The continuous increase on the penetration levels of Renewable Energy Sources (RESs) in power systems has led to radical changes on the design, operation, and control of the electrical network. This paper investigates the influence of these changes on the operation of a transmission network by developing a set of indices, spanning from power losses to GHG emissions reduction. These indices are attempting to quantify any impacts therefore providing a tool for assessing the RES penetration in transmission networks, mainly for isolated systems. These individual indices are assigned an analogous weight and are mingled to provide a single multiobjective index that performs a final evaluation. These indices are used to evaluate the impact of the integration of RES into the classic WSCC 3machine, 9bus transmission network.
European Union countries have a set of specific targets to promote the use of energy from Renewable Energy Source (RES) in accordance with the Directive 2009/28/EC of the European Parliament [
The 16% of global final energy consumption comes from renewable sources during 2012, with 10% coming from traditional biomass, which is mainly used for heating and 3.4% from hydroelectricity. New renewable sources (small hydro, modern biomass, wind, solar, geothermal, and biofuels) accounted for another 2.8% and are growing very rapidly [
Nevertheless, RESs have not been a significant part of the energy mix for the vast majority of countries around the world, fact which has led governments to provide incentives to entities that are interested in investing in RES electricity generation, in most cases using wind and solar power.
Consequently, it is of crucial importance to investigate how RES generation affects the network’s operational ability and which potential configurations could prove beneficial. Hence, a series of technical aspects must be considered by the planners in order to evaluate the pros and cons of such penetration. In particular, the minimization of power losses has so far been the most important issue for the planners [
Indexrelevant literature references.
Reference  Power losses  Voltage  Line capacity  SCL  Emission reduction  Spinning reserve 

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Yes  No  No  No  No  No 
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Yes  Yes  No  No  No  No 
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Yes  Yes  Yes  Yes  No  No 
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No  Yes  No  Yes  No  No 
Present work  Yes  Yes  Yes  No*  Yes  Yes 
There are several aspects to be considered in order to integrate RES into traditional networks. However, there are two parameters that have high impact on the integration of RES plants in the network: the selection of the size (rated capacity) and the installation’s location of such plants. This paper investigates these effects by developing a series of indices, spanning from power losses to GHG emissions’ reduction, which quantify this impact and provide a tool for assessing the RES penetration in transmission networks, mainly for isolated systems.
The paper is organized as follows; Section
In this section, the assessment indices are presented. Six individual indices are considered in this paper to evaluate the steadystate performance of the network, each one relating to a specific technical aspect. Table
Indices’ acronyms.
Index acronym  Acronym meaning 

ILp  Active power losses index 
ILq  Reactive power losses index 
IVD  Voltage profile index 
IC  Line capacity index 
IEm  Emissions’ reduction index 
ISR  Spinning reserve index 
In particular, ILp and ILq relate to power losses, active and reactive, respectively. IVD is used to define the voltage deviation. IC is related to the system’s line capacity usage; IEm relates to the GHG emissions reduction and ISR to the spinning reserve of the system, meaning the total synchronized capacity, minus the losses and the load [
The following indices are used to evaluate the changes on the total active and reactive power losses:
Near unity values of these indices imply a maximization of the positive effect of RES integration on losses.
Voltage issues are of critical significance as they are an indicator of the network's condition. The following index evaluates the maximum voltage deviation of the configuration under study:
One important aspect of RES integration is the altered branch power flows, meaning the different power flow allocation through the lines of the network. A key parameter to optimally introduce RES plants in a network is the relief in the network’s line flows. In other words, the introduction of RES in the network should help in reducing the transmission line exploitation and lead to greater tolerance in demand growth.
The IC index is used to evaluate how the configuration under study affects the total branch flows of the network:
CO_{2} emission production is maybe the most important environmental factor that RES integration has to tackle. This is to be achieved through minimization of the use of conventional, fossilfuelled plants. At first sight it seems that the larger the RES penetration, the less the need for conventional plant use. However, this is only partially true since RES effects on the system’s reliability due to their variability and unpredictability have to be accounted as well in order to correctly evaluate the conventional generation requirements.
Hence, the following index was developed in order to appropriately calculate the CO_{2} emissions' reduction for every possible network configuration. The planner can include this information when assessing the system before reaching to a decision. Near unity index values represent nullification of the emissions produced:
Large RES integration radically alters the system's reserve requirements, both shortterm and long term [
Three auxiliary indices are introduced in this section. These indices are not a part of the evaluation process, but they are very helpful for observing the system’s status.
The first and most commonly used of these is the
Furthermore the other two indices developed are similar to each other and regard the RES rated capacity in relation to the system's capacity.
These two indices are the ratio of the RES rated capacity over the capacity that existed
The assessment indices presented in the previous section of this paper are used on a classical test network: WSCC 9bus system which is depicted in Figure
Bus data.
Bus  Type 



5  PQ  90  30 
7  PQ  100  35 
9  PQ  125  50 
 
Total  315  115 
Branch data.
From 
To 



Rated ampacity (MVA) 

1  4  0.000  0.0576  0.000  250 
4  5  0.017  0.092  0.158  250 
5  6  0.039  0.170  0.358  150 
3  6  0.000  0.0586  0.000  300 
6  7  0.0119  0.1008  0.209  150 
7  8  0.0085  0.072  0.149  250 
8  2  0.000  0.0625  0.000  250 
8  9  0.032  0.161  0.306  250 
9  4  0.010  0.085  0.176  250 
Reactance values are in pu on a 100MVA base.
Generator data.
Bus 




Fuel type  Efficiency [pu] 

