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dc.contributor.authorDoorman, Gerardnb_NO
dc.date.accessioned2014-12-19T13:29:43Z
dc.date.available2014-12-19T13:29:43Z
dc.date.created2000-12-20nb_NO
dc.date.issued2000nb_NO
dc.identifier125349nb_NO
dc.identifier.isbn82-7984-128-8nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/249796
dc.description.abstractThe theme of this thesis is the supply of capacity during peak demand in restructured power systems. There are a number of reasons why there is uncertainty about whether an enegyonly electricity market (where generators are only paid for the energy produced) is able to ensure uninterrupted supply during peak load conditions. Much of the public debate in Europe has been about the present surplus generation capacity. However, in a truly competitive environment, it is hard to believe that seldom used capacity will be kept operational. This is illustrated by developments in Sweden. For this reason, the large surplus of generation capacity in the European Union may vanish much faster than generally assumed. In the USA, much of the debate has been about California. During the last three summers, California has occasionally experienced involuntary load shedding and prices have been very high during these periods. To some extent, the Californian situation illustrates the relevance of the subject of this thesis: in a deregulated system generators may not be willing to invest in peaking capacity that is only needed occasionally, even though prices are very high during these periods. A good solution to the problem of providing peaking power is pivotal to the success of power market restructuring. Solutions that fail to create the right incentives will result in unacceptable load shedding and can endanger the whole restructuring process. On the other hand, solutions that pay too much for investments in peaking power will lead to generation capacity surpluses and thus represent a societal loss. Why is peaking capacity a problematic issue in energy-only markets? Traditionally, probabilistic methods are applied to calculate the required generation capacity to obtain a desired level of reliability. In a centrally planned system, this level of generation capacity is developed in a least-cost manner. A single utility or central authorities can thus control the level of reliability directly. This is not possible in a market-based system, if suppliers are only paid for the energy produced. Under the assumption of certainty and continually varying prices, generators fully recover their variable and investment costs under ideal market conditions. When uncertainty is taken into account, generators will cover their expected costs. However, revenues will be extremely volatile, especially for peaking generators. Combined with a risk-averse attitude, it is unlikely that investments will be sufficient to maintain the traditional level of reliability in an energyonly market. Consequently, one would expect reserve margins to decline in such markets. This effect is very clear in Sweden that deregulated in 1996, and less explicit in a number of other cases like Norway, California and Alberta. Pricing and Consumer Preferences The theory of electricity pricing was originally developed for vertically integrated utilities, but elements from this theory are also valuable in a restructured context. Many authors have agreed on the presence of a capacity element in the optimal price during peak-load conditions, while price should equal marginal cost during low-load conditions. An important assumption is that prices have to be stable. More recently, spot pricing of electricity has been advocated. A number of papers have been written about how to efficiently include security considerations in the spot price. Because the availability of capacity cannot be directly controlled in an energy-only spot market, the probability of occasional capacity shortages increases. It is important to be prepared for this situation. The core of the problem is that demand is de facto inelastic in the short-term because of traditional tariff systems. It is shown that considerable economic gains are obtained when demand elasticity can be utilized, even if only minor shares of demand are elastic in the short-term. Better utilization of demand elasticity was also profitable in traditional systems, but after restructuring the gain is much larger: the alternative is not expensive generation but random rationing, which is unacceptable in modern society. It is possible to go one step further. Consumers have different preferences for the use of energy and reliability. Some consumers have a low tolerance about being disconnected, while others are more willing to accept this. This will be reflected by their willingness to pay for reliability. A better solution would emerge if consumers could buy electricity and reliability more or less as separate commodities, based on their preferences. In the context of pricing it should be pointed out that ”profile-based settlement” that allows small consumers to freely choose their supplier without hourly metering is detrimental with respect to the correct pricing of capacity. It should only be used in the initial phases of opening a market. Improved utilization of system resources Even in the short-term, demand and the availability of generation and transmission resources are uncertain. Therefore, it is necessary to have reserves available in a power system. When capacity becomes scarce, it is difficult to satisfy the reserve requirements. If these requirements are strict, the only possibility is to resort to what can be called ”preventive loadshedding” to satisfy the reserve requirements. This is obviously an expensive solution, but there are no obvious ways of balancing the (societal) cost of preventive load shedding against reduced system security. In this thesis, a model is developed for unit commitment and dispatch with a one-hour time horizon, with the objective of minimizing the sum of the operation and disruption costs, including the expected cost of system collapse. The model is run for the IEEE Reliability Test System. It is shown that under conditions where there is not enough capacity available to satisfy the reserve requirements, large cost savings can be obtained by optimizing the sum of the operation and disruption costs instead of using preventive load-shedding. In the model, it is also possible to directly target reliability indexes like the Loss of Load Probability or Expected Energy not Served. It is shown that increased reliability (in terms of the values of the indexes) can be obtained at a lower cost by targeting the indexes directly instead of resorting to reserve requirements. This is especially the case if flexible load-shedding routines are developed, making it possible to disconnect and reconnect the optimal amounts of load efficiently. The use of alternatives to fixed reserve requirements as a means to maintain system security does not solve the problem about how to ensure the availability of peaking capacity. However, in a situation with occasional capacity shortages, it gives the System Operator a tool to find the optimal balance