scholarly journals An approach to balance state of charges of distributed batteries in virtual power plants

2018 ◽  
Vol 56 (1) ◽  
pp. 81
Author(s):  
Duc Huu Nguyen
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
State Of Charge ◽  
Energy Sources ◽  
Virtual Power ◽  
Distributed Energy ◽  
Virtual Power Plant ◽  
Virtual Power Plants ◽  
Balance State ◽  
The Difference

Small distributed energy sources could be aggregated to form a virtual power plant (VPP) in order to overall improve technical and market issues. VPPs should be composed of several distributed batteries (DB) to solve the problem of intermittency due to wind and solar. This paper presents an approach to balance state of charge batteries. It is therefore to improve the lifetime of batteries in VPPs. According to the proposed method, the real-time SOC of DB will be tracking on the balancing SOC determined in VPP. During operation, the difference of SOC among DBs will be shrunk and finally the share of exchange power among DB is equal. Moreover, the duration time to achieve the balancing SOC can be determined by adjusting the exponent parameter of SOC in the presented function.

scholarly journals A Virtual Power Plant Solution for Aggregating Photovoltaic Systems and Other Distributed Energy Resources for Northern European Primary Frequency Reserves

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1242
Author(s):  
Rakshith Subramanya ◽  
Matti Yli-Ojanperä ◽  
Seppo Sierla ◽  
Taneli Hölttä ◽  
Jori Valtakari ◽  
...  
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Photovoltaic Systems ◽  
Virtual Power ◽  
Distributed Energy ◽  
Virtual Power Plant ◽  
Virtual Power Plants ◽  
Primary Frequency

Primary frequency reserves in Northern Europe have traditionally been provided with hydro plants and fossil fuel-burning spinning reserves. Recently, smart distributed energy resources have been equipped with functionality needed to participate on frequency reserves. Key categories of such resources include photovoltaic systems, batteries, and smart loads. Most of these resources are small and cannot provide the minimum controllable power required to participate on frequency reserves. Thus, virtual power plants have been used to aggregate the resources and trade them on the frequency reserves markets. The information technology aspects of virtual power plants are proprietary and many of the details have not been made public. The first contribution of this article is to propose a generic data model and application programming interface for a virtual power plant with the above-mentioned capabilities. The second contribution is to use the application programming interface to cope with the unpredictability of the frequency reserve capacity that the photovoltaic systems and other distributed energy resources are able to provide to the frequency reserves markets in the upcoming bidding period. The contributions are demonstrated with an operational virtual power plant installation at a Northern European shopping center, aggregating photovoltaic Primary Frequency Reserves resources.

scholarly journals Clustering time series applied to energy markets

2019 ◽  
Vol 2 (S1) ◽  
Author(s):  
Cornelia Krome ◽  
Jan Höft ◽  
Volker Sander
Keyword(s):  
Time Series ◽  
Power Plant ◽  
Electricity Market ◽  
Power Plants ◽  
Large Scale ◽  
Energy Systems ◽  
Weather Data ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Virtual Power Plants

Abstract In Germany and many other countries the energy market has been subject to significant changes. Instead of only a few large-scale producers that serve aggregated consumers, a shift towards regenerative energy sources is taking place. Energy systems are increasingly being made more flexible by decentralised producers and storage facilities, i.e. many consumers are also producers. The aggregation of producers form another type of power plants: a virtual power plant. On the basis of aggregated production and consumption, virtual power plants try to make decisions under the conditions of the electricity market or the grid condition. They are influenced by many different aspects. These include the current feed-in, weather data, or the demands of the consumers. Clearly, a virtual power plant is focusing on developing strategies to influence and optimise these factors. To accomplish this, many data sets can and should be analysed in order to interpret and create forecasts for energy systems. Time series based analytics are therefore of particular interest for virtual power plants. Classifying the different time series according to generators, consumers or customer types simplifies processes. In this way, scalable solutions for forecasts can be found. However, one has to first find the according clusters efficiently. This paper presents a method for determining clusters of time series. Models are adapted and model-based clustered using ARIMA parameters and an individual quality measure. In this way, the analysis of generic time series can be simplified and additional statements can be made with the help of graphical evaluations. To facilitate large scale virtual power plants, the presented clustering workflow is prepared to be applied on big data capable platforms, e.g. time series stored in Apache Cassandra, analysed through an Apache Spark execution framework. The procedure is shown here using the example of the Day-Ahead prices of the electricity market for 2018.

