Filters
Availability
Publication Year
Resource Type
Faculty
School/Institute
Publication Search Results
Sort
Results per page
1 - 10 of 103
-
-
-
-
-
-
-
(1994)ThesisSystems with storage allow the production and use of a commodity to be separated in time to reduce costs or to make better use of available capacity. Hydro-reservoirs play a central role in many electricity systems. On the demand side there is a much greater variety of storage plant; buffer storages in manufacturing, ice storage systems and compressed air systems. Battery storage can also be used in remote area power supply systems (RAPS). Determining an effective and efficient operating strategy for storages can be difficult. The literature reveals a wide variety of approaches to the hydro-dispatch problem. More recently more emphasis has been placed on the operation of distributed demand-side storages, be they centrally controlled or individually influenced through time-of-use or spot pricing tariffs. The difficulty of modelling and optimising the operation of storage systems arises from the separation over time of production and use of the stored commodity. Determining the optimal operating strategy is a time-staged problem, presenting practical difficulties with problem size. The operating strategy also depends on expectations of future plant operation and external conditions which cannot always be known with certainty. This thesis presents an exact and efficient solution method for a general class of deterministic, single storage systems. While many real systems are more complex than this, the approach developed combines elements of both dynamic programming and general mathematical programming methodology and so offers good prospects for extension to more complex multiple storage or stochastic systems. An important insight used throughout this thesis is that, for a large class of storage problems, the "production" and "storage" elements of the system can be separated. This leads to the further insight that the behaviour of a wide variety of production systems can be encapsulated in a single "production cost function" which describes the way all the system costs per unit time vary with the rate of flow into (or out of) the store. For the purpose of this thesis, this function is taken to be piece-wise linear and convex, although such restrictions can largely be removed if the algorithm is modified. Once the production element of the system can be described in this standardised way, it is possible to write both linear programming and dynamic programming representations of the time-staged optimisation problem to be solved. By analysing the mathematical properties of this formulation and the conditions for its solution, a simple, exact and highly efficient solution algorithm is developed. One advantage of the algorithm is that it has a simple and intuitive graphical representation. The algorithm combines the best features of the linear and dynamic programming approaches while eliminating their worst features for the class of problem addressed. As a dynamic programming approach, the solution is obtained by solving a sequence of small, single period optimisations, which is much more efficient than solving a time-stage linear program. As a linear programming approach, the solution is exact and obtained without discretising the storage variable. The dual properties of the linear programming solution also provide useful supplementary information such as the shadow value of the storage contents over time. As a practical matter, commercial codes for the storage algorithm can be developed by extending existing mathematical programming codes. Two examples are presented. The first works through a simple model analytically to illustrate the workings of the algorithm. The second is a larger and more complex model of a pumped storage hydro-electric system. While the thesis concentrates on single storage, deterministic systems, possible extensions to deal with multiple storage and stochastic systems are also reviewed.
-
(1995)ThesisNew methods are required to make optimal operation decisions for electricity generating and consuming plants in market-based electricity industries. Since wholesale electricity is traded on a spot price basis, both generators and consumers face uncertainty in their future income. Operating plants with inter-temporal links are particularly difficult since operation decisions at one instant affect the available operation decisions after that, and hence affect future income. Operation decision making with a risk-averse attitude is a method to handle uncertainty, however, some form of financial instruments, such as forward contracts, are required to allocate risk. Since electricity markets operate on a discrete time basis, a multi-stage decision making method is required to operate an electricity plant with inter-temporal links. Although risk-averse decision making has been used in other contexts, few attempts have been made to use these techniques for multi-stage problems. In this thesis, a new multi-stage risk-averse decision making algorithm is proposed and applied to make operation and forward contract trading decisions for a plant in an electricity market. In the proposed algorithm, risk aversion is incorporated in sequential decision making using the expected utility method with a von Neumann-Morgenstern utility function. Decisions are taken to maximise the utility of total financial income. Since utility functions have a concave shape, the marginal utility of income diminishes with increased income, giving risk aversion. A solution structure similar to dynamic programming is proposed for the risk management algorithm by introducing a state variable to represent past behaviour. The proposed algorithm is applied to make decisions for electricity plant and market models. Simulation results for different plant models show a clear reduction in financial risk when compared with risk-neutral operation. Any reduction in risk is shown to be sensitive to the decision maker s attitude toward risk used in the algorithm. Simulation results suggest that forward contracts play a major role in minimising risk when starting plants with high start up costs. Forward contracts ensure financial security even under unfavourable market conditions. It is shown that, plants employing a risk-averse attitude which do not commit to start, do so after securing their future financial position using forward contracts. In general, the proposed risk management algorithm shows potential for use in electricity markets.
-
-