Simulating Multi-Reservoir Operation Rules by Network Flow Model

Author(s):  
Frederick N.-F. Chou ◽  
Chia-Wen Wu ◽  
Cheng-Hao Lin
Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2564 ◽  
Author(s):  
Anderson Passos de Aragão ◽  
Patrícia Teixeira Leite Asano ◽  
Ricardo de Andrade Lira Rabêlo

The Hydrothermal Coordination problem consists of determining an operation policy for hydroelectric and thermoelectric plants within a given planning horizon. In systems with a predominance of hydraulic generation, the operation policy to be adopted should specify the operation of hydroelectric plants, so that hydroelectric resources are used economically and reliably. This work proposes the implementation of reservoir operation rules, using inter-basin water transfer through an optimization model based on Network Flow and Particle Swarm Optimization (PSO). The proposed algorithm aims to obtain an optimized operation policy of power generation reservoirs and consequently to maximize the hydroelectric benefits of the hydrothermal generation system, to reduce the use of thermoelectric plants, the importation and/or energy deficit and to reduce the cost associated with meeting the demand and reduce CO2 emissions from combustion of fossil fuels used by thermoelectric plants. In order to illustrate the efficiency and effectiveness of the proposed approach, it was evaluated by optimizing two case studies using a system with four hydroelectric plants. The first case study does not consider transfer and water and the second case study uses water transfer between rivers. The obtained results illustrate that the proposed model allowed to maximize the hydroelectric resources of a hydrothermal generation system with economy and reliability.


Author(s):  
Heejin Cho ◽  
Sandra D. Eksioglu ◽  
Rogelio Luck ◽  
Louay M. Chamra

The Combined Cooling, Heating, and Power (CCHP) systems have been widely recognized as a key alternative for thermal and electric energy generation because of the outstanding energy efficiency, reduced environmental emissions, and relative independence from centralized power grids. Nevertheless, the total energy cost of CCHP systems can be highly dependent on the operation of individual components and load balancing. The latter refers to the process of fulfilling the thermal and electrical demand by partitioning or “balancing” the energy requirement between the available sources of energy supply. The energy cost can be optimized through an energy dispatch algorithm which provides operational/control signals for the optimal operation of the equipment. The algorithm provides optimal solutions on decisions regarding generating power locally or buying power from the grid. This paper presents an initial study on developing an optimal energy dispatch algorithm that minimizes the cost of energy (i.e., cost of electricity from the grid and cost of natural gas into the engine and boiler) based on energy efficiency constrains for each component. A deterministic network flow model of a typical CCHP system is developed as part of the algorithm. The advantage of using a network flow model is that the power flows and efficiency constraints throughout the CCHP components can be readily visualized to facilitate the interpretation of the results. A linear programming formulation of the network flow model is presented. In the algorithm, the inputs include the cost of the electricity and fuel and the constraints include the cooling, heating, and electric load demands and the efficiencies of the CCHP components. This algorithm has been used in simulations of several case studies on the operation of an existing micro-CHP system. Several scenarios with different operational conditions are presented in the paper to demonstrate the economical advantages resulting from optimal operation.


Author(s):  
Jacek Błażewicz ◽  
Grzegorz Pawlak ◽  
Marie-Laure Espinouse ◽  
Gerd Finke

1976 ◽  
Vol 22 (11) ◽  
pp. 1221-1228 ◽  
Author(s):  
Gordon Bagby ◽  
Arne Thesen

Energies ◽  
2018 ◽  
Vol 11 (3) ◽  
pp. 613 ◽  
Author(s):  
Juliano Camargo ◽  
Fred Spiessens ◽  
Chris Hermans

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