Abstract
The penetration of DG in electrical distribution systems has many benefits. The paper highlights the impact of DG penetration at different load centers and different operating conditions in a distribution feeder. The impact of DG penetration on feeder voltage profile that depends on the size and location of DG in the system is illustrated. Mitigating methods are used to reduce the effect of voltage disturbances. Economic assessment studies are used for assisting in the economic choice of mitigating methods. Economical aspects of distribution systems connected to DGs are considered through the analysis of the life cycle cost of these distribution generation sources. Maintenance strategies are illustrated and discussed to keep these sources always ready for operation regarding minimization of maintenance cost. Technical and economical assessments depend on the availability of historical data for disturbances cost including damages and cost of disturbance mitigation using different mitigation methods. These data are difficult to be available for different types of loads. Therefore, load indices, K1, K2, and K3, are proposed in this paper for the different loads as referring it to reference load has available data to overcome the challenge of data shortage. Also, a techno-economic assessment index F is proposed for the assessment of the impact of mitigating device improving cost and its feasibility. PSCAD/EMTDC simulation software package is used in this analysis. The results show that the proposed techno-economic assessment methodology facilitates the decision of choosing the mitigation method for power quality problems and to overcome the challenge of data shortage in the techno-economic assessment.
1. Introduction
Power quality is an important issue during the current decades due to the mass use of electronic devices, and it’s more sensitive to voltage variations and the use of renewable resources for power generation [1]. Electric power quality disturbances are significant economic consequences for different types of facilities. The main terms that are used in association with power quality are voltage sag, interruption, long-duration supply interruption, transients, voltage unbalance, and harmonics [2–4].
Voltage sags are the most important power quality concerns for customers. According to IEEE standard 1159, Figure 1 illustrates definitions of voltage sags, swells, and transients (IEEE 1159: 2009) as it is the RMS reduction in the AC voltage at power frequency from half of a cycle to a few seconds’ duration.
The primary source of voltage sags observed on the public network is the electrical short circuit occurring at any point in the electricity supply system. The short circuit causes a very large increase in the fault current, and this, in turn, gives rise to large voltage drops in the impedances of the supply system. Short circuit faults are an unavoidable occurrence on electricity systems. An example of a voltage sag due to a downstream fault current is shown in Figure 2.
This results in some financial compensation for parties incurring losses [5]. Location of sag sources is crucial in developing mitigation methods and deciding responsibilities. Technologies used for mitigating power quality are translated in terms of cost and the expected improvements in the system performance they can provide. Thus, the improved performance is translated into economic benefits. With the costs of the different technologies and the expected benefits, comparison of the different technologies yields the best return on investment [5].
The use of distributed generation (DG) as a source of active power in the system is effective to mitigate the voltage regulation problems. The DG size and location in the system are important; otherwise, adverse effects, such as misoperation of protection relays, may occur [6, 7]. DG is used at different positions and with different ratings.
This paper introduces a technical and economical assessment of the voltage sag effect in the distribution system connected to DG. Life cycle cost analysis for mitigating equipment and renewable energy source is to be made to assist in the study of the economic assessment and taking the decision of choosing a mitigating method. Therefore, the presented work proposes a fast preliminary assessment of the economic and technical assessment of voltage sag mitigation. Thus, fast and efficient tools are necessary to analyze the feasibility of these systems in the most effective and accurate way. Financial assessment is achieved when both the return on the total capital invested and the return on the paid are at a sufficient level of innovation. The study is carried out in steady-state and fault conditions using PSCAD/EMTDC.
The paper is organized by starting with a background of DG in electrical distribution systems in Section 2. Then, the life cycle cost (LCC) model for main renewable DG technologies (solar and wind) energy is explained also in Section 2. In Section 3, the voltage sag analysis is introduced with explaining of losses, mitigation methods, and its economic considerations. For the techno-economic assessment, the main challenge is the shortage of data. Therefore, to overcome this shortage, indices are proposed in Section 4. The validity of the proposed indices is tested via an electrical distribution system. The techno-economic assessment is carried out using the proposed indices in both steady-state and fault conditions using PSCAD/EMTDC in Section 5. Finally, the main conclusions are given in Section 6.
