runtime (t):

12 Recent Improvements of Power Plants Management and Technology

consider [4] for reference to operational time.

(Wa) and maximum power plant output (Pmax):

Power factor is monitored for energy quality assurance.

power/energy:



Performance ratio can be evaluated on different time intervals (hourly, monthly, quarterly and annually). The main disadvantage of this indicator is that it is sensitive to temperature variations, and when plotted in a typical year, the index values are lower in warm periods and higher in cold periods.

It can be calculated on annual basis to make comparisons between photovoltaic power plants having similar climatic conditions but is not suitable for short periods of time or for comparing PPP efficiency under different climatic conditions.

2. Compensated performance ratio (CPR)

As reflected in the performance ratio formula, it is directly influenced by the energy produced by the photovoltaic power plant, which is directly influenced by solar irradiation and indirectly by the cell temperature. Therefore, it appears that PR decreases with increasing temperature.

According to [5, 8], offsetting factors such as cell temperature (Ktemp) can be applied to the performance ratio to adjust the rated power under standard test conditions (STC).

$$PR\_{Temp\text{Comp}} = \frac{\frac{kWh\_{AC}}{kW\_{DC\text{STC}} \times K\_{Tmpp}}}{\frac{kWh\_{Sun}}{1 kW}}\tag{8}$$

Where


This indicator is suitable for daytime values due to the fact that during night, the PPP production, irradiation and insolation are zero.

3. The yield is the ratio between the PPP's produced energy (kWh) during the operation time (t) and peak load power (kWp or kW peak) of the PPP or rated power on standard test conditions (STC), and it varies yearly depending on climate conditions.

The yield is determined annually based on the formula:

$$Yield = \frac{\sum\_{i=1}^{t} kWh\_{AC}}{kW\_{DC\,STC}}\tag{9}$$

Due to the fact that the yield increases with the number of hours of operation and insolation etc., a high yield due to favorable climatic conditions can mask problems of premature aging of the equipment and vice versa.

When comparing the performance for two power plants or the yield for the same PPP in different periods of time, then the number of hours, insolation and cell temperature must be equivalent to achieve a fair comparison. Also, the power plant output (measured annually or at smaller intervals) can be compared with PPP's output from previous years. In this case, it must be taken into consideration the climate influence and correct the differences with a correction coefficient, to avoid masking problems of degradation of solar panels.

4. Normalized efficiency is another KPI for measuring the performance ratio [8]:

$$
\eta\_N = \frac{\frac{P}{P\_n}}{\frac{E\_{PO4}}{E\_{ref}}} \tag{10}
$$

Where:


Exposure to irradiation measures the total available solar exposure, and it is based on location exposure and direction of modules. It is calculated at the module level and average at central level. In order to maximize exposure to irradiation, modules are oriented towards the equator, the tilt modules depending on geographical latitude of the location. Optimal orientation in terms of space restrictions may not coincide with the orientation that maximizes exposure (due to the fact that a lower slope leads to more modules in a project).

One drawback of the performance index is that the normalized efficiency is sensitive to temperature variations, as any change in temperature leads to changes in efficiency, power and consequently in the produced energy.

Changing efficiency or power for a photovoltaic module can be quantified using the temperature coefficient of power γ, which allows the module power (or efficiency) to be modelled to a certain temperature. For silicon crystals, γ is between �0.3%/�C (for newer technologies) and �0.5%/�C (for older technologies).

Power for a certain temperature for a photovoltaic cell is determined by:

$$P(T) = P\_{STC} \left( 1 + \gamma (T\_{\text{cell}} - T\_{STC}) \right) = P\_{STC} (1 + \gamma \Delta T\_{STC}) \tag{11}$$

Where

ð9Þ

ð10Þ

This indicator is suitable for daytime values due to the fact that during night, the PPP produc-

3. The yield is the ratio between the PPP's produced energy (kWh) during the operation time (t) and peak load power (kWp or kW peak) of the PPP or rated power on standard test conditions

