Direct load control-based optimal scheduling strategy for demand response of air-conditioning systems in rural building complex

Abstract

The abrupt surge in electricity consumption for air-conditioning (AC) in rural areas has exacerbated the rural power supply and demand imbalance, presenting a significant challenge to the reliability and stability of power provision in rural low-voltage grids. Implementing power demand response (DR) in buildings is recognized as an effective solution to address the grid's power imbalance and reliability issues. Among various building DR strategies, direct load control (DLC) stands out as a proficient approach to rapidly curtail building AC loads. However, applying this method solely to individual rural buildings proves less effective in peak regulation (PR). To fully exploit the DR potential of AC systems in rural building complex, it is essential to scale up the application of DLC. Consequently, a DLC-based DR optimal scheduling strategy is proposed for rural building complex AC systems. This strategy aims to meet PR demand and maximize the benefits for load aggregator. It establishes four DLC methods and differential compensation mechanisms, taking into account the varying thermal comfort requirements of AC users. The DR optimization model is solved using a genetic algorithm (GA), with PR demand derived from long and short-term memory neural network predictions. To validate the proposed strategy, a simulation study is conducted on a 200-unit farmhouse AC system, utilizing a typical rural soil source heat pump system in Xi'an, Shaanxi Province. The results demonstrate that the strategy surpasses the PR target by approximately 6.65 % during the DR period, while ensuring a minimum level of thermal comfort for all user categories. Additionally, it yields a PR benefit of 88.73 yuan per day for all users, thereby promoting the adoption of clean energy in rural areas.