SQUEEZING MARGINS: REDUCING COSTS WHILE BALANCING RISKS. G.A. Bloemhof, J. Knijp. KEMA T&D Power, the Netherlands

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1 SQUEEZING MARGINS: REDUCING COSTS WHILE BALANCING RISKS G.A. Bloemhof, J. Knijp KEMA T&D Power, the Netherlands Liberalising the energy market increased the awareness of transmission and distribution companies for optimising network activities and reducing costs. Network operators have to balance between performance, risks and costs. The traditional approach leads to sub-optimisation. When planning, adapting or operating existing power supply systems one can save by using the system and its components closer to their limits. Increased use of margins means: taking more risks. By the end of the 2 th century - especially in the liberalising countries - an increase in optimising the activities of electricity transmission and distribution companies became apparent. Former practices could be characterised by maximising performance (reliability/safety), intuitive cost approach and avoiding risks. The new ambitions demand customer-oriented performance and thus cost effectiveness, requiring integral cost methods and controlled risks. Major concerns of network operators are about asset management: reducing costs and postponing investments, while keeping up reliability and power quality. New methods and techniques like life cycle costing, risk management and performance management are introduced, as in the left figure. Measures resulting in cost savings can be classified according to different aspects: planning or operations system oriented or component oriented time versus capacity limit Classification of measures alone is not enough. Each measure effects different dimensions like cost, risk and length of life. Dimensions concern technical constraints, economic goals, reliability and power quality and environment. Using practical cases, the paper demonstrates how investments, reliability and technical constraints can be handled jointly in one integral decision process. The examples prove that by doing so savings can be realised. The right figure shows how to compare margins for different aspects. The paper shows that margins and risks are inherent multidisciplinary problems. Decreasing costs, trying to maintain quality, or improving quality with minimal expenses, demands a balance between all aspects. Making decisions, when different scenarios are possible, brings risks. Risk is both in uncertainties about the future and in incomplete data. Comparing disciplines means using weighing factors, using break-even analysis or sensitivity analyses. A uniform system comparing all the disciplines involved, achieving optimal solutions and reaching a balance between all constraints is presented. Relieving a limit through working closer to another is delicate. Tools are available, however a systematic and consistent approach is required to use the system to its edges. An integrated analysis allows avoiding or postponing costs. The examples prove that significant savings can thus be achieved. Maximum Customer oriented supply (Cost/benefit analyses) SC 5 PERFORMANCE -5-1 Rational (Lifecycle costing) COST RISK Avoiding Intuitive (Risk management) Controlled Changing network management, balancing performance, risk and costs System performance related to 5 dimensions

2 SQUEEZING MARGINS: REDUCING COSTS WHILE BALANCING RISKS G.A. Bloemhof, J. Knijp KEMA T&D Power, the Netherlands ABSTRACT Liberalising the energy market increased the awareness of transmission and distribution companies for optimising network activities and reducing costs. Network operators have to balance between performance, risks and costs. The traditional approach leads to sub-optimisation. When planning, adapting or operating existing power supply systems one can save by using the system and its components closer to their limits. Increased use of margins means: taking more risks. This paper handles topics like types of risks, tools and methods and the decision-making process. Using practical cases, the paper demonstrates how investments, reliability and technical constraints can be handled jointly in one integral decision process. The examples prove that by doing so savings can be realised. CHANGE IS THE NAME OF THE GAME By the end of the 2 th century - especially in the liberalising countries - an increase in optimising the activities of electricity transmission and distribution companies became apparent. Former practices could be characterised by maximising performance (reliability/safety), intuitive cost approach and avoiding risks. The new ambitions demand customer-oriented performance and thus cost effectiveness. That requires rational and integral cost methods and controlled risks. Figure 1 shows the shift in network management. In the liberalised market different parties are concerned. Shareholders demand certain levels of operating profits. Governmental regulators impose Rational (Lifecycle costing) Intuitive Figure 1 Maximum Customer oriented supply (Cost/benefit analyses) COST PERFORMANCE RISK Avoiding (Risk management) Controlled Changing network management, balancing performance, risk and costs limits on transmission and distribution tariffs. Customers demand high reliability and are assertive, and threat with claims when disturbances occur. Knijp and Van Doorn (4) explain his further. That is why the major concerns of the contemporary network operators are about asset management: reducing costs and postponing investments, while keeping up reliability and power quality standards. Therefore new methods and techniques like life cycle costing, risk management and performance management are introduced, as shown in figure 1. Cliteur and Wetzer (3) and Hafkamp and Schutters (5) elaborate on this. SAVING COSTS MEANS TAKING MORE RISK In the liberalising energy market, cost reduction is the most important topic. The cost reduction process starts with a bottleneck, when the margin has become zero. Then there are opportunities to increase use and postpone investments. Traditional solutions have to be re-evaluated critically. Making decisions, avoiding additional costs, induces substituting margins. Going away from one limit and increasing the margin to above zero involves reducing the margin for a non-critical constraint. Increased use of margins means taking more risks. Classification of cost saving measures Measures that can result in cost savings can be classified according to different aspects: planning or operations system oriented or component oriented time versus capacity limit Planning or operation. The distinction between measures in operations or measures taken in the planning stage, lies in the remaining time to the actual bottleneck. The closer the deadline, the less the degrees of freedom. If there is sufficient time, we can change the transmission capacity by changing the network topology using planning criteria. During operation the topology is fixed and transmission capacity can only be changed within the operational limits. Figure 2 illustrates the difference. An example of such difference is the use of dispersed generation, distinguishing location and operation. During planning location, point of network coupling, rating and even time of installation