2. Distributed Generation Background
2.1. Renewable DG Integration
Distribution generation is “small-scale generating units located close to the loads that are being served.” It can be classified as nonrenewable and renewable energy resources [8]. The former includes reciprocating engines, micro-turbines, combustion gas turbines, fuel cells, and micro-combined heat and power (CHP) plants. The latter includes biomass, wind, solar PV, geothermal, and tide power plants [9].
Solar PV technologies require high capital investment cost. It has the advantages of long-life service and silent operation. It requires low maintenance but is redundant [1].
Wind turbine is classified as vertical axis wind turbines and horizontal axis wind turbines. It is characterized as emissions-free and requires no fuel [1].
Comparing DG with centralized generation, DG has the advantage of lower capital cost because of its small size, it can be easily assembled and installed within a short time, and the power delivered can be increased or decreased by additional or removing modules [10]. Also, DGs are connected very close to the load. Therefore, reduction in the cost of building new transmission and distribution lines can be achieved. Additionally, the closeness to the load reduces the price of transporting electrical power to the load. When the DGs have excess power not needed by the load, the excess power is delivered to the grid. Table 1 illustrates the summary of some renewable DG technologies costs [11].
2.2. Life Cycle Cost for Main Renewable DG Technologies
Life cycle cost (LCC) is important to assess the economic feasibility of engineering systems. Electrical energy systems require more capital investment and more operating costs compared to other systems. Renewable energy sources such as wind energy and solar energy have an important role in energy production scenarios. The cost of energy systems includes the initial cost of delivering components of the system, fuel, maintenance, wages, and other costs. Therefore, the cost of kWh of electricity is determined. However, many different energy technologies exist for generating electricity (coal-fired steam power plants, gas turbine combine-cycle power plants, fuel cells, hydropower power plants, wind power, solar, and many others), and comparison between these different technologies needs economic assessment for each of these technologies [19].
2.2.1. LCC Model of Solar PV System
The LCC model of solar PV system composed of the following cost categories: planning CDev, PV panels CPanel, electrical apparatus CElec, mounting structure and civil work CCivil, in addition to operation and maintenance CO&M [13] as follows:
2.2.2. LCC Model for Wind Farm
The life cycle of wind farm passes through four stages: development stage, implementation stage, operation stage, and decommissioning stage [10]. The development stage starts by finding suitable site that has suitable wind characteristics. Then, starting the design, prepare the equipment and construct it where the whole capital is used. Next is the operation stage which is the longest stage; hence, the design continues to last for 20 to 25 years during this, and the costs are distributed on maintenance, spare parts, and overheads. Finally, the decommissioning stage has two choices either removing the turbines or replacing them with newer technology. Therefore, the LCC model of wind farm is divided into four categories as wind turbines cost CWT, civil work and installation Ccivil, electrical apparatus CElec, and operation and maintenance costs CO&M as follows:
3. Voltage Sag Analysis
The characteristics of voltage sag are the voltage reduction magnitude and its duration. For single-phase systems and three-phase balanced systems, this characterization is fine [14]. Whereas for three-phase unbalanced sags, the three individual phases would be affected differently; hence, three different magnitudes and three different durations are found and the most affected phase is taken as a measure of sag. The performance of voltage sags is obtained by the following:(a)Long-term monitoring of voltages at system buses [15, 16]. It provides information about the expected severity and frequency of voltage disturbances. Also, it allows the utility to study the power quality level and guide in a realistic way the investment in using devices for voltage sag mitigation [1, 6].(b)Fault positions method which is a commonly used method for voltage sag estimation. Large number of faults are generated throughout the power system, and corresponding magnitude and duration of sags are measured and computed.
Voltage sags can be calculated and analyzed utilizing two main types of simulation tools: custom-made tools usually developed on commercial software platforms and general-purpose simulation packages, e.g., PSCAD/EMTDC.
