Abstract
To improve the coordination and complementarity of multiple energy sources, balancing the interests of different participants in a multi-energy system is of great importance. However, traditional centralized optimization can hardly reflect the game relationship between supply side and demand sides. A trading model based on the Stackelberg game model is proposed in this paper to balance the interests of the supply side and demand side and reduce the carbon emissions. First of all, the process of trading between the supply side and demand side based on smart contracts is described. A contractual consensus is obtained through an internal game, and the transaction is completed automatically. Secondly, a bilevel optimization model is established to coordinate the benefits of both parties based on the Stackelberg game model. The energy operator acts as a leader, and considers the two objectives, i.e., maximizing net income and minimizing carbon emissions, and uses the linear weighting method to convert the dual objectives into single objective. Users act as followers and aim to increase the comprehensive benefits, including energy cost and comfort. Then, Karush–Kuhn–Tucker optimality condition is used to transform the bilevel optimization model into an equivalent single-level model. Finally, simulation results show that the proposed method can coordinate the economic interests of both sides of supply and demand and effectively reduce the carbon emissions of the energy operator.
Highlights
As the world’s energy demand increases and natural resources come under enormous pressure, it has become an important strategy for all countries to improve the efficiency of energy utilization [1]
The operation and planning of traditional energy systems are limited to systems formed by single energy sources, such as electricity, gas, and heat, which cannot meet the needs of the current society
The energy operator effectively manages the operation of all equipment including cooling heat and power cogeneration system (CCHP), gas boiler (GB), heat pump (HP), centrifuge (Cen), and thermal storage tank (ST) to increase economic benefits and reduce carbon emissions
Summary
As the world’s energy demand increases and natural resources come under enormous pressure, it has become an important strategy for all countries to improve the efficiency of energy utilization [1]. Dashti et al [16] proposed an energy pricing model of smart distribution networks with multiple microgrids based on the non-cooperative game theory, in which the profits of all beneficiaries are guaranteed. For the bilevel optimization model, many literatures directly transfer the associated variables between the upper and lower models, such as prices of energy in the upper layer and power of load in the lower layer This method is causes the upper model to fall into the local optimal solution. This paper proposes an interaction method between supply and demand sides based on the Stackelberg game. The energy operator, as a leader, considers two objectives, i.e., economic net income and carbon emissions, and uses the linear weighting method to convert the two objectives into single objective.
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