scholarly journals Day Ahead Bidding of a Load Aggregator Considering Residential Consumers Demand Response Uncertainty Modeling

2020 ◽  
Vol 10 (20) ◽  
pp. 7310
Author(s):  
Zhaofang Song ◽  
Jing Shi ◽  
Shujian Li ◽  
Zexu Chen ◽  
Wangwang Yang ◽  
...  
Keyword(s):  
Demand Response ◽  
Electricity Consumption ◽  
Uncertainty Modeling ◽  
Physical Models ◽  
Bidding Strategy ◽  
Willingness To Participate ◽  
Demand Side ◽  
Bidding Strategies ◽  
Optimal Bidding ◽  
Residential Consumers

As the electricity consumption and controllability of residential consumers are gradually increasing, demand response (DR) potentials of residential consumers are increasing among the demand side resources. Since the electricity consumption level of individual households is low, residents’ flexible load resources can participate in demand side bidding through the integration of load aggregator (LA). However, there is uncertainty in residential consumers’ participation in DR. The LA has to face the risk that residents may refuse to participate in DR. In addition, demand side competition mechanism requires the LA to formulate reasonable bidding strategies to obtain the maximum profit. Accordingly, this paper focuses on how the LA formulate the optimal bidding strategy considering the uncertainty of residents’ participation in DR. Firstly, the physical models of flexible loads are established to evaluate the ideal DR potential. On this basis, to quantify the uncertainty of the residential consumers, this paper uses a fuzzy system to construct a model to evaluate the residents’ willingness to participate in DR. Then, based on the queuing method, a bidding decision-making model considering the uncertainty is constructed to maximize the LA’s income. Finally, based on a case simulation of a residential community, the results show that compared with the conventional bidding strategy, the optimal bidding model considering the residents’ willingness can reduce the response cost of the LA and increase the LA’s income.

scholarly journals Combined Bidding Strategy of Multi-owner Cascaded Hydropower Stations in Day-Ahead Market

2018 ◽  
Vol 246 ◽  
pp. 02036 ◽  
Author(s):  
Ying Yang ◽  
Weibin Huang ◽  
Guangwen Ma ◽  
Shijun Chen ◽  
Gang Liu ◽  
...  
Keyword(s):  
Electricity Market ◽  
Power Market ◽  
Bidding Strategy ◽  
Competitive Advantages ◽  
Bidding Strategies ◽  
Cascade Hydropower Stations ◽  
The Game Theory ◽  
Optimal Bidding ◽  
Hydropower Stations ◽  
Operation Characteristics

Under the background of the electricity market reform, if the multi-owner cascade hydropower stations bid separately, the overall competitive advantages of river basin cannot be exerted, and the overall benefits cannot achieve the maximization. Based on the operation characteristics of cascade hydropower stations and the rule of competitive bidding, this paper established a bi-level optimal model for bidding game in day-ahead market, and used the Nash equilibrium principle of the game theory and genetic algorithm to solve this model, the optimal bidding strategies of the multi-owner cascade hydropower stations have been solved under the circumstances of bidding by oneself and alliance. The results from the calculating examples showed that the unified price declaration of the multi-owner cascade hydropower stations in day-ahead market can improve the overall and individual generation efficiency, and proved the effectiveness and feasibility of the combined bidding strategy in power market.

scholarly journals On the Use of Causality Inference in Designing Tariffs to Implement More Effective Behavioral Demand Response Programs

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2666 ◽  
Author(s):  
Kamalanathan Ganesan ◽  
João Tomé Saraiva ◽  
Ricardo J. Bessa
Keyword(s):  
Demand Response ◽  
Response Rate ◽  
Current Trend ◽  
Electricity Consumption ◽  
Residential Electricity ◽  
Causality Inference ◽  
Residential Electricity Consumption ◽  
Demand Response Programs ◽  
Residential Consumers

Providing a price tariff that matches the randomized behavior of residential consumers is one of the major barriers to demand response (DR) implementation. The current trend of DR products provided by aggregators or retailers are not consumer-specific, which poses additional barriers for the engagement of consumers in these programs. In order to address this issue, this paper describes a methodology based on causality inference between DR tariffs and observed residential electricity consumption to estimate consumers’ consumption elasticity. It determines the flexibility of each client under the considered DR program and identifies whether the tariffs offered by the DR program affect the consumers’ usual consumption or not. The aim of this approach is to aid aggregators and retailers to better tune DR offers to consumer needs and so to enlarge the response rate to their DR programs. We identify a set of critical clients who actively participate in DR events along with the most responsive and least responsive clients for the considered DR program. We find that the percentage of DR consumers who actively participate seem to be much less than expected by retailers, indicating that not all consumers’ elasticity is effectively utilized.

scholarly journals Simulation on Bidding Strategy at Day-Ahead Market

2014 ◽  
Vol 2014 ◽  
pp. 1-13
Author(s):  
Kazunori Sawai ◽  
Tetsuo Sasaki
Keyword(s):  
Demand Response ◽  
Low Cost ◽  
Price Sensitivity ◽  
Bidding Strategy ◽  
Small Companies ◽  
Market Prices ◽  
Power Generators ◽  
Bidding Strategies ◽  
Strategic Bidding ◽  
Market Simulation

In an electric power day-ahead market, market prices are not always cleared at marginal cost caused by the strategic bidding of generators. This paper presents the results of day-ahead market simulation by using a simple three-generation-companies’ model for the case of demand with price sensitivity and analysis of the profits depending upon bidding strategies. The results show that, without a demand response, generation companies with diverse generation can increase their profit by strategic bidding. Moreover, under this condition, even if the demand response is made sensitive, these characteristics do not change. It is clarified that one of these factors is the operating constraint of power generators. If the generation company’s low-cost power generators decrease, the company’s profit monotonically decreases as the speculated capacity increases. However, realizing this case requires an unreal demand response and many small companies without diverse generation. Unless the conditions above are satisfied, the wholesale power transactions only through a day-ahead market without price-sensitive demand mechanisms would create a sellers' market, where the sellers can easily manipulate the price.

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