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A group of energy resources distributed in the network which are placed under a unified and integrated management with a central control system is called a Virtual Power Plant (VPP). Electromechanical storage units composing VPP may provide arbitrage opportunities in power market. This paper proposes a new mathematical approach based on a comprehensive model for arbitrage of a VPP in power markets. In our proposed model network topology, VPP constraints and network constraints are considered. The method determines the amount of energy and reserve that should be bought or sold in day-ahead markets, commitment of distributed energy resources, charge or discharge status of storage units and the amount of load curtailments. By applying the proposed model to a case study, different arbitrage opportunities for VPP in power market are investigated.

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In recent years, the penetration of distributed energy resources has been increased dramatically in the power system, however, according to their small capacity, we need to aggregate these resources in an incorporated unit and examine their participation in the energy and ancillary services market. This goal can be achieved using virtual power plants (VPPs) concept. This paper describes the optimal bidding strategy of a VPP in the energy and spinning reserve markets. In order to improve the performance of the VPP, dispatchable distributed generation (DGs) sources, wind turbines (WTs), thermal and electrical energy storages, combined heat and power (CHP) unit and electric vehicles (EVs) have been considered in the VPP structure. The optimization task has also been addressed in the form of a MILP problem with considering the network and unit constraints and smart EVs’ charging. Finally, to evaluate the effectiveness of the proposed method, simulations are performed on a 21-bus VPP. The simulation results show that the VPP profit will increase by 23% by participating in the spinning reserve market.

 

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Due to the progress of renewable energy technologies and the intention of energy policymakers to use these clean and cheap resources, many studies have focused on ways to take advantage of these energies. Limitations, such as low capacity, output power uncertainty, and sustainability problems, make the use of distributed energy resources costly and difficult. Among distributed generation resources, renewable energy resources such as wind energy and solar energy are more environmentally friendly and are used more than other technologies. Despite the many advantages of these resources, their output power depends on such factors as wind speed and solar intensity, which cannot be accurately predicted. For this reason, the infiltration[MSH1]  of high levels of these resources into power systems increases system uncertainty and can reduce reliability while system reliability is very important for power system designers and operators, as well as energy consumers. To solve these problems, a new concept, named virtual power plant, is proposed. A virtual power plant is a collection of distributed energy resources that come together to participate in the market. Virtual power plants can efficiently coordinate, aggregate, and manage different distributed energy resources such as distributed generation, energy storage systems, and controllable loads. These plants are flexible agents for a range of distributed energy sources that can be used in wholesale markets to provide services to system operators. The energy management system is the heart of a virtual power plant that coordinates the flow of power from generators, controllable loads, and energy storage devices. This paper proposes a full model for optimal planning of a virtual power plant if uncertainties of distributed generation sources such as wind and solar energy, as well as electrical vehicles, are considered. To prevent the negative effects of the presence of electric vehicles on electricity networks, especially in virtual power plants, it is necessary to charge these vehicles in a controlled manner and with careful planning. In addition, the demand response whose modeling is based on price-based demand response for non-users and encouragement-based for electric vehicles is optimized on two scenarios, and a 32-bus network is studied. The main goal of the research is to maximize the profit of the virtual power plant for the simultaneous use of load response and electric vehicles with the capability of connecting to the grid.
 

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 New power systems based on virtual power plants (VPPs) will expand in the future, so it is of crucial importance for system operators to analyze the frequency behavior of these systems compared to current systems in the field of disruptions. In this paper, the equations of the frequency response model of conventional power systems are expanded by considering VPPs and their effective components, and a new model is presented for the frequency response of large power systems based on VPPs. To analyze the frequency behavior of the network, different scenarios are studied on a sample network. To cover the possible situations of the future network, several VPP models with different specifications are considered from the perspective of frequency responsiveness. The simulation results indicate the necessity of using frequency responsive devices in future power networks that are based on VPP.