A combined heat and power (CHP) unit can use its waste heat to supply building thermal loads so that the electrical heating or cooling load is reduced and the overall efficiency is improved. When multiple CHP units ar...
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ISBN:
(纸本)9781538622124
A combined heat and power (CHP) unit can use its waste heat to supply building thermal loads so that the electrical heating or cooling load is reduced and the overall efficiency is improved. When multiple CHP units are running in a microgrid, it is therefore critical to balance the output of each unit so that both the electricity consumption and the building thermal loads can be satisfied with least cost. This paper presents an optimal microgrid dispatchalgorithm for scheduling multiple gas-fired combined heat and power units when the microgrid is disconnected from the main grid. A coordination controller is developed to determine the power output reference for each CHP unit such that the total electric power output of all CHP units are minimized while both electric and thermal demands are met. A few test cases are presented to illustrate the effectiveness of the algorithm.
In recent years, the use of interconnected multi-area systems has increased significantly. To operate these systems efficiently, a proper coordination approach among different areas is required. With this context, a n...
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In recent years, the use of interconnected multi-area systems has increased significantly. To operate these systems efficiently, a proper coordination approach among different areas is required. With this context, a novel decentralised optimal dispatch algorithm is proposed in this study. The centralised economic dispatch model is decoupled into a series of sub-problems for different areas, allowing the independent decision of each area without a central operator. The detailed information of each area is not required for information exchange. To better estimate the impact of each area's decision on other areas, the approximate value functions of the tie-line powers are added into the local objective function of the sub-problem. This technique makes the decentralised solution of the proposed algorithm more explicit and rational compared with most existing distributed algorithms. Besides, the proposed technique does not require parameter tuning and has good convergence performance. Numerical simulations on several test systems and a real power system demonstrate that the proposed algorithm is favourable in terms of accuracy, adaptability, and computational efficiency.
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