Optimal Day-ahead Dynamic Pricing of Grid-connected Residential Renewable Energy Resources Under Different Metering Mechanisms

Abstract

Nowadays, grid-connected renewable energy resources have widespread applications in the electricity market. However, providing household consumers with photovoltaic (PV) systems requires bilateral interfaces to exchange energy and data. In addition, residential consumers' contribution requires guaranteed privacy and secured data exchange. Dayahead dynamic pricing is one of the incentive-based demand response methods that has substantial effects on the integration of renewable energy resources with smart grids and social welfare. Different metering mechanisms of renewable energy resources such as feed-in tariffs, net metering, and net purchase and sale are important issues in power grid operation planning. In this paper, optimal condition decomposition method is used for dayahead dynamic pricing of grid-connected residential renewable energy resources under different metering mechanisms: feed-intariffs, net metering, and net purchase and sale in conjunction with carbon emission taxes. According to the stochastic nature of consumers' load and PV system products, uncertainties are considered in a two-stage decision-making process. The results demonstrate that the net metering with the satisfaction average of 68% for consumers and 32% for the investigated electric company leads to 28% total load reduction. For the case of net purchase and sale mechanism, a satisfaction average of 15% for consumers and 85% for the electric company results in 11% total load reduction. In feed-in-tariff mechanism, in spite of increased social welfare, load reduction does not take place.

Improved Low-Cost Home Energy Management Considering User Preferences with Photovoltaic and Energy-Storage Systems

“…In this study, for making optimum and decentralized decisions for various household devices, multi-agent reinforcement learning was used along with predicted upcoming costs. Parandeh et al proposed OCDM for day-ahead dynamic pricing of grid-connected residential renewable energy resources under different metering mechanisms: feed-in-tariffs, net metering and net purchase and sale in conjunction with carbon emission taxes [15]. According to the stochastic nature of consumers' load and PV-system products, uncertainties were considered in a two-stage decision-making process.…”

Voltage regulation in low voltage distribution networks with unbalanced penetrations of photovoltaics and battery storage systems

“…Day-ahead dynamic pricing strategies based on time-varying feed-in tariffs (FiTs), net metring, and net purchase/sale were evaluated in Ref. [12], aimed at maximising consumer profits. The results show that the profitability of day-ahead dynamic pricing varies under each of the metering mechanisms.…”