3.1. Voltage Sag Losses
The total losses caused due to voltage sag can be expressed according to the following equation:
The nominal loss value of an industrial process “maximum loss value” is defined as the financial loss incurred due to process interruption during peak production period [9, 17, 18]. Two main parameters are needed to estimate financial loss caused by voltage sag and short interruption which are the nominal loss value and process failure risk. It is given [19] by the following equation:
The nominal loss for existing customers in the system is determined from customer surveys. Having analyzed the results from the survey, three categories of voltage sag profile were resulted as most meaningful for estimation of costs which are as follows [14]:(1)Group A includes 10 or less voltage sags per year with residual voltage less than 40% of nominal for sag duration shorter than 100 ms(2)Group B includes 10 or less voltage sags per year with residual voltage less than 40% of nominal for sag duration shorter than 100 ms and 5 or less voltage sags per year with residual voltage less than 70% of nominal and duration ranging from 100 ms to 300 ms(3)Group C includes 1 interruption with duration of 3 minutes or more
3.2. Voltage Sag Economic Analysis
Economic analysis for any investigated system can be evaluated using the net present value method [19, 20]. The mathematical expression to evaluate the NPV is reported [21, 22] as follows:where C0 is the cash flow when the time is zero, Cy is the year cash flow, i is the interest rate, and y is the year of investment.
Thus, the NPV sign positive or negative indicates the feasibility of the investment and therefore the economic convenience.
Benefit-cost ratio (B/C) and payback period (PP) are two economic measures used for the optimal selection of voltage sag mitigation solutions [19, 23]. The benefit-cost ratio (B/C) is an economic measure that illustrates the feasibility of using the voltage sag mitigation solution. It is given by [6]where A is the saved annual cost accumulated/year after employing a mitigation solution, is the present worth factor, I is the annual interest rate, t is the time period in years, AOC is the cost of the annual operation, IC is the cost of investment solution, and T is the mitigation devices’ lifetime.
The payback period measure shows the period (e.g., number of months) of benefits required for the project to break even [24]. It is calculated for a voltage sag mitigation solution as follows:
Generally, a solution having the least payback period is mostly preferred.
3.3. Voltage Sag Mitigation
As the electrical loads in the electrical distribution systems include electronic devices and components, power quality is to be improved by using suitable fast response compensator as Static VAR Compensator (SVC), thyristor control series compensator (TCSC), and UPFC (Unified Power Flow Controller), STATCOM, and (DVR) dynamic voltage resistor. The major technologies available for voltage sag mitigation are [7, 24] Uninterruptible Power Supplies (UPS), Static Transfer Switch (STS), Sag Proofing Transformer, Dynamic Voltage Restorer (DVR), and STATCOM.
Equations (9)–(12) illustrate the cost functions for SVC, TCSC, and UPFC and STATCOM in $/kVAR [25]. Also, Table 2 illustrates a sample of data for cost of some mitigation devices.
Economically, the value of the service provided is the most important parameter in voltage sag management given by equation (13). The positive value indicates a gain in return of investment for voltage sag mitigation. Maximizing the “value of service” brings maximum profit [15].
3.4. Economic Analysis of Voltage Sag Mitigation
To make economic study for voltage sag mitigation technologies, cost of equipment operation and maintenance is a major item to be considered. Maintenance is defined as a combination of all technical, administrative, and managerial actions during the life period of equipment. For example, the annual cost of maintenance for STATCOM’s is 5% of its capital cost per kVA [13]. However, maintenance and operation cost for wind energy and PV energy as a renewable energy source is more than STATCOM [14, 15].
3.4.1. Life Cycle Costing (LCC) Model for Equipment
As previously mentioned in Section 2.2.2, the LCC model of equipment is also divided into four categories: development costs CDev, equipment Ceq, installation Cin, and operation and maintenance costs CM.
The condition of any equipment and its components with its operation during its life period can be represented as illustrated in Figure 3. As shown in Figure 3(a), any equipment starts its operation in new condition. As the time of its operation increases, its efficiency begins to decrease, and as the time of operation passed, its condition is deteriorated, and this can be represented by a decaying curve (condition versus time). This curve may be straight line or in general as shown in Figure 3(b). After a certain time interval, it becomes in condition less than new and some spare parts require replacement, and this is represented at the first point on the curve (failure starts to occur). As the time of operation increases more, the equipment condition will be less till the indicated potential failure point, repair is required at the indicated functional failure F, and the equipment requires major maintenance or to be replaced. Figure 3(b) shows system condition during its life period with adopting preventive and corrective maintenance according to the system time schedule.
