Compromise Scheduling of Bilateral Contracts in Electricity Market Environment

Author(s):  
Sergey I. Palamarchuk
Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2239
Author(s):  
Bin Luo ◽  
Shumin Miao ◽  
Chuntian Cheng ◽  
Yi Lei ◽  
Gang Chen ◽  
...  

The large-scale cascade hydropower plants in southwestern China now challenge a multi-market environment in the new round of electricity market reform. They not only have to supply the load for the local provincial market, but also need to deliver electricity to the central and eastern load centers in external markets, which makes the generation scheduling much more complicated, with a correlated uncertain market environment. Considering the uncertainty of prices and correlation between multiple markets, this paper has proposed a novel optimization model of long-term generation scheduling for cascade hydropower plants in multiple markets to seek for the maximization of overall benefits. The Copula function is introduced to describe the correlation of stochastic prices between multiple markets. The price scenarios that obey the Copula fitting function are then generated and further reduced by using a scenario reduction strategy that combines hierarchical clustering and inconsistent values. The proposed model is applied to perform the long-term generation scheduling for the Wu River cascade hydropower plants and achieves an increase of 106.93 million yuan of annual income compared with the conventional scheduling model, without considering price scenarios, showing better performance in effectiveness and robustness in multiple markets.


2020 ◽  
Vol XXIII (1) ◽  
pp. 180-185
Author(s):  
Adela Bâra

Owning several types of generating units requires an optimized schedule to cover the negotiated bilateral contracts. This approach will lead to a better electricity market strategy and benefits for an electricity producer. In this paper, we will simulate the operation of five different generators including generators based on Renewable Energy Sources (such as wind turbines and photovoltaic panels) that belong to an electricity producer. The five generators are modelled considering the specificity of their type and primary energy source. For instance, for renewable energy sources, we will consider the 24-hour generation forecast. The objective function of the optimization process is to obtain an optimal loading of generators, while the constraints are related to the capacity and performance of the generators. The output consisting in a generating unit optimized operation schedule will be further used for day-ahead or balancing market bidding process. Hence, the producer will be able to adequately bid on the future electricity markets knowing the commitment of generators for negotiated bilateral contracts market. The simulations are tested for more than five generators considering the connection to a relational database where more data for generators is stored.


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