> X<sup>t</sup> i¼1

Due to the fact that the yield increases with the number of hours of operation and insolation etc., a high yield due to favorable climatic conditions can mask problems of premature aging of

When comparing the performance for two power plants or the yield for the same PPP in different periods of time, then the number of hours, insolation and cell temperature must be equivalent to achieve a fair comparison. Also, the power plant output (measured annually or at smaller intervals) can be compared with PPP's output from previous years. In this case, it must be taken into consideration the climate influence and correct the differences with a

kWhAC kWDC STC

Yield ¼

correction coefficient, to avoid masking problems of degradation of solar panels. 4. Normalized efficiency is another KPI for measuring the performance ratio [8]:

η<sup>N</sup> ¼

).

Exposure to irradiation measures the total available solar exposure, and it is based on location exposure and direction of modules. It is calculated at the module level and average at central level. In order to maximize exposure to irradiation, modules are oriented towards the equator, the tilt modules depending on geographical latitude of the location. Optimal orientation in terms of space restrictions may not coincide with the orientation that maximizes exposure (due

One drawback of the performance index is that the normalized efficiency is sensitive to temperature variations, as any change in temperature leads to changes in efficiency, power and

Changing efficiency or power for a photovoltaic module can be quantified using the temperature coefficient of power γ, which allows the module power (or efficiency) to be modelled to a

P Pn EPOA Eref

tion, irradiation and insolation are zero.

14 Recent Improvements of Power Plants Management and Technology

the equipment and vice versa.



consequently in the produced energy.


to the fact that a lower slope leads to more modules in a project).


Where:

(STC), and it varies yearly depending on climate conditions.

The yield is determined annually based on the formula:



The temperature—corrected power (P\*) can be determined as in [9]:

$$P^\* = \frac{P(T)}{1 + \gamma \Delta T\_{STC}} \tag{12}$$

Thus, the temperature-corrected normalized efficiency can be expressed as:

$$
\eta\_N \stackrel{\*}{}{=} \frac{\frac{P^\*}{P\_n}}{\frac{E\_{\text{POA}}}{E\_{\text{ref}}}} \tag{13}
$$

This indicator shows the performance of the photovoltaic module as if it operates at standard temperature (TSTC). In this way, the technical performance of the PPP can be attributed to other factors, such as the irradiance spectrum or inverter efficiency at lower irradiances [9].

#### 2.3. Key performance indicators for wind power plants

1. Specific energy production (SPE) measured in kWh/m2 for a wind turbine is defined in [10] as the ratio between total energy production during nominal period (W) and swept rotor area (SSR):

$$SPE = \frac{W}{\mathcal{S}\_{\mathcal{SR}}} \tag{14}$$

The nominal period is the period covered by the report, usually considered as 1 year. SPE is also called as energy yield or energy productivity [11], and it depends on the turbines' rated power.

2. Capacity (load) factor (CF %) defined in [11] is the ratio between total energy production during the nominal period (W) and the potential energy production during the reported period (Wp):

$$CF = \frac{W}{W\_p} \tag{15}$$

Usually, the capacity factor varies depending on the turbines specifications and climate conditions between 18 and 40% for onshore turbines and 30–40% for offshore turbines.

3. Equivalent full load hours (Eh) can be defined as the annual energy production (W) divided by the rated power (Sn), and it represents the number of hours as if turbines generate at rated power:

$$E\_h = \frac{\mathcal{W}}{\mathcal{S}\_n} \tag{16}$$

4. Availability factor (%) represents an important indicator especially for WPP due to the wind influence that affects the turbines' generation and can be calculated as ratio between total hours of operation during the reported period (Top) and total hours of reported period (Tp):

$$AF = \frac{T\_{op}}{T\_p} \tag{17}$$

#### 2.4. KPIs for maintenance operations

Several maintenance strategies have been developed as described in [12, 13] with the main objective to preserve the efficiency of power plants' components. Each of these methodologies has its own characteristics, but mainly they focus on internal characteristics of the power plants' components. The industry has adopted for a long period of time maintenance that focuses on corrective actions. But, in recent years, the maintenance plans focus on predictive maintenance where monitoring or inspection activities are performed to determine the best time to start the maintenance in order to minimize the efforts compared to corrective maintenance.

