Abstract
In recent years, taking advantage of renewable energy sources (RESs) has increased considerably due to their unique capabilities, such as a flexible nature and sustainable energy production. Prosumers, who are defined as proactive users of RESs and energy storage systems (ESSs), are deploying economic opportunities related to RESs in the electricity market. The prosumers are contracted to provide specific power for consumers in a neighborhood during daytime. This study presents optimal scheduling and operation of a prosumer owns RESs and two different types of ESSs, namely stationary battery (SB) and plugged-in electric vehicle (PHEV). Due to the intermittent nature of RESs and their dependency on weather conditions, this study introduces a weather prediction module in the energy management system (EMS) by the use of a feed-forward artificial neural network (FF-ANN). Linear regression results for predicted and real weather data have achieved 0.96, 0.988, and 0.230 for solar irradiance, temperature, and wind speed, respectively. Besides, this study considers the depreciation cost of ESSs in an objective function based on the depth of charge (DOD) reduction. To investigate the effectiveness of the proposed strategy, predicted output and the real power of RESs are deployed, and a mixed-integer linear programming (MILP) model is used to solve the presented day-ahead optimization problem. Based on the obtained results, the predicted output of RESs yields a desirable operation cost with a minor difference (US$0.031) compared to the operation cost of the system using real weather data, which shows the effectiveness of the proposed EMS in this study. Furthermore, optimum scheduling with regard to ESSs depreciation term has resulted in the reduction of operation cost of the prosumer and depreciation cost of ESS in the objective function has improved the daily operation cost of the prosumer by $0.8647.
Highlights
Over the last two decades, using renewable energy sources (RESs) such as wind turbines (WTs) and photovoltaic (PV) systems has increased considerably due to some environmental concerns andAppl
Some theoretical details of the multilayer perceptron (MLP) are available in a case study was defined in a further subsection (Section 4.3.3) in order to analyze the level of accuracy
Day-ahead optimization was conducted by taking advantage of time of use (TOU) prices and real load data as well as predicted weather data according to details described in previous sections
Summary
Over the last two decades, using renewable energy sources (RESs) such as wind turbines (WTs) and photovoltaic (PV) systems has increased considerably due to some environmental concerns andAppl. Sci. 2020, 10, 2774 their unique features. From this perspective, traditional centralized power generations are replaced with modern forms of decentralized power generation, which can change consumption and production patterns pragmatically. In the modern electricity market, a new expression has been recently introduced to present a bilateral role. Prosumers are regarded as an entity consumes electrical energy and reserve the capability to generate electricity in a reasonable way. It is often argued that market reform and regulatory support promote electricity market and ensure the promising profits to individual prosumers. The distribution system operator (DSO) encourages prosumers to achieve benefits and reduction in maintenance and expansion cost of equipment. In the U.S and some European countries, the development of this kind of market has led to achieving a great balance between supplies and demand as well [1,2,3,4,5]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
