Bilateral contract transaction among generation companies and large consumers is attracting much attention in the electricity market. A large consumer can purchase energy from generation companies directly under a bilateral contract, which can guarantee the economic interests of both sides. However, in pursuit of more profit, the competitions in the transaction exist not only between the company side and the consumer side, but also among generation companies. In order to maximize its profit, each company needs to optimize bidding price to attract large consumers. In this paper, a master-slave game is proposed to describe the competitions among generation companies and large consumers. Furthermore, a Bayesian game approach is formulated to describe the competitions among generation companies considering the incomplete information. In the model, the goal of each company is to determine the optimal bidding price with Bayesian game; and based on the bidding price provided by companies and the predicted spot price, large consumers decide their personnel purchase strategy to minimize their cost. Simulation results show that each participant in the transaction can benefit from the proposed game.
Abstract:In a competitive electricity market with substantial involvement of renewable electricity, maximizing profits by optimizing bidding strategies is crucial to different power producers including conventional power plants and renewable ones. This paper proposes a game-theoretic bidding optimization method based on bi-level programming, where power producers are at the upper level and utility companies are at the lower level. The competition among the multiple power producers is formulated as a non-cooperative game in which bidding curves are their strategies, while uniform clearing pricing is considered for utility companies represented by an independent system operator. Consequently, based on the formulated game model, the bidding strategies for power producers are optimized for the day-ahead market and the intraday market with considering the properties of renewable energy; and the clearing pricing for the utility companies, with respect to the power quantity from different power producers, is optimized simultaneously. Furthermore, a distributed algorithm is provided to search the solution of the generalized Nash equilibrium. Finally, simulation results were performed and discussed to verify the feasibility and effectiveness of the proposed non-cooperative game-based bi-level optimization approach.
Purpose -This paper aims to answer the following questions concerning rural-to-urban labor migration in China: What is the impact of discrimination against non-Hukou in urban public service provision? Will such discrimination disappear in the future within the current policy-making framework? What is the result of such an endogenous policy change as far as urbanization and economic growth are concerned? Design/methodology/approach -The authors build a theoretical model of rural-urban migration, taking into account the cost of social conflict due to discrimination against urban non-Hukou in local public service. The possibility of endogenous policy change is also considered by numerical simulation. Findings -The authors prove that, in the early stage of urban economic growth when the losses of potential conflicts are relatively small, the exclusive urban public service provision may be beneficial to them, but the losses under such unequal public service provision policy increase in the process of urban growth, and after a certain stage of development, opening public service access equally to the immigrants will be a better choice, even if only the natives' utility is considered. Such an endogenous policy change not only decreases the within-city inequality and conflicts, but also advances the urbanization and urban economic growth.Research limitations/implications -The authors only consider two extreme cases of local public service provision, that is, the urban non-Hukou residents have equal access to public service or they are totally not entitled. The possibility of partial access to local public service is not considered in the model. Originality/value -The authors investigate impact of social conflicts on within-city inequality, urbanization as well as urban economic growth due to unequal social public service within urban residents. The model also shows an endogenous policy change during rural-urban labor migration.
Purpose
The purpose of this paper is to analyze the effects of private investor's fair preference on the governmental compensation mechanism based on the uncertainty of income for the public-private-partnership (PPP) project.
Design/methodology/approach
Based on the governmental dilemma for the compensation of PPP project, a generalized compensation contract is designed by the combination of compensation before the event and compensation after the event. Then the private investor's claimed concession profit is taken as its fair reference point according to the idea of the BO model, and its fair utility function is established by improving the FS model. Thus the master-slave counter measure game is applied to conduct the behavior modeling for the governmental compensation contract design.
Findings
By analyzing the model given in this paper, some conclusions are obtained. First, the governmental optimal compensation contract is fair incentive for the private investor. Second, the private fair preference is not intuitively positive or negative related to the social efficiency of compensation. Only under some given conditions, the correlation will show the consistent effect. Third, the private fair behavior’s impact on the efficiency of compensation will become lower and lower as the social cost of compensation reduces. Fourth, the governmental effective compensation scheme should be carried out based on the different comparison scene of the private claimed portfolio profit and the expected revenue for the project.
Originality/value
This study analyzes the effects of private investor's fair preference on the validity of governmental generalized compensation contract of the PPP project for the first time; and the governmental generalized compensation contract designed in this study is a pioneering and exploratory attempt.
Integrated energy systems (IESs) have attracted increasing attention in recent years due to the high energy efficiency and low emission of carbon dioxide. To deal with the limitation of single IES, distributed energy networks consisting of multi-IESs are proposed to improve the complementarity of both the energy supply and the demand. This paper mainly focuses on the day-ahead energy management of the whole energy network for the economic operation of the system, following which, a cooperative game is formulated to determine the optimal strategy of each IES to minimize the coalition daily cost. Meanwhile, an allocation mechanism is designed from the perspective of probability to allocate coalition cost to each IES. According to the results of the numerical study, the proposed approach can improve the economic performance of both the energy network and the individual IES by interchanging electrical and thermal energies in the network.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.