3 criteria for planning network topology Figure 2 Planning stage transmission capacity Operation stage criteria for operation network topology transmission capacity Differences between utilisation in planning and in operation are free to choose. For an already installed unit only the generated power is free for an operator. System or component. Crossing system thresholds can be solved on component level as well as a system level. Each component has its own limits mostly determined by physical characteristics. Exceeding the limits of components can often be solved locally. For the system level however other criteria are valid. These criteria are influenced by all components together. A simple example is the maximum load of bundled cables in one bedding. Although criteria can clearly be distinguished in limits per component and limits for the system, this is not so easy for the measures to be taken. For example overloading of a cable can be solved in several ways: (1) by replacing with a heavier component, (2) by changing the environment of the cable, (3) by applying newer standards (uprating), (4) by placing redundant elements in the systems, (5) by rerouting the load or (6) by changing the demands on the system (e.g. dropping a N-1 criterion or revising a load forecast or risk level). Time versus limit. Figure 3 shows the margins in limit (e.g. capacity) and in time and the interchangeability. Usually components can be overloaded at the cost of a reduction of the remaining lifetime. This is a long term balance. A short term effect is for instance planning using dynamic load profiles leading to a higher maximum load, which is only temporarily allowed. Grotenhuis et al (7) present a detailed application. Time is also related to risk, how long does it take for the next bottleneck to appear, either at the (same) component level or for the system elsewhere? Which scenarios are most critical? How to make decisions? Classification of measures alone is not enough. Different measures have to be compared mutually, in particular regarding the expected effect. After all, a decision made in a consequent and unambiguous manner is needed. Therefore quantification is essential. Each measure effects different dimensions like cost, risk and length of life. Table 1 shows different disciplines involved in the decision making process. These disciplines are external, related to the stakeholders, to laws and to physics, outside the control of the planner or operator. All the internal limits, usually based on isolated worst case scenarios, can be influenced and are thus part of the decision process. This also implies integration of activities like planning, operation and maintenance, throughout all departments, such as generation, transmission, distribution and protection. A uniform system, comparing all the disciplines involved, is necessary to achieve optimal solutions and to reach a balance between all constraints. It is important to avoid sub-optimisation. A systematic and consistent approach is needed to use the system to its utter limits. TABLE 1 Disciplines involved when squeezing margins and reducing cost 1. Technical constraints, considering margins for the (partial) system (e.g. voltage drop), and individual components (e.g. loading) 2. Economic targets (maximum profit) and budgetary constraints for the company put limits to decisions. Investments and life-cycle costs have to be combined. 3. Reliability, both the availability of components and the reliability of supply to customers. Deterministic criteria, as the N-1, and probabilistic parameters are involved. 4. Supply quality, from customers viewpoint 5. Environmental issues PRACTICAL EXAMPLES limit increased use (of margin) The following two cases will illustrate the decision making process in bottleneck situations. Both examples are from actual studies for Dutch utilities. For each we give the case, the bottleneck, the solutions, the approach, the results and conclusions. planned usage and horizon extended life Case 1: cost versus performance Figure 3 Margins in time or capacity limit time The case and the bottleneck. This case involves a 6 kv MV distribution network serving a medium sized village in the Netherlands, with about 3.

