Stochastic multi-objective expansion of renewable resources in distribution systems incorporating responsive loads towards achieving zero energy structure

Due to the increase in global warming and environmental pollution, heavy penalties have been imposed on pollution producers such as electrical energy networks. Hence, the role of renewable resources expansion in power systems is unavoidable. However, their high penetration increases the uncertainties and decreases the reliability. This paper investigates the expansion of renewable resources in distribution systems based on the zero energy concept. In this regard, different scenarios are designed to determine the optimal location and sizing of wind turbines and photovoltaics as the most matured technologies. To achieve such a goal, a multiobjective linear programming consisting of investment cost and environmental pollution is suggested, which is solved by the augmented epsilon constraint method. Moreover, an incentive-based demand response program is implemented using shiftable and curtailable responsive loads. Eventually, the uncertainties of renewable resources are modeled by a scenario generation and reduction approach to simulate realistic conditions. The results show that the system that includes only wind turbines or only photovoltaics cannot completely overcome the pollution problem due to the uncertainties. By contrast, a zero energy structure is achievable by their combination, where the investment cost is increased by 73.17% and 48.13% compared to the separate expansion of photovoltaics and wind turbines, respectively. The participation of responsive loads decreases the investment cost by 49.29% as well. Furthermore, the uncertainties of renewable resources increase the total cost by only about 5.95% in the presence of responsive loads; however, the system will be robust against at least 6% of wind turbines and photovoltaics fluctuations.

Automated summary

This paper investigates the expansion of renewable resources in distribution systems based on the zero energy concept. Different scenarios are designed to determine the optimal location and sizing of wind turbines and photovoltaics. A multiobjective linear programming and an incentive-based demand response program are suggested to minimize investment cost and environmental pollution. The uncertainties of renewable resources are modeled and the results show that a combination of wind turbines and photovoltaics can achieve a zero energy structure with increased investment cost, and the participation of responsive loads can decrease the investment cost.