Preventive maintenance activity has a direct impact on the reliability of the equipment or components by improving their technical condition and prolonging their life. All maintenance procedures involve both costs and benefits. Maintenance operations are profitable when the costs are lower than associated potential cost of a failure, which these operations are trying to prevent. Most of the maintenance plans on short and medium term do not take into account the operation conditions in which the components operated throughout their runtime but rather are scheduled based on the occurrence of defects and previous repairs. But, in recent years, several applications for continuous monitoring of current operation led to the development of a variety of diagnostic techniques. According to [14], these techniques verify certain parameters and then analyze whether certain components are defective at the moment and can make an estimate of their evolution.

The main purpose of the maintenance plan is to minimize production costs per unit of energy generated. In general, this is achieved by minimizing operational and maintenance costs, improving turbine/photovoltaic panels' performance and efficiency and lowering insurance policy and equipment's protection. Thus, we proposed two KPIs for determine the loss due to preventive (planned) maintenance or to corrective (unplanned) maintenance.

1. Preventive loss indicator (PLIplan) is the ratio between estimated energy loss caused by planned interruptions and the maximum energy that can be produced during the reported period (usually 1 year).

$$PLI\_{plau} = \frac{W\_{lossplan}}{W\_{max\\_prod}} \times 100\% \tag{18}$$

Where:



2. Corrective loss indicator (PLIunplan) is the ratio between estimated energy loss caused by unplanned interruptions and the maximum energy that can be produced during the reported period.

$$PLI\_{unplan} = \frac{W\_{lossumplan}}{W\_{max\\_prod}} \times 100\% \tag{19}$$

Where:

ð16Þ

ð17Þ

Eh <sup>¼</sup> <sup>W</sup> Sn

4. Availability factor (%) represents an important indicator especially for WPP due to the wind influence that affects the turbines' generation and can be calculated as ratio between total hours of operation during the reported period (Top) and total hours of reported period (Tp):

> AF <sup>¼</sup> Top Tp

Several maintenance strategies have been developed as described in [12, 13] with the main objective to preserve the efficiency of power plants' components. Each of these methodologies has its own characteristics, but mainly they focus on internal characteristics of the power plants' components. The industry has adopted for a long period of time maintenance that focuses on corrective actions. But, in recent years, the maintenance plans focus on predictive maintenance where monitoring or inspection activities are performed to determine the best time to start the

Preventive maintenance activity has a direct impact on the reliability of the equipment or components by improving their technical condition and prolonging their life. All maintenance procedures involve both costs and benefits. Maintenance operations are profitable when the costs are lower than associated potential cost of a failure, which these operations are trying to prevent. Most of the maintenance plans on short and medium term do not take into account the operation conditions in which the components operated throughout their runtime but rather are scheduled based on the occurrence of defects and previous repairs. But, in recent years, several applications for continuous monitoring of current operation led to the development of a variety of diagnostic techniques. According to [14], these techniques verify certain parameters and then analyze whether certain components are defective at the moment and can

The main purpose of the maintenance plan is to minimize production costs per unit of energy generated. In general, this is achieved by minimizing operational and maintenance costs, improving turbine/photovoltaic panels' performance and efficiency and lowering insurance policy and equipment's protection. Thus, we proposed two KPIs for determine the loss due to

1. Preventive loss indicator (PLIplan) is the ratio between estimated energy loss caused by planned interruptions and the maximum energy that can be produced during the reported

Wmax\_prod

� 100% ð18Þ

PLIplan <sup>¼</sup> Wlossplan

preventive (planned) maintenance or to corrective (unplanned) maintenance.

maintenance in order to minimize the efforts compared to corrective maintenance.

2.4. KPIs for maintenance operations

16 Recent Improvements of Power Plants Management and Technology

make an estimate of their evolution.

period (usually 1 year).

Where:



Depending on these indicators, the maintenance policy can be schedule in order to minimize the production losses.