4 customers. An annual load growth of 2% is foreseen. During the last 1 years the network operator installed components suitable for 1 kv, still operated on 6 kv. When a fault occurs in the MVfeeders the restoration process requires switching customers off, due to capacity constraints and voltage limits. Possible solutions and approach. The solutions analysed are several changes in the configuration on the 6 kv level. Changing the nominal voltage to 1 kv would enhance the capacity, but would also require additional investments. The current bottleneck situation was analysed by comparing 4 different scenarios as in table 2. The main question was the future system voltage to be used: continuing with 6 kv or changing to 1 kv. TABLE 2 Four future alternatives for case 1 Variant nr. Description 1 6 kv with modification in 2 6 kv modifications in 2 en 3 1 kv variant 1, parallel 4 1 kv variant 2, looped All alternatives were evaluated regarding: investments (equipment, labour, maintenance) network losses, valued and capitalised over the lifetime (planning horizon) of the system reliability (non delivered energy), only the mutual differences are calculated Voltage quality and environmental issues are not accounted for in this case. The technical constraints are: the loadflow, checking component capacities and voltage levels short circuit, checking fault conditions and restoration schemes the N-1 criterion for the MV feeders All solutions were dimensioned such that all constraints are fulfilled. Results and conclusion case 1. In figure 4 relates the main results, both the total costs and the (Non-Delivered Energy) are presented. There is no single optimal solution, since the cheapest and the most reliable solution are not the same. The 1 kv variants appear to be cheaper than all 6 kv variants. The choice between the cheapest and the best depends on the value of, a subject widely under discussion. A break-even analysis shows that the break-even value in this case is very high, about 4 EUR/kWh. Since realistic values in the discussion range between.4 and 4., the decision is obvious. Total Cost (x 1 Euro) kv variant 1 6 kv variant Non Delivered Energy (kwh) Figure 4 Results Case 1: Performance vs. Cost This is not a general conclusion. The decision depends on the configuration, and on parameters like interest rate, planning horizon, value of energy losses, etc. It does show however how different aspects can be combined, and even if not all the parameters are exactly known, one still can reach an unambiguous decision. Case 2: multiple constraints 1 kv variant 1 1 kv variant 2 Linear break-even The case and the bottleneck. This study was performed for a Dutch 5/1kV substation with a double busbar configuration as shown in figure 5. Both busbars are connected through a bus coupler, which is normally closed. The station feeds a distribution network made up of 11 km underground cable with about 4 customers. Ajodhia and Bloemhof (1) describe this case in more detail. Here only the main results are given. In the underlying network there is a large number of greenhouses with lots of dispersed generation. The abundance of dispersed generation has lead to a situation where very high short circuit currents could exist in the station. This could lead to a situation (S2 in table 3) where the limits of safe operation would be exceeded. Transformer I Figure 5 Closed breaker Open breaker Bus coupler Transformer II Closed disconnector Open disconnector Case II: initial configuration (Bus coupler Closed ) Bus I Bus II