(a)
(b)
To put the system and its components in a ready state of operation during its life period, the following maintenance types are made and scheduled. Maintenance is the main factor that any system will be in a ready state for operation during its life period. Maintenance is defined as a combination of all technical, administrative, and managerial actions during the life period of an item intended to retain it or restore it in a state in which it can perform the required function [17].
3.4.2. Maintenance Types
Maintenance is essentially classified as preventive maintenance and corrective maintenance. Preventive maintenance is classified as preventive scheduled maintenance and preventive condition-based maintenance [18].(a)Preventive maintenance Preventive maintenance (PM) is defined as the maintenance, which is carried out before failures occur. It is divided into the following:(i)Preventive scheduled maintenance: it is carried out according to an established time schedule(ii)Preventive condition-based maintenance: it is based on the performance and parameter system components monitoring for the prediction when maintenance is needed [18](b)Corrective maintenance Corrective maintenance (CM), which is the maintenance carried out after fault to put the item into a state to perform components required function [19].
3.4.3. Maintenance Cost Optimization
The main objective for maintenance optimization is as follows [16]:(a)The total costs for maintenance must be minimized(b)The maintenance should be done to have high availability and safety operation of the equipment. Maintenance cost must be as low as possible(c)The equipment after maintenance should have a long lifetime
Hence, it is required to balance between preventive and corrective maintenance regarding the relationship between those maintenance types. Figure 4 illustrates the total cost required in relation with maintenance.
Minimization of total maintenance cost through equipment life period and due to its use and operation is required, as it deteriorates, as shown in Figure 4. This deterioration is measured as the increase in the operation and maintenance (O&M) costs [18]. These costs will reach a value at which it is preferred economically to replace the equipment. This requires to have an optimal replacement policy for total cost minimization. The equipment components should be replaced by an identical one to return the equipment in new condition after replacement.
4. Techno-Economic Assessment for Voltage Sag Mitigation
Techno-economic assessment for voltage sag mitigation depends on the availability of historical data for disturbances cost including damages and cost of disturbance mitigation using different mitigation techniques. These data are difficult to be available for different types of loads.
4.1. Requirements of Techno-Economic Assessment
The requirements for adopting any techno-economic assessment depend on data collection, data analysis and report, and project formulation.
Technical assessment is carried out according to the following:(a)The electrical distribution system is simulated(b)The bus voltages are obtained by running load flow analysis(c)Different FACTS are considered with different size and the voltage profiles are obtained(d)The electrical losses are calculated for each value of DG at each bus(e)The impact of mitigating device is given by the analysis and comparison with the obtained results(f)The impact of DG penetration is given by the analysis and comparison with the obtained results(g)Technical system improvement in voltage system profile is given by system electrical losses and system disturbances after mitigation is obtained
Economical assessment is carried out according to the following:(a)Annual cost of system voltage disturbances before mitigation is computed(b)Mitigating devices that include annual initial investment cost, annual repair, and maintenance cost are determined.(c)Annual cost of system voltage disturbances after mitigation is computed.(d)The total annual cost improvements of electrical system performance are obtained.
Therefore, the techno-economic assessment requires comparison between costs associated with the impact of disturbance (damages and costs associated with interruption) and the cost of equipment required to improve the technical performance. Figure 5 illustrates annual outages and its cost on the right side, and the left side represents the cost of mitigating equipment. Then, cost-benefit analysis (comparison between these two costs) is considered to have the feasible techno-economic solution.
4.2. Proposed Load Indices
The main challenge for good techno-economic assessment is the availability of data. Therefore, it is proposed in this paper to formulate load indices for any load data depending on the reference load data. Therefore, it is proposed to use the following proposed indices as given in the next sections.
