Increasing generation capacity of natural gas and renewable energy for economic dispatch benefit and carbon credit allocation in perspective of power generation end

Abstract A carbon credit is a permit to allocate specific carbon emissions and can also be converted into a traded commodity through the carbon trading market (CTM). For government agencies and private enterprises, these carbon credits can be traded on the CTM. Under this trading mechanism, the institutions with low‐carbon emissions can obtain the specific benefits and rewards from fossil fuel consumption reduction, carbon emission reduction, and remaining carbon emissions credits, thereby incentivizing them to reduce greenhouse gas (GHG) emissions and achieve the overall carbon reduction goals. Carbon emissions can be reduced from either power generation ends or high‐level pollution electricity‐consumer ends. Under the schemes of regulated and voluntary markets, the target of carbon emission reduction can be achieved within a foreseeable timeframe by using the power generation proportions adjustment, saving energy on the electricity‐consumer ends, strengthening energy management and efficiency, and increasing renewable energy penetration in the electrical grid. However, power generation significantly has major contributions to carbon dioxide (CO 2 ) and other GHG emissions. For economic dispatch (ED) and carbon emission allocation, this study investigates the ED benefits of power generation proportions adjustment with increasing the generation capacity of natural gas and renewable energy in perspective of power generation end. Four typical scenarios are designed and advanced strategy with different power generation proportions to obtain the fuel cost of various generation units, the carbon emissions of various fuel units, and the benefits of carbon emission reductions, which are used to validate the benefits of increasing the proportions of natural gas generations and renewable energy as decreasing the proportions of oil fuel generations. Considering various scenarios, fuel costs, pollution emissions, and increasing renewable energy, the power generation, carbon emissions, and allowable carbon emissions of various generating units can be estimated by using the swarm intelligence optimization algorithm, such as the particle swarm optimization algorithm (PSOA), which can offer the carbon credit allocation and trading information in the CTM.