A Decision Methodology for Coal Inventory Optimization

Twisdale, Lawrence A.; Chu, Jie

doi:10.1109/tpas.1979.319374

Cited by 8 publications

(6 citation statements)

References 2 publications

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“…These works on GSS only focused on optimizing the generation schedules without considering fuel supply decisions. On the other hand, studies on CS in power plants can be found in [10]- [13]. In [10], a general decision analysis formulation of coal inventory for power plants was presented to assess optimal purchase and storage decisions.…”

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confidence: 99%

Co-Optimization of Generation Self-Scheduling and Coal Supply for Coal-Fired Power Plants

et al. 2020

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Generation self-scheduling and coal supply in coal-fired power plants are closely related but typically optimized separately. To enhance the optimal operation of power plants, we propose a coordinated optimal operation strategy of generation and coal management in this paper. Uncertainties in electricity prices and demands, coal prices, and coal inventory holding costs are captured and modeled by discrete scenarios. Emission constraints are introduced to control generation emissions. The heat loss caused by the weathering of coal during the storage is taken into account, which distinguishes the considered co-optimization problem from the previous ones. The proposed strategy is built on a mixed-integer linear programming-typed two-stage stochastic programming model, in which whether to purchase coal is determined in the first stage and the quantity of coal purchase, the coal inventory, and the economic generation dispatch are determined in the second stage. The objective is to maximize the expected profits. An improved Benders decomposition algorithm is developed to solve the problem where multiple Benders cuts are added in each iteration and valid inequalities are introduced to speed up the convergence of the algorithm. Numerical experiments demonstrate the effectiveness of the proposed strategy and algorithm.

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confidence: 99%

Co-Optimization of Generation Self-Scheduling and Coal Supply for Coal-Fired Power Plants

et al. 2020

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“…Jha (2015) finds that firms which face wholesale market electricity prices save roughly 3% per month in coal purchase and storage costs compared to firms subject to output price regulation. Twisdale and Chu (1979) find that coal purchases tend to follow a seasonal, sawtooth pattern from month to month. Sensitivity analysis shows that potential replacement costs (the cost to replace power when the plant is short on coal) and/or revenue losses greatly affect the optimal strategy.…”

Section: Literature Reviewmentioning

confidence: 91%

“…Data for natural gas inventories are not included because of the inherent dangers of natural gas storage and the ease in transportation, which cause natural gas to usually be stored within the gas sector and not the electric power sector. Previous literature and economic theory suggest that input inventory decisions in the electricity sector are affected by input and output prices and opportunity costs (Jha 2015;Takriti et al 2001;Twisdale and Chu 1979). Following this intuition, coal inventories are expected to be related to fuel input prices, electricity (output) prices, and the opportunity cost of holding inventories.…”

Section: Introductionmentioning

confidence: 99%

Fuel inventory and price relationships in the U.S. electric power sector under regulatory and market change

Binder

Mjelde

2017

J Regul Econ

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Long-run relationships among coal inventories at U.S. electric power plants, corporate bond rates and coal, natural gas, and electricity prices are estimated over the period July 1976 to October 2014. Tests for constancy of the long-run relationships show periods of instability which coincide with major regulatory events in the electric power sector. Deregulation of the natural gas and electricity markets are likely sources of instability for the period mid-1994 to mid-2001. Additionally, inventory behavior may have had a smoothing effect over instability caused by natural gas prices during the recent U.S. shale boom. Policy makers should be aware that altering the regulatory environment can result in considerable fluctuations in how firms' inventory decisions interact with input and output markets and opportunity costs in the long run.

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“…Monte Carlo simulation has been used to calculate the probability distribution of total cost resulting from various sources of uncertainly [3]. A dynamic programming optimization procedure of the decision problem has been developed to assess the tradeoffs between excessive stockpiling and fuel shortage as well as to optimize coal-purchasing in an uncertain market [6]. Sensitivity Analysis also has been applied to analyze how different future events affect the performance of a plan.…”

Section: Introductionmentioning

confidence: 99%

GenCos decision-making constrained by operational and financial requirements

Gutiérrez-Alcaraz

2010

2010 IEEE International Conference on Industrial Engineering and Engineering Management

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In the new power business, the goal of electric generation companies is to commit their services at profit. The committed services will determine the future cash flows and consequently financial performance. However, purely generation assets' cash flows are path-dependent, since the path dependency relies on operational generating units' constraints. This paper focuses on the GenCos' future cash revenue flows required to fulfill total costs and financial requirements. For simplicity's sake, the future cash flows are dependent on a single commodity, electric energy.

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A Decision Methodology for Coal Inventory Optimization

Cited by 8 publications

References 2 publications

Co-Optimization of Generation Self-Scheduling and Coal Supply for Coal-Fired Power Plants

Co-Optimization of Generation Self-Scheduling and Coal Supply for Coal-Fired Power Plants

Fuel inventory and price relationships in the U.S. electric power sector under regulatory and market change

GenCos decision-making constrained by operational and financial requirements

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