Hourly Dynamic Emission Factors and Integrated Optimization of Electricity Market Prices in Grid-Connected Photovoltaic Systems: Sensitivity Analysis Under Sales Quotas and Decarbonization Scenarios

Abstract

This study develops a single-level energy management optimization model that evaluates hourly electricity market data and hourly dynamic emission factors (DEF) within a grid-connected photovoltaic (PV) system. The model uses hourly PV production data for 2025, hourly market clearing price (MCP) data from the EPİAŞ day-ahead market, and hourly dynamic emission factors. The aim is to maximize total benefit by considering both the revenue from electricity sales and the carbon credits associated with the estimated avoided emissions resulting from PV energy exported to the grid during periods of high grid carbon intensity. To represent real grid operating conditions, a quota constraint for annual energy sales to the grid is defined, and the model is tasked with distributing this quota to the most optimal hours throughout the year. According to the baseline scenario results, where 60% of annual PV production is allowed to be sold to the grid and the carbon credit price is set at USD 15/tCO2, 8062.04 MWh was curtailed due to quota restrictions. As a result of the optimum hourly sales plan, electricity sales revenue of USD 1,007,770.44 and carbon credits of USD 81,460.01 were obtained. The estimated quantity of avoided emissions, calculated according to dynamic emission factors, was 5430.67 tons of CO2. In this study, comprehensive sensitivity analyses were conducted to evaluate the effects of different grid sales quota levels, carbon credit prices, and hourly emission factor reduction scenarios, representing the long-term decarbonization of the grid in line with Türkiye’s 2053 Net Zero Emissions Target. The findings suggest that dynamic emission factors are one of the key elements determining the economic and environmental performance of PV systems under different sales limits, carbon credit prices, and emission reduction scenarios.