5 TABLE 3 S S1 S2 S3 S4 A1 A2 Description of Situations and Actions Case history, no bottlenecks Reaching short circuit limit of busbar Exceeding short circuit limit of busbar Open the coupling breaker Situation after opening breaker Add telecontrol system Final situation after adding telecontrol Possible solutions and approach. The first solution proposed was based on the N-1 principle and consisted of adding an additional (stand by) transformer. This would lead to a reduction of the short circuit currents. Installing such an extra transformer however would require high investments while its utilisation would be very low. The network operator looked for more cost-effective solutions. In the second solution it was proposed to just open the coupling breaker (table 3: A1) between the two busbars so short circuit currents would be limited. Each bus bar is then fed through a single transformer. The loads have been distributed between the busbars. In this case there would not be a N-1 situation anymore, since a fault in the supply of one of the busbars or one of the transformers would lead to an outage. Maintaining the reliability level, expressed in expected Non-Delivered Energy (), was defined as an extra constraint. During the study a third option arose: adding telecontrol using the SCADA system (table 3: A2), enabling a major reduction in restoration times. For the second proposed solution it was not clear what the effect on reliability would be when the N-1 criterion was abandoned. Therefore a reliability study was performed using a probabilistic computer programme. Results case 2. A graphical overview of the results is given in figure 6. On the X-axis the number of outages for the average customer is presented in outages/year. The Y-axis gives the average outage duration. The hyperbolic curves are iso-lines where the product of outage duration and outage frequency is a constant, apart from some constants they are iso- curves. In situation S1 there are no constraints. Increasing dispersed generation leads to too high short circuit currents in the station. These damage the station, requiring a considerable restoration time (S2). Opening the breaker (A1, S3) cancels this adverse effect. As figure 6 shows the situation S3 is still not as good as in situation S1. Comparing the values of shows an increase of 31%. A second action (A2, adding telecontrol) brings the average Outage Duration 2, 15, 1, 5,, constant =1% 131% 2% 88% S1 S2 S3 S Failure rate Figure 6 Reliability results for case 2 outage duration for S4 to 8% of the level in S1. Telecontrol appears to be a very cost-effective measure. Compared with the initial situation the Non-Delivered Energy has been lowered, the average duration is shorter, while the frequency of interruption rose with only 9%. Overall, the quality of supply (the reliability), has been improved. Note however that the N-1 criterion is still not fully met. Conclusion case 2: Case 2 handles the intended expansion of a substation, N-1 safe, for which modifications had to be made. Traditional and alternative options were compared. Reliability results showed that both the number of interruptions and the annual customer minutes lost increased. From the value of the extra Non Delivered Energy it was concluded that high investments were not justified from reliability point of view. Alternative measures were needed. This led to high savings in investments with only a minor decrease in reliability. GENERALISATION OF THE METH Figure 7 shows the main results of case 2 in an alternative way. Several constraints are given along relative axes in one diagram, as explained in the legend. The shaded area in the centre is not feasible or not allowed. Figure 7 shows situation S2 on top. For two criteria ( and ) the performance is not acceptable. The diagram in the middle shows S3, where the constraints are partially relieved. The bottom diagram shows the system in situation S4. The system performs within all limits, there is a margin for each constraint. This example shows how different margins could be used to keep the overall performance of the system within its target limits.

6 SC 5 CONCLUSION -5-1 It is shown that margins and risks are inherent multidisciplinary problems. Decreasing costs, trying to maintain quality, or improving quality with minimal expenses, demands a balance between all aspects. Making decisions, when different scenarios are posible, brings risks. Risk is both in uncertainties about the future and in incomplete data. Comparing disciplines means also using weighing factors, using break-even analysis or sensitivity analyses. SC 5-5 A uniform system comparing all the disciplines involved to achieve optimal solutions and to reach a balance between all the constraints is presented. Relieving a limit through working closer to another is a delicate matter. The tools needed are available, however a systematic and consistent approach is required to use the system to its edges. An integrated analysis allows avoiding or postponing costs. Practical examples prove that significant savings can thus be achieved. -1 ACKNOWLEDGEMENT The authors thank EnergieNed, who funded part of this work on behalf of the Dutch utilities. REFERENCES: 5 SC 1. Ajodhia V., Bloemhof G.A., Probabilistic criteria: Saving costs while maintaining high reliability, CEPSI Bloemhof G.A., Dijk H.E., Technico-Economic evaluation of protection systems taking reliability aspects into account, CIRED 1995, paper Cliteur G.J., Wetzer J.M, Condition assessment of power transmission and distribution components, CIRED 21, session Knijp J., Van Doorn J.C., Opportunity Or Responsibility? Developments in Marketing Power Quality, Distributech 2. Figure 7: Radar plot of system performance, top down: situations S2, S3, S4 Legend: SC Short circuit limit of busbar Non Delivered Energy Outage Duration Maximum System Voltage Maximum load current of critical cable 5. Hafkamp P.J.M., Schutters G., Designing and implementing a maintenance management system with an expert support system: Methodology, implementation, expert IT-system, achieved cost reductions after implementation, CIRED 21, session Bloemhof G.A., Wolters B.O, Protection of HVsystems: is simple and cheap good enough?, DPSP Grotenhuis B.J., Jaspers, J.E., Kerstens A., Van der Wey A.H., De Wild F.H., Increasing the Capacity of Cable Systems Using Cable Asset Management Based on Thermal and Mechanical Properties, CIRED 21, session 3.

DECISION SUPPORT FOR LIFE TIME MANAGEMENT OF HV INFRASTRUCTURES

DECISION SUPPORT FOR LIFE TIME MANAGEMENT OF HV INFRASTRUCTURES E.Gulski (1), J.J.Smit (1), B. Quak (1), E.R.S.Groot (2) (1) Delft University of Technology, (2) KSANDR The Netherlands e.gulski@ewi.tudelft.nl