between preventive load shedding and system security, which can result in significantly lower disruption costs in such cases. More research and development in this area is necessary to develop methods and tools that are suitable for large power systems. Ancillary Services Investment in peaking capacity is insufficient in restructured systems because expected revenues are too low or too uncertain. If generator revenues are increased, the situation improves. One way to obtain this is to create markets for ancillary services. In the thesis, a model is developed for a central-dispatch type of pool. In this model, markets for energy and three types of ancillary services are cleared simultaneously for 24 hours ahead. Market prices are such that volumes and prices are consistent with the market participants. self-dispatch decisions . i.e. given these prices, market participants would have chosen the same production of energy and ancillary services as the outcome of the optimization program. With this model, it is shown that markets for ancillary services increase generator revenues, but this effect is partly offset by lower energy prices. This shows that markets for ancillary services can contribute to improving the situation, but given the remaining uncertainty, this is hardly enough to solve the problem. Capacity Subscription Because consumers have preferences for two goods: electricity and reliability, they should ideally have the choice of purchasing the preferred amount of each of these. Traditionally this is not possible . reliability is a public good, produced or obtained by a central authority on behalf of all consumers. Technological progress is presently changing this. Capacity subscription is a method that allows consumers to choose their individual level of reliability, at the same time creating a true market for capacity. It is based on the concept of selfrationing. Consumers anticipate (for example on a seasonal basis) their need for capacity at the instant of system-wide peak demand. Based on this anticipation, they procure their desired level of capacity in a market, where generators offer their available capacity. Demand is limited to subscribed capacity by a fuse-like device that is activated when total demand exceeds total available generation. In this way, the capacity payment only influences the market when demand is close to installed capacity, and does not distort the energy price in other periods. Demand is not limited when there is ample capacity. Demand will never exceed supply, because it can be limited in an acceptable way when this situation occurs. Moreover, both consumers and suppliers can adapt to situations with scarce or ample capacity, and the price of capacity will reflect this situation. There is one problem with the method: as consumers do not reach their subscribed capacity simultaneously, there will be a capacity surplus at the instant the fuse-devices are activated. Two methods to solve this problem are analysed, and it is shown that the problem can be solved optimally by giving consumers who prefer this the opportunity to buy power in excess of their subscription on the spot market. Policy evaluation Six alternative policies to assess the peaking power problem are analysed based on the following criteria: - Static efficiency: the welfare-optimal match of consumption and supply - Dynamic efficiency: the ability to create incentives for innovation - Invisibility: with invisible strategies, each market actor pursues his or her own objectives without worrying about anyone else.s - Robustness: a robust policy is less sensitive to deviations from assumptions - Timeliness: the ability of a policy to be employed at the right time - Stakeholder equity: the degree to which all the involved parties are treated equitable - Corrigibility: the extent to which a policy can be corrected once it is employed - Acceptability: the degree to which the policy is acceptable to all parties - Simplicity: ceteris paribus simple strategies are preferable over more complicated strategies - Cost: the cost of implementing the policy - System security: the policy.s ability to obtain an acceptable level of system security The policies are, in short (an example is given in parentheses): - Capacity obligation: suppliers are obliged to keep sufficient capacity (PJM) - Fixed capacity payment: a fixed payment is offered for available capacity (Spain) - Dynamic capacity payment: capacity payment is based on the Loss of Load Probability (England and Wales) - Energy-only: no explicit payments or obligation (Scandinavia, California) - Proxy prices: very high administrative prices are used as a proxy to the Value of Lost Load when load shedding is necessary (Australia) - Capacity subscription: cf. the description above (not implemented) As could be expected, no single policy performs best on all criteria. The obligation and fixed payment methods do not perform well on market efficiency criteria, as essentially they are not market-based policies. The proxy prices policy is a reasonable policy on most criteria. It is easy, cheap and quick to implement. Because there is little experience with the method so far, there is some uncertainty with respect to if it is effective. One can anticipate that the threat of having to buy power at rationing prices will motivate market participants to avoid coming in a buying position in such cases, and that this will stimulate the adaptation of innovative solutions, especially on the demand side. The capacity subscription policy looks very promising on the issues of efficiency, robustness and system security. This is especially true for dynamic efficiency: consumers will weigh the cost of capacity against the cost of innovative load control devices, and if the price of capacity is high, a market for such technology will emerge. However, there is a considerable threshold prior to the introduction of capacity subscription, caused by the implementation costs and complexity. The conclusion on policies is thus that in an early stage after restructuring it may be appropriate to resort to the capacity obligation or payment method if the capacity balance is tight at the time of transition. For the medium-term, or if there is ample capacity initially, it is sensible to introduce proxy market prices to transfer the risk of a capacity deficit to market participants, with due attention being paid to the appropriate price level. Capacity subscription can be a long-term objective.nb_NO
dc.languageengnb_NO
dc.publisherFakultet for informasjonsteknologi, matematikk og elektroteknikknb_NO
dc.relation.ispartofseriesDr. ingeniøravhandling, 0809-103X; 2000:100nb_NO
dc.subjectElectrical power technologyen_GB
dc.subjectTelekommunikationen_GB
dc.subjectTECHNOLOGY: Electrical engineering, electronics and photonics: Electric power engineeringen_GB
dc.subjectInformation technology: Telecommunicationen_GB
dc.titlePeaking Capacity in Restructured Power Systemsnb_NO
dc.typeDoctoral thesisnb_NO
dc.source.pagenumber172nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikknb_NO
dc.description.degreedr.ing.nb_NO
dc.description.degreedr.ing.en_GB


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