Cost Estimation of Voltage Dips in Small Industries Based on Equipment Sensitivity Analysis

Voltage dip is one of the detrimental power quality problems that can lead to huge financial losses in industries. Its economic impact is not only associated with the quality of the supply but also with sensitivity of electronic controls and equipment of the industry which are susceptible to voltage dips. Mitigating solutions are available but the choice depends on the careful assessment of the economic impact of voltage dips and economic gains of solutions. This paper presents an approach for estimating the economic cost of voltage dips based on sensitivity analysis. The voltage-tolerance curves of the sensitive equipment are obtained from experimental tests under different conditions. From the behavior and interaction of process equipment, different failure modes and economic sensitivity density are determined for different types of voltage dips. Voltage events monitored in the MV-network for several years are assessed to determine the frequency and severity of voltage dips at the customer terminal. The economic values of equipment and processes are assessed to get insight into alternative solutions with more rewarding measures. Then, cost-benefit analysis is performed to compare the economic gains of solutions protecting equipment or processes showing more rewarding economic values.

the severity of the disturbance and the robustness of the process equipment. The severity of voltage dips are often expressed in terms of magnitude and duration. On the other hand, the robustness of process equipment is a measure of the ride-through capability of devices against different voltage dips. The annual economic loss of an industrial plant depends on the number of voltages dips causing load outages, size of critical load, and cost of process interruption. This paper presents an approach for assessing the economic loss of voltage dips in small industrial plants based on equipment sensitivity analysis. The paper is organized as follows: first, a critical review of existing standards and previous work is given in

Review of Existing Standards and Previous Work
As defined in several standards [1] [2], a voltage dip is the sudden reduction in the RMS voltage below a specified threshold followed by its quick recovery. It is mainly caused by short-circuit faults but switching-on of large loads can cause longer-and shallow dips [3]. Severity of the disturbance is commonly expressed in terms of magnitude of the residual voltage, which depends on the network impedance and type of fault, and duration that is related to the fault clearing time of the protection devices [3] [4]. However, additional parameters including the type of voltage dip, location and type of measurement, and more importantly the robustness of process equipment can influence the effect of voltage dips on different types of loads.
The proper operation of modern industries relies on electronic controls and equipment which are often susceptible to voltage dips [5] [6] [7] [8] [9]. The response of industrial processes to incoming voltage dips is directly influenced by the voltage dip ride-through capability of equipment that make up the process. PQ standards like SEMI F47 and ITIC are developed for defining immunities of industrial device against voltage dips at the customer installations [10] [11]. The IEC 61000-4-11/34 standards [12] [13] specify different immunity classes of devices against voltage dips based on testing and measurements. However, different types of equipment exhibit different sensitivities to voltage dips [5] [6] [7] [8] [9]. Besides, different brands of the same equipment type, and even different models of the same equipment brand often have different sensitivity curves. From this perspective, industries can obtain the realistic behavior of their process equipment from laboratory tests. In [14] [15] [16] [17] probabilistic approaches are considered to address the effects of compositions of equipment types and their interconnections on customer process sensitivity.
The disruption of an industrial process caused by voltage dips can result in very sub-stantial costs [18] [19] [20] related to loss of production, damaged equipment, restarting the process, etc. Although there exist solutions to mitigate voltage dips, it is important that facilities evaluate the economic impact of voltage dips before making new investments for reducing the problems. Over the years, numerous attempts have been made to address the economic consequence voltage dips. Some methods concentrating at network level are proposed in [18] [19] while others applied on plant-level losses are suggested in [21] [22] [23]. The accuracy of the overall assessment of the economic loss relies on the precise information about the cost a single process failure, accurate data of voltage profile at the point of connection (POC) of an industrial plant, and equipment sensitivity to voltage dips. Detailed approaches that consider direct and indirect costs are proposed in [22] [24]. However, this method highly depends on the cost figures of every sub-processes in the plant related to all direct and indirect costs which are difficult to obtain; require time-consuming investigation; and often involve confidentiality issues. Another estimation approaches [16] [9] provides guidelines for calculating the costs of voltage dips at customer facility. The standard stipulates the participation of frontline workers, suppliers, finance, accounting, sales and marketing staff to determine the cost related to process stoppage. The sensitivity of the entire industrial process is determined by the most sensitive equipment in the process. In fact, tripping the most sensitive equipment may not disrupt the entire process. Besides, the standard does not consider the interconnections between equipment and sub-processes, and it is not flexible enough to compare morealternative solutions.
With all efforts made so far, the direct evaluation of the economic losses caused by voltage dips is still almost untouched and is a challenging issue. This paper discusses an approach that allows assessing the economic contribution of individual equipment and processes in the manufacturing line. This helps customers to consider more alternative solutions at different levels.