1  250  75  300  −300  Diesel  0.4 
2  300  90  300  −300  Coal  0.34 
3  270  81  300  −300  Lignite  0.38 
Oneline diagram of the test network: WSCC 3machine, 9bus system [
It should be noted that the minimum active power generation is set to 30% of the maximum generation of every generator in order for the system to be more realistic. The fuel type and efficiency selected for each generator are generic but realistic. Furthermore, the reader can find the analytical methodology of emissions production calculation that was utilized for this work in [
A special MATLAB code was developed to obtain the solution of the optimal power flow problem using routines provided by MATPOWER [
The MATPOWER data file has been edited in order to assign plant type and efficiency values to each generator. The algorithm caters for several other fuel types.
In this section, the results for each individual index of the previous section are presented. The MATLAB script that was developed executes a series of simulation scenarios. For this particular test network, the scenarios investigated are for 10 MW up to 150 MW of RES rated capacity (i.e., from
The results obtained regarding the power losses of every configuration are presented in Figures
Active power losses (ILp) versus location of RES power plant and load level penetration.
Reactive power losses (ILq) versus location of RES power plant and load level penetration.
Another interesting aspect of the results obtained is the behavior of the network when a generator shutdown takes place. This occurs at the 70 MW (
Figure
Voltage profile (IVD) versus location of RES power plant and load level penetration.
IC index is a way to measure the potential benefit of RES penetration in terms of branch power flow alteration. If a configuration leads to a relief of the power flows through the network’s transmission lines, then the network becomes more tolerant to load growth. As can be seen in Figure
Remaining Line Capacity (IC) versus location of RES power plant and load level penetration.
As can be seen in Figure
Emissions’ reduction (IEm) versus location of RES power plant and load level penetration.
In Figure
Spinning reserve (ISR) versus location of RES power plant and load level penetration.
In order to create a general index that allows evaluating the performance of the network considering all the previously defined indices (except from the auxiliary), a new approach is presented in this paper combining the aforementioned indices into a single multiobjective index (IMO).
This multiobjective index is defined as
Although the weight selection is decisive for shaping the results of the evaluation, the literature is not very clear on how to define the proper values to each index. It is common, though, that the appreciation of every factor is left on the planner's judgment and personal experience [
It is apparent that the results of the multiobjective assessment employed in this work strongly depend on the weight selection for each individual index. The weight values are of course defined by the planner in respect to his objectives. Consequently, every planner could potentially reach to a different decision with regard to his subjective judgement.
As a first general approach to the weight selection, power losses indices, namely ILp and ILq, are considered the most important factors and, therefore, are given the largest weight values summing up to 45% of the total weight value. Specifically, ILp, which relates to active power losses, has been so far considered the most important factor as it expresses the direct cost of losses that utilities tend to try and minimize. ILq has also received a significant weight value as reactive power support, an ancillary service, is becoming increasingly important to TSOs, as described in [
Indices’ weight selection.
Index weight  Absolute value  Normalized value 


30  0.30 

15  0.15 

20  0.20 

20  0.20 

8  0.08 

7  0.07 
 
Total  100  1.00 
Utilizing the weight values of Table
Multiobjective assessment (IMO) versus location of RES power plant and load Level penetration utilizing the weight values of Table
It comes as no surprise that the best results attained are for bus 9, since it presented the best performance for almost every individual index. It is also the bus with the largest load of the network, which means that the RES generation immediately supplies it, minimizing the need for distant generators to cover the demand. It has to be noted that for bus 9, the IMO index values are relatively close to each other, which leaves the planner with a variety of possible configurations that could prove beneficial for the network's planning process. Bus 5 is proven as the second best in performance, fact which also widens the variety of the planner's choices.
Bus 5 is a load bus as well. This suggests that RES integration is usually more beneficial when located at load buses or buses close to the load. The best case is proven to be the 150 MW (
In order to investigate this, the
Indices’ weight limits for the Monte Carlo simulation.
Index weight  Lower limit  Upper limit  Expected value 


20  40  30 

10  20  15 

10  30  20 

10  30  20 

5  11  8 

5  9  7 
 
Total  60  140  100 
In Figure
Monte Carlo indices’ weights For maximum IMO value.
Index weight  Absolute value  Normalized value 


39.31  0.4550 

10.80  0.1251 

10.88  0.1259 

10.01  0.1159 

10.03  0.1161 

5.36  0.0620 
 
Total  86.40  1.0000 
Monte Carlo indices’ weights For minimum IMO value.
Index weight  Absolute value  Normalized value 


20.37  0.2258 

19.03  0.2110 

26.58  0.2947 

10.53  0.1168 

5.24  0.0581 

8.45  0.0936 
 
Total  90.20  1.0000 
IMO values for the 70 MW (
IMO values for the best case scenario of the Monte Carlo simulation.
A number of indices that assess the impact, positive or negative, of RES integration were introduced in this paper. These indices cover a wide spectrum of technical aspects that are crucial to the network’s operational procedure, spanning from power losses to emissions’ reduction and system security. Thus, an attempt to connect the operational stage with the planning process of a power system has been made. These individual indices are assigned a specific weight and are incorporated into a single multiobjective index that caters for the final evaluation of each configuration under study. The weight selection is proven to be crucial to the final outcome of the evaluation. This was investigated through a Monte Carlo simulation that pointed out the potential IMO variation of the same network configuration when the weight selection varies between certain limits. Therefore, this work pins out the need for careful consideration of every factor when planning with RES, especially for isolated systems that exacerbate possible contingency situations, since there can be no external support from other interconnected networks that can act as a source or sink of energy. In conclusion, this work examines the impact of RES integration in the system’s operational stage in order to determine the technical constraints that directly or indirectly affect the system planning process and, consequently, define the parameters for shaping the National Action Plans of each country.