scholarly journals Optimal Management of a Virtual Power Plant

2016 ◽  
Vol 1 (3) ◽  
pp. 106
Author(s):  
Dan Jigoria-Oprea ◽  
Gheorghe Vuc ◽  
Marcela Litcanu
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Optimal Management ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Renewable Power ◽  
System Operator ◽  
Energy Companies

Deregulation of energy market led to the development of flexible and efficient framework for energy trading by energy companies in a competitive environment. Both deregulation and the concern towards environment issues increased the number of small and medium renewable power plants distributed in the network. The variability of renewable energy sources and the lack of their central monitoring led to new challenges concerning power system operation. The idea of aggregation for distributed energy sources led to the concept of virtual power plant, which determines a better control of production units but also a better visibility for the system operator. In this paper, the authors propose an optimal management solution which can offer a virtual power plant the capability to sell complete services, both for production and demand side management, by decreasing the necessary reserve for balance.

scholarly journals Bidding Strategy of Virtual Power Plant with Energy Storage Power Station and Photovoltaic and Wind Power

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zhongfu Tan ◽  
Qingkun Tan ◽  
Yuwei Wang
Keyword(s):  
Energy Storage ◽  
Power Plant ◽  
Wind Power ◽  
Electricity Market ◽  
Power Plants ◽  
Bidding Strategy ◽  
Virtual Power ◽  
Power Station ◽  
Virtual Power Plant ◽  
Virtual Power Plants

For the virtual power plants containing energy storage power stations and photovoltaic and wind power, the output of PV and wind power is uncertain and virtual power plants must consider this uncertainty when they participate in the auction in the electricity market. In this context, this paper studies the bidding strategy of the virtual power plant with photovoltaic and wind power. Assuming that the upper and lower limits of the combined output of photovoltaic and wind power are stochastically variable, the fluctuation range of the day-ahead energy market and capacity price is stochastically variable. If the capacity of the storage station is large enough to stabilize the fluctuation of the output of the wind and photovoltaic power, virtual power plants can participate in the electricity market bidding. This paper constructs a robust optimization model of virtual power plant bidding strategy in the electricity market, which considers the cost of charge and discharge of energy storage power station and transmission congestion. The model proposed in this paper is solved by CPLEX; the example results show that the model is reasonable and the method is valid.

scholarly journals Energy Management of Virtual Power Plant Considering Distributed Generation Sizing and Pricing

2019 ◽  
Vol 9 (14) ◽  
pp. 2817 ◽  
Author(s):  
Masoud Maanavi ◽  
Arsalan Najafi ◽  
Radu Godina ◽  
Mehrdad Mahmoudian ◽  
Eduardo M. G. Rodrigues
Keyword(s):  
Power Plant ◽  
Energy Management ◽  
Smart Grids ◽  
Power Plants ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Security Issues ◽  
Network Availability ◽  
Virtual Power Plants ◽  
Efficient Vector

The energy management of virtual power plants faces some fundamental challenges that make it complicated compared to conventional power plants, such as uncertainty in production, consumption, energy price, and availability of network components. Continuous monitoring and scaling of network gain status, using smart grids provides valuable instantaneous information about network conditions such as production, consumption, power lines, and network availability. Therefore, by creating a bidirectional communication between the energy management system and the grid users such as producers or energy applicants, it will afford a suitable platform to develop more efficient vector of the virtual power plant. The paper is treated with optimal sizing of DG units and the price of their electricity sales to achieve security issues and other technical considerations in the system. The ultimate goal in this study to determine the active demand power required to increase system loading capability and to withstand disturbances. The effect of different types of DG units in simulations is considered and then the efficiency of each equipment such as converters, wind turbines, electrolyzers, etc., is achieved to minimize the total operation cost and losses, improve voltage profiles, and address other security issues and reliability. The simulations are done in three cases and compared with HOMER software to validate the ability of proposed model.

scholarly journals Multi-objective Interval Optimization of Virtual Power Plant Considering the Uncertainty of Source and Load

2021 ◽  
Vol 299 ◽  
pp. 01011
Author(s):  
Shuai Han ◽  
Leping Sun ◽  
Xiaoxuan Guo ◽  
Jianbin Lu
Keyword(s):  
Power Plant ◽  
Electric Vehicles ◽  
Power Plants ◽  
Interval Optimization ◽  
Virtual Power ◽  
Power Sources ◽  
Distributed Power ◽  
Virtual Power Plant ◽  
Multi Objective ◽  
Virtual Power Plants

