Demand response model by locational marginal electricity–carbon price considering wind power uncertainty and energy storage systems

With the increasing prominence of global carbon emissions, how to achieve carbon emission reduction in power systems is an urgent issue. Early research introduced carbon cost in the objective functions or constraints in an optimization model. However, the carbon cost cannot account for the time-varying carbon emissions caused by load electricity consumption. To address this challenge, this paper proposes a demand response (DR) program based on the locational marginal prices on both electricity consumption and carbon emission to reshape the load consumption pattern, which guide the load from both "electricity perspective" and "carbon perspective". This model can reduce the carbon emissions of the power system while considering the economics of power purchase and the traditional DR to peak load shifting. Meanwhile, historical data fitting, Monte Carlo sampling and scenario reduction techniques are used to take full account of wind power uncertainties. The energy storage (ES) systems are introduced to simultaneously arbitrage from both electricity and carbon markets by appropriate charging strategies. The simulation results using PJM 5-bus system show that the locational marginal electricity–carbon price proposed in this paper can reduce the carbon emissions of the power system while ensuring an economic operation. By adding the carbon emission factor to the price, the load demand not only follows the fluctuation of electricity price, but also shows the trend of following the change of carbon emission.