Prosumer Energy Management Considering Contract With Consumers Under Progressive Pricing Policy

• Main Authors: Laihyuk Park, Yeunggurl Yoon, Sungrae Cho, Sungyun Choi
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Energy management; energy storage; uncertainty; energy efficiency; progressive pricing; prosumer
• Online Access: https://ieeexplore.ieee.org/document/9123872/

The prosumer market allows prosumers to sell their energy surplus to consumers. The prosumer should offer the amount of energy to sell and its unit price to the contracted consumers while economically operating their system. This paper presents optimal operations and business strategies to maximize the prosumer's benefit by utilizing an energy storage system and ensuring a contract with residential consumers under a progressive pricing policy, where electricity unit price increases with the amount of monthly electricity consumption. By the proposed method, a prosumer under time-of-use pricing scheme stores abundant renewable energy or utility energy at a low price and uses it during a high-price period. Moreover, the proposed optimization can determine the amount of energy and the unit price that the prosumer will offer as a contract in a way that gives consumers strong motivation for the contract; the contract can eventually alleviate consumers' electricity rates by avoiding a high-price zone. For optimization, a quadratic objective problem with quadratic constraints is formulated, and the interior-point algorithm with the Hessian function is used. This study investigates the effectiveness of the proposed method not only under the various penetration rates of renewables but in consideration of uncertainties of renewables and loads. Based on actual field data from Jeju Island of South Korea for 30 days, numerical simulations were performed, and the results indicate that the prosumer's operating costs were reduced by about 12%, simultaneously offering a smaller contract price to the consumer. The Hessian function of the Lagrangian reduced the processing time for the optimization by a maximum of 98.3%. Finally, the ensemble forecast method generating multiple statistical scenarios was tested to address the uncertainty of renewables, showing that the uncertainty had no impact on the contract price and energy.