Sensitivity Analysis
In industrial plants, AC contactors, adjustable speed drives (ASDs), programmable logic controllers (PLCs) and personal computers (PCs) are the most common voltage sensitive devices. With this approach, the process of cost estimation depends on the composition, interconnection, robustness and significance of process equipment.

Process Layout
To illustrate the procedures of cost estimation, a manufacturing facility that comprises four independent processes connected to the LV-network is considered as depicted in Figure 2. The complete production of the manufacturing facility will depend on the performance of the four processes during voltage dips. The performance of each process is determined by the ride-through capability of the equipment that make up the process. In this case, process P 1 depends on the immunity of AC contactor (D 1 ) connected in series with ASD (D 2 ), while process P 2 depends on the sensitivity of two PCs (D 3 and D 4 ) supplied from two different phase-voltages and connected in parallel to perform the same task. PLC (D 5 ) and SEMI F47 device (D 6 ) are considered as devices vulnerable to voltage dips in process P 3 and P 4 . It is presumed that • Process P 1 trips if the contactor (D 1 ) and/or ASD (D 2 ) fails, • Process P 2 trips if both PCs (D 3 and D 4 ) fail, • Process P 3 trips if the PLC (D 5 ) fails, and • Process P 4 trips if the SEMI F47 device (D 6 ) fails.

Voltage-Tolerance Curves of Equipment
By generating different magnitude and duration of voltage dips from a programmable source, the voltage-tolerance curves of six conductors, an ASD and three PLCs are obtained from experimental tests conducted at the TU/e PQ lab [30]. Table 1 gives a summary of experiment parameters.

Failure Modes of Load Process
For a facility that comprises "n" independent processes, the maximum possible number of failure modes (N fm ) can be found using Equation (1), where "r" is the number of processes failing at a the same time during a voltage dip.
The actual number of failure modes (m), however, depends on the ride-through capabilities of process equipment and their interaction against various types of voltage dips in the facility.

Sensitivity Values of Failure Modes
Suppose L 1 , L 2 , …, L n are the load compositions of the respective processes such that a particular dip causes a partial disruption of the total load that can be expressed as percentage of loss relative to a total shutdown of the load process. The sensitivity index (Is) of the "m" failure modes can be calculated using Equation (2), where F ppf is matrix of process participation factor of the failure modes and L cp is the percentage of load composition matrix of processes, articulated by Equation (3). The By replacing each failure mode with its corresponding value of sensitivity index (I s ), tables of sensitivity density ( (one-phase dips, two-phase dips and three-phase dips) having "u" magnitude of residual voltage and "Δt" duration.

Voltage Dip Analysis
In

Economic Impact of Voltage Dips
By combining the voltage dip density with the respective sensitivity density, the total annual impact of voltage dips (f 0 ) relative to a complete shutdown of the total load can be estimated using Equation (4), where d k and s k are the annual voltage dip density and sensitivity density functions of each type of dip.

Cost of Voltage Dips
For an industrial plant of size "S cl " critical loads in kVA and experiencing f 0 average outages per year due to voltage dips, the total annual load outage cost (ALOC) can be calculated by Equation (5), where C int is the cost of interruption per unit load (€/kVA). The economic loss due to voltage dips can be reduced by improving the power supply performance and/or improving the equipment ride-through capabilities. In practice, not every mitigating solution is effective to solve all voltage dip problems and the investments on the mitigation solution can vary with the type, size and effectiveness of the solution.

Economic Significance of Equipment and Processes
Before making any investment for reducing the voltage dip problems, it is very important to know the expected contribution of equipment and processes to the economic loss. This will help to rank the economic values of equipment and processes, and paves the way to compare more alternative solutions. Evaluating the economic importance of equipment and processes involves the following steps. For each equipment, process or group of processes, the above steps can be repeated to determine the respective economic values. In each case, the reduction in equivalent interruption (f r ), calculated by Equation (6), indicates the maximum contribution of the equipment, process or group of processes to the economic loss of the facility under consideration, where f am is the annual interruption after a mitigation.