The proposed indices are used to overcome the shortage of data for different electrical loads. The proposed strategy for techno-economic assessment of DG in electrical distribution systems started with data collection for the disturbances occurred in the different industries and the outages occurred. Field data are collected from project owners, construction industry consultants, contractors, and working engineers. The collected (quantitative) data were gathered by face-to-face interviews, online contact, mail, and phone.
In Figure 6, the electrical loads are classified into different sectors such as industrial and commercial. Each sector concerns different types of loads, e.g., industrial sector includes paper industry, textile, and chemical.
4.2.1. Reference Load Data
Load indices are defined as the ratio between certain reference energy consumption of different types of events (categories A, B, and C) for residential, commercial, industrial, …, etc.
Semiconductor industrial load is taken as reference load as shown in Figure 6 as it has complete and enough historical data about system supply interruption cost, and disturbances cost is taken as the annual reference load energy consumption which is (Y) MWh. Therefore, load in the same reference load sector suffers from shortage in data and has an annual load energy consumption of (X) MWh.
4.2.2. The Proposed Load Sector Index (K1)
It is proposed that k1 is the ratio between the annual energy consumption of the load, and the annual energy consumption in the reference load (X/Y) is the load sector index. Therefore,
Then, the load sector index can be used to define the cost of interruption of certain load through the following equation:
4.2.3. The Proposed Load Type Index (K2)
It is proposed that K2 is the load type index, which is the ratio between the annual energy consumption of the load sector and the annual energy consumption in the reference load sector. Therefore,
4.2.4. The Proposed Disturbance Type Cost Index (K3)
Due to the common availability interruption event cost in electrical loads, K3 is the voltage sag event cost referred to the voltage sag event interruption cost. Therefore,
Table 3 gives the weighting factors for the cost of the voltage sag event that are expressed in per unit of the cost of the interruption. The weighted events can then be assumed [21]. K3 is used to calculate the number of equivalent interruptions to get the total cost of all the events using the interruption cost. Table 3 illustrates an example of the weighting factors or different voltage variations referred to as interruption [5, 21].
For the different types of loads of the different load sectors, it is proposed that
4.3. The Proposed Methodology of System Data Preparation
Using the proposed indices given in Section 4.2 (K1, K2, and K3), the required data can be calculated to overcome the problem of data shortage. Figure 7 shows the flowchart for the steps adopted for preparing the data used in techno-economic assessment for voltage sag mitigation in distribution systems which suffer from shortage in historical data about cost of voltage sag disturbances.
4.3.1. The Proposed Techno-Economic Assessment Index (F)
It is proposed that the techno-economic assessment index is the cost of voltage sag improvements referred to the annual cost of mitigation scenario used as given in equation (21). As the total annual cost of each scenario for voltage sag mitigation and its corresponding net annual cost of improvements are computed, the analysis and comparison of the obtained results illustrate the impact of the mitigating device and its feasibility.
Therefore, for feasible solutions F, it is more than 1, and for nonfeasible solutions, it is less than 1.
5. Application of the Proposed Techno-Economic Assessment Method
For the validity of the proposed strategy, a radial distribution feeder, shown in Figure 8(a), is used. The feeder feeds four electrical loads which are part of IEEE 34 electrical bus distribution system [23]. The system is simulated by PSCAD/EMTDC as shown in Figure 8(b). The simulation is verified by comparing the results of studying the system operation at normal condition with that published in [23]. The close agreement between both results is achieved. Different operating scenarios with DG of less than 10 MW capacity connected directly at the different system buses are considered.
(a)
(b)
5.1. Results of Voltage Sag Technical Assessment with DG Connected
The simulation is carried out in the following cases:(a)Without inserting the DG into the system and the voltage at each bus is measured(b)With implementing the DG with different values and at the different buses and the voltage at each bus is measured(c)With implementing the DG with different values and at the different buses with three-phase faults through resistance at different buses and the voltage at each bus is measured
Figure 9 shows the voltage for the system buses without DG connection. Figures 10(a)–10(d) illustrate the system buses voltages with different values of DGs connected at buses 1, 2, 3, and 4, respectively.
