Virtual Power Plant Management Research Articles

Efficient virtual power plant management strategy and Leontief-game pricing mechanism towards real-time economic dispatch support: A case study of large-scale 5G base stations

Amidst high penetration of renewable energy, virtual power plant (VPP) technology emerges as a viable solution to bolster power system controllability. This paper integrates a novel flexible load, 5G base stations (gNBs) with their backup energy storage systems (BESSs), into a VPP for power system real-time economic dispatch (RTED). Leveraging BESSs dispatchable capacity, the VPP offers power support and gains economic incentives, where the dispatchable capacity is estimated based on distribution network reliability and gNB availability requirements. Then, an efficient and refined VPP management strategy is proposed, where numerous gNBs are aggregated into limited number of virtual generators (VGs). The VPP dispatchable capacity can be efficiently and accurately evaluated via VGs states. Each VG is assigned a control cost function, enabling optimal control decisions resembling power system RTED, to minimize overall VPP control costs. Finally, a power support and incentive determination mechanism is presented based on the Leontief union bargaining model, ensuring reciprocal transactions between VPP and power system. To solve the Leontief model and address information privacy issues between the two parties, a distributed iterative algorithm is developed. Simulations based on actual data and IEEE 118-bus system illustrate that the proposed approach can smoothen intra-day load profiles, achieving mutual economic benefits for the power system and VPP without compromising the security of 5G network operations.

Levelling the Photovoltaic Power Profile with the Integrated Energy Storage System

The extensive penetration in the energy mix of variable renewable energy sources, such as wind and solar, guarantees boosting of the transition toward a decarbonized and sustainable energy system as well as tackling of climate targets. However, the instability and unpredictability of such sources predominantly affect their plant production. Thus, utility-scale energy storage is required to aid in balancing supply and demand and, as a result, to prevent unbalances that might cause issues at different grid levels. In the present study, the authors’ patented energy storage technology, known as Integrated Energy Storage System (I-ESS), is combined with a 10 MWp solar plant. The PV plant and the I-ESS unit function as a Virtual Power Plant (VPP). The selected VPP management strategy attempts to optimize the daily hours during which the plant supplies steady power output. Numerical simulations show that the VPP plant can effectively smooth the PV peak and manage the power supply. In particular, by the definition of a novel metric expressing the ratio between regular hours of power provided to the grid plus the energy stored in the backup unit and the total number of hours in a year, the results show that the VPP regularity is relatively high in terms of PV output, ranging from a low of 50% in December to a high of 87% in August. Thus, the proposed VPP arrangement seems to be a promising technology for pushing toward the carbon-neutral transition.

Effectiveness of optimization procedures on the economic profitability of a virtual tri-generation power plant connected to a district heating cooling network

This study investigates the impact of an optimized schedule procedure in enhancing the Economic Profitability (EP) of a tri-generation energy facility located in the Northern Italy and connected to a local District Heating and Cooling (DHC) network.The FICOTM Xpress Software has been utilized to optimize the thermal and electrical scheduling of the Combined Heating Cooling Power Plant (CHCPP)–DHC system by making use of both the effective exercise parameters of the CHCPP machines and a series of heating/cooling data loads delivered to the grid and appropriately selected from those considered representative of each season. The complex evolution of the traditional energy market has suggested to improve the optimization procedure by including the constrains resulting from the subscription of a Virtual Power Plant Management (VPPM) agreement. As main purpose, this work analyses and compares the impact that the implementation of both the adopted optimization procedure and the subscription of the VPPM contract can have in enhancing the EP index of the investigated energy facility. The outcomes of this analysis evidence that the acceptance of the VPPM can entail a positive impact of the entire EP index of the facility. This happens at the condition that the machines are rescheduled at the exercise conditions resulting from the simultaneous implementation of an optimization procedure. Therefore, this study highlights the importance of the optimization procedures in enhancing the global energy efficiency of complex energy systems. Furthermore, it demonstrates the role that innovative management solutions, as those represented by the emerging VPPM opportunities, could have in making the existing energy plants active players in the future Distributed Energy Generation (DEG) scenarios.

A Partnership of Virtual Power Plant in Day-Ahead Energy and Reserve Markets Based on Linearized AC Network-Constrained Unit Commitment Model

This paper presents coordinated energy management as a virtual power plant (VPP) framework with a wind farm, a storage system, and a demand response program in the transmission network according to the cooperation of VPPs in day-ahead energy and reserve markets. This strategy is based on a bilevel method, where it maximizes the expected VPP revenue in the proposed markets subject to constraints of renewable and flexible sources and the VPP reserve model in the upper-level problem. Also, a market-clearing model based on network-constrained unit commitment (NCUC) is explained in the lower-