Cost-Benefit Analysis
Investments on PQ solutions could be too expensive or cost competitive as compared with the expected reduction in the outages caused by voltage dips. In this paper, the net present value (NPV) method is used to perform the cost-benefit analysis, and this is given by Equation (7), where f r is annual frequency of reduction in the load outages; C int is cost of load interruption (€/kVA); S cl is size of the critical load (kVA); C 0 is cost of initial investment on the PQ solution (€); OMC t is the annual operating and maintenance cost (€/yr) in the t-year time; n is period of investment (yr), and r is the discount rate. With PQ investment, the main target is cost reduction and this can be achieved by maximizing the avoided economic damages that depends on the future benefits and expenditures. This can be expressed by Equation (8

Results and Discussions
In this section, a case study of industrial facility described in section 3.1 is considered to analyze the proposed methodology for estimating the economic impact of voltage dips.
Experiment results of sensitive equipment and their interaction for obtaining sensitivity density of various types of voltage dips are discussed.

Immunity Tests
The voltage-tolerance curves of six AC contactors against voltage dips with 0˚ and 90˚ point-on-wave dip initiations are shown in Figure 3. Voltage dips below the respective curves cause three-phase power supply interruptions of the load. With a PQ analyser connected to the load terminals, the automatic reengagement of contactors is affirmed by the U-0-U transition in the RMS voltage.
As can be seen from Figure    bring the system to operation. According to the experiment, the sensitivity of the ASD is not only affected by the magnitude and duration of voltage dips but also by the type of voltage dips and the loading condition the ASD.
As can be seen from Figure 4, the ASD is observed to be immune to one-phase dips when the machine is loaded to below 70% of rated load. At fixed and low loading con-

Failure Modes and Economic Sensitivity Values
Depending on the voltage-tolerance curves of equipment, different processes exhibit  different behavior to voltage dips that trigger to the malfunction of the equipment. For the illustrative facility considered in this paper, process equipment are considered tohave the tolerance curves of,  contactor C 1 that trips for u r ≤ 54% and Δt > 20 ms (considering characteristics of both 0˚ and 90˚ point-on-wave dip initiations),  ASD at 75% rated load which fails for one-phase, two-phase and three-phase dips when u r ≤ 70%, Δt ≥ 1000 ms; u r ≤ 70%, Δt ≥ 30 ms; and u r ≤ 80%, Δt ≥ 30 ms,  Programmable logic controller PLC 1 that trips the process when u r ≤ 32%, Δt ≥ 30 ms and u r ≤ 35%, Δt ≥ 130 ms,  PCs and SEMI device that comply with the ITIC and SEMI F47 curves. Figure 6 shows the tolerance curves of the sensitive devices of the plant plotted together against three types of voltage dips and the possible failure modes of the load process are indicated. Examining the behavior and interaction of process equipment subjected to different types of voltage dips (Figure 6), the facility that consists of four processes actually resulted in nine failure modes (F 1 -F 9 ). The vulnerability area of each failure mode varies with different types of dips. Considering 30%, 20%, 10% and 40% as load compositions of the respective processes, Table 2 gives a summary of processes and dip types affecting each failure mode, and their sensitivity index values.
It can be seen from Table 2 that all processes fail for two-phase and three-phase dips in the first failure mode (F 1 ), and participation of the processes P 1 , P 2 , P 3 and P 4 is indicated by the participation factor 1111. Similarly, the ninth failure mode is affected by single-phase dips and this involves only process P 4 . The sensitivity index of the failure modes range from 20% for F 8 to 100% when all processes are affected in F 1 . It can be concluded that the sensitivity index value of any failure mode is affected by the number of processes and the load composition of each process. By assigning values of sensitivity index of failure modes, tables of sensitivity density are obtained for the three types of  Figure 6. Failure modes of the load process obtained from the voltage-tolerance curves of equipment when subjected to (a) One-phase dips; (b) Two-phase dips; (c) Three-phase dips.