(a)
(b)
(c)
(d)
Simulation of results indicates that the connected DG shares the responsibility of supplying the required demand with the substation. The summary of the simulation results is given in Table 4. Table 5 and Figure 11 illustrate the system losses for different values of DG at different locations. It can be seen that the DG reduces the losses due to close proximity to loads. Installing DGs close to loads and in modular sizes matches the local load or energy requirement of the customer, and reduction of transmission and distribution losses is achieved.
Also, simulation is run considering cases of three-phase fault through resistance at different buses at different locations. Table 6 illustrates the summary of simulation results of different values of DG and places when three-phase fault happens at each bus. Figure 12 shows the relation of bus voltages for different values and different locations of DG when three-phase fault occurs at the different system buses. It is noticed that the least electrical losses and best voltage profile occur at bus 3 with DG value of 6.5 MW. It is clear that the implementation of DG as an active power source has an impact on improving the buses voltage in the distribution network.
(a)
(b)
(c)
(d)
A number of cases of technical studies are simulated on radial distribution system while the change of the size and location of DG in the system occurred. DGs connected very close to the load are the best case. They reduce the losses and cost of building a new transmission and distribution lines. Also, DG improves power quality and reliability.
5.2. Results of Techno-Economic System Assessment
For data preparation of the system studied shown in Figure 8, assuming load 1 is a semiconductor industrial load has 18 events of voltage sag disturbances per year which are classified as illustrated in Table 7. Based on the disturbances weights index K3 given in Table 3, the system equivalent events are 11 interruption events per year. Table 8 illustrates the data of the reference load, L1 and L2. K3 is calculated with the total number of events based on interruptions in Table 3. Load indices K1 and K2 are calculated and given in Table 8 from equations (17) and (20).
The cost per one event of interruption is 50000 $ for the reference load as it is a semiconductor industrial load with electrical annual energy consumption of 100 MWh [22]. The improvement cost of 20% improvement is illustrated in Table 9. The equivalent interruption event is improved from 11 events to 8.8 events and the disturbance cost from 192500 $ to 154000 $.
It is assumed that the 20% improving in this system required 10 MVA, and the total cost per year for each mitigation device is calculated from Table 2 and equations (9)–(12) as illustrated in Table 10.
Therefore, the saving due to the use of the different mitigation devices in case of 20% improvement as it is the difference between the total cost/year and the improvement cost is illustrated in Table 11. Therefore, and with the proposed system data, the system is feasible with using STATCOM, SVC, TCSC, and UPFC, and the mitigating device for minimum cost is SVC as its cost is 1349.66 $/year, and the saving is 37150.34 $/year.
6. Conclusion
Based on the expected costs associated with the power quality variations, the improved performance is translated into economic benefits. With the costs of the different mitigating technologies used and the expected benefits, techno-economic assessment is performed to choose the optimal scenario of the case of lowest total costs which includes the costs of the power quality mitigation equipment based on the study of equipment life cycle cost and maintenance cost.
As the main challenge for the techno-economic assessment is the availability of historical data for cost disturbances in the different load types, and to overcome the data shortage about the cost of voltage disturbances in different load types, proposed indices are suggested to have it.
In this paper, three load indices K1, K2, and K3 are proposed to overcome the main challenge for the techno-economic assessment which is the availability of historical data for the cost of disturbances of the different load types. Also, a techno-economic assessment index F is proposed for the assessment of the impact of mitigating device improving cost and its feasibility.
Technical and economic studies are introduced in this paper including the impact of DG penetration at different load centers and different operating conditions in a distribution feeder. The economic assessment is achieved using the proposed indices. The technical system performance is checked using PSCAD/EMTDC software. Hence, through techno-economic assessment, best decision for choosing a suitable mitigating device is achieved, regarding the cost of power disturbances and the cost of mitigating devices used.
It is also concluded that recording the economic effects of voltage disturbances is important and necessary to develop a database for the cost of voltage sag disturbances for the various load types to overcome the main challenge in the techno-economic assessment of evaluating voltage sag mitigation methods.
Data Availability
The data can be obtained from published references cited within the article.
Conflicts of Interest
The authors declare that they have no conflicts of interest.