As the proportion of electric vehicles and distributed power sources connected to the power grid continues to increase, virtual power plants provide new ideas for effectively solving electric vehicles and distributed power sources connected to the grid. Considering that there are obvious uncertainties in the number of dispatchable electric vehicles and the output of distributed power sources, this paper focuses on the multi-objective interval optimization problem of virtual power plants considering the uncertainty of source load. Based on the analysis of the virtual power plant architecture, aiming at the uncertainty of the source load, a multi-objective interval optimization model of the virtual power plant was established using the interval number theory; in order to verify the validity of the established model, a virtual power plant in a certain area was selected as an example for analysis. The results show that the uncertainty of distributed power sources and electric vehicles can be better avoided in the interval optimization process, and the proposed scheme has strong robustness.

scholarly journals Research on Two-stage Game Strategy of Virtual Power Plant in Deep Peak Regulation Auxiliary Service Market

2021 ◽  
Vol 256 ◽  
pp. 01026
Author(s):  
Yuan Guili ◽  
Chen Sixuan ◽  
Dou Xiaoxuan
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Northern China ◽  
Combined Heat And Power ◽  
Correction Coefficient ◽  
Virtual Power ◽  
Two Stage ◽  
Service Market ◽  
Virtual Power Plant ◽  
Virtual Power Plants

There is a large number of combined heat and power units in northern China, and due to the limit of heating demand, the operating mode of setting electricity by heat of combined heat and power units has seriously took over the consumption space of other energy, resulting in severe wind power curtailment and rationing situation in some areas, so this paper studies the deep peak regulation bidding strategy problem considering multiple uncertainties on virtual power plants, and established a two-staged optimization model of virtual power plant to maximize the net revenue, then introduced the Shapely value method with correction coefficient redistribute the peak regulation revenue. The simulation results showed that the two-stage bidding model can not only improve the market competitiveness of the virtual power plant, but also promote the consumption of renewable energy and reduce the market peak regulation service cost. Meanwhile, the improved apportion method can effectively guarantee the enthusiasm of all kinds of units to participate in the deep peak regulation market.

scholarly journals Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework

2021 ◽  
Vol 11 (9) ◽  
pp. 3814
Author(s):  
Poushali Pal ◽  
Parvathy Ayalur Krishnamoorthy ◽  
Devabalaji Kaliaperumal Rukmani ◽  
S. Joseph Antony ◽  
Simon Ocheme ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Virtual Power ◽  
Distributed Energy ◽  
Distribution Method ◽  
Virtual Power Plant ◽  
Optimal Dispatch ◽  
Market Framework

Renewable energy sources prevail as a clean energy source and their penetration in the power sector is increasing day by day due to the growing concern for climate action. However, the intermittent nature of the renewable energy based-power generation questions the grid security, especially when the utilized source is solar radiation or wind flow. The intermittency of the renewable generation can be met by the integration of distributed energy resources. The virtual power plant (VPP) is a new concept which aggregates the capacities of various distributed energy resources, handles controllable and uncontrollable loads, integrates storage devices and empowers participation as an individual power plant in the electricity market. The VPP as an energy management system (EMS) should optimally dispatch the power to its consumers. This research work is proposed to analyze the optimal scheduling of generation in VPP for the day-ahead market framework using the beetle antenna search (BAS) algorithm under various scenarios. A case study is considered for this analysis in which the constituting energy resources include a photovoltaic solar panel (PV), micro-turbine (MT), wind turbine (WT), fuel cell (FC), battery energy storage system (BESS) and controllable loads. The real-time hourly load curves are considered in this work. Three different scenarios are considered for the optimal dispatch of generation in the VPP to analyze the performance of the proposed technique. The uncertainties of the solar irradiation and the wind speed are modeled using the beta distribution method and Weibull distribution method, respectively. The performance of the proposed method is compared with other evolutionary algorithms such as particle swarm optimization (PSO) and the genetic algorithm (GA). Among these above-mentioned algorithms, the proposed BAS algorithm shows the best scheduling with the minimum operating cost of generation.

Sign in / Sign up

Export Citation Format

Share Document