Voltage Dip Profile and Economic Impact
From the dataset of voltage events monitored at the point of common coupling (PCC) of a MV-network for four years, the dips that can be seen at the customer terminals are obtained [31]. Corresponding to the voltage dips sensitivity density table (given in Table 3), Table 4 shows the average density of three types of voltage dips having different magnitude and duration. On average, the facility experiences 9.25 dips per year. In this case, most of the dips are three-phase dips and a majority of them are deeper and longer dips.
By combing the annual dip density with the sensitivity density values, the annual equivalent interruption of the facility are obtained as shown in Table 5. It can be seen that the facility would experience about 5.83 annual interruptions equivalent to the 9.25 dips per year and this will incur 5.83 times the economic impact relative to that of a total shutdown of the load process.
A closer look at the contribution of failure modes (Table 6) shows that ~97% of the economic impact is due to tripping of processes in F 1 , F 2 and F 4 while other failure

Mitigation and Economic Gains
A maximum economic gain may be attained with a mitigation strategy that is capable of alleviating the most disruptive voltage dips equipment and/or processes could experience. The economic significance of individual equipment, individual processes and combined processes during the most optimistic situation are summarized in Table 7.
At equipment and process level, maximum economic gain of 38.6% can be attained when the ASD is completely immune followed by the SEMI F47 device and PCs. When group of processes are fully protected, the economic gains increase. In practice, not every mitigation technique is able to solve all dip disturbances. Assuming 50% as minimum economic gain from the most optimistic situations (Table 7), seven conditions all involving group of processes can be considered for comparing alternative solutions. As depicted in Figure 7, combination of two processes, three processes and all processes protected by solutions at "A", "B" and "C" are considered for further cost-benefit analysis.
In  Taking the effectiveness of each solution into account, the reduction in the annual economic losses are evaluated and presented in Table 8. It can be noticed that AVC and DVR would reduce the annual shutdown of the manufacturing facility by less than 30%. This is because most of the dips are deeper which could not be mitigated by these devices. On the other hand, DySC, UPS and FW can effectively reduce the number of  Figure 7. Positions of solutions considered for cost-benefit analysis protecting (a) two processes (A 1 = P 1 P 2 , A 2 = P 1 P 4 , or A 3 = P 2 P 4 ) at "A", (b) three processes (B 1 = P 1 P 2 P 3 , B 2 = P 1 P 2 P 4 , or B 3 = P 2 P 3 P 4 ) at "B", (c) all processes (P 1 P 2 P 3 P 4 ) at "C". voltage dips by ~57% -100% depending on the position of solutions application.

Cost-Benefit Analysis
To compare the cost of voltage dips with cost of solutions, 1 MW critical load of Electronics and Semiconductor manufacturing industries having the same layout as the in the illustration and experiencing the dip density presented in Table 4 are considered here. Average cost of interruption 3 €/kVA and 40 €/kVA are used from surveys for electronics and semiconductor industry [4] [32]. The initial costs and running costs associated with the alternative solutions are summarized in Table 9 [4] [33]. Considering a 10-year investment on the solutions, Figure 8 shows a comparison of  To choose the most profitable position of an acceptable solution, Figure 9 shows the NPVs of investments on the DySC projected over the lifetime of the projects. It can be seen that DySC is the most preferable solution at A 1 and the least acceptable at B 3 in the Electronics industry. In the Semiconductor plant, maximum economic gains would be expected when the DySC is used at C, and the solution is comparatively the least acceptable at A 3 .
When mutually exclusive investments yield positive NPV values, the project with the largest positive value is most preferred. Industrial companies also usually consider PQ investments with higher return rate, and decision can also be made based on the payback times (PBT). In Figure 10,

Conclusion
This paper describes an approach for estimating the economic cost of voltage dips incurred by industrial facilities based on sensitivity analysis. For a case of manufacturing facility with four processes, the approach considers the behavior and interaction of process equipment to derive the number of failure modes. For each failure mode, sensitivity index is determined from the participation of processes within each failure mode and the load composition of processes to the total load. This is useful for obtaining the sensitivity density of different types of voltage dips. A case study is used to apply the approach and average annual economic losses incurred by two industries are compared by taking into account the variation in frequency and severity of voltage dips over several years. By evaluating the economic significance of individual equipment and processes, the method helps to rank their economic contribution. This paves the way to carry out cost-benefit analysis of mitigation solutions with more rewarding economic values that would be possible at different levels. In the analysis, it is confirmed that the economic loss due to voltage dips depends on the frequency and severity of voltage dips, the behavior and interaction of process equipment to voltage dips, type of facility and load composition of processes. The approach also gives more opportunities for customers to consider more alternative solutions, and chose the most optimal solution