Abstract
With the technical growth and the reduction of deployment cost for distributed energy resources (DERs), such as solar photovoltaic (PV), energy trading has been recently encouraged to energy consumers, which can sell energy from their own energy storage system (ESS). Meanwhile, due to the unprecedented rise of greenhouse gas (GHG) emissions, some countries (e.g., Republic of Korea and India) have mandated using a renewable energy certificate (REC) in energy trading markets. In this paper, we propose an energy broker model to boost energy trading between the existing power grid and energy consumers. In particular, to maximize the profits of energy consumers and the energy provider, the proposed energy broker is in charge of deciding the optimal demand and dynamic price of energy in an REC-based energy trading market. In this solution, the smart agents (e.g., IoT intelligent devices) of consumers exchange energy trading associated information, including the amount of energy generation, price and REC. For deciding the optimal demand and dynamic pricing, we formulate convex optimization problems using dual decomposition. Through a numerical simulation analysis, we compare the performance of the proposed dynamic pricing strategy with the conventional pricing strategies. Results show that the proposed dynamic pricing and demand control strategies can encourage energy trading by allowing RECs trading of the conventional power grid.
Highlights
With technological advancement and growing awareness on how fossil-fuel-based energy generation is contributing unprecedentedly to global warming and climate change, more and more people are adopting eco-friendly distributed energy resources (DERs)(e.g., harnessing the Sun’s energy using solar photovoltaic cells)
Unlike the solution in [22], where a distributed demand-side management was proposed, taking into consideration the wind power forecasting uncertainty, our solution introduced in this paper considers uncertainty in actual PV generation data, which is widely used in households
We have proposed an optimal demand and dynamic pricing mechanism in order to maximize the profit of consumers by increasing the profit of an energy provider in an energy trading ecosystem where clean energy generation is encouraged through
Summary
With technological advancement and growing awareness on how fossil-fuel-based energy generation is contributing unprecedentedly to global warming and climate change, more and more people are adopting eco-friendly distributed energy resources (DERs). Note that the ISOs may form wholesale power markets where the power transmission operators, utilities and power consumers can trade Due to these energy trading shifts from the conventional energy exchange to energy brokers, dynamic pricing is considered for balancing energy demand and distribution [9]. In [16], a dynamic pricing algorithm is proposed in order to detect spiteful users and insecure energy providers According to this solution, the users only consume energy and do not sell any energy from their DERs to an energy market. The SEAs can be mounted on energy providers, energy brokers, and energy consumer sides Information, such as power generation, energy price, consumption, and renewable energy trading can be defined as distributed local information in their respective areas, and global information can be updated over the communication network to update their local information again. The quantity of carbon footprint in the k-th unit time slot the energy generated by the energy provider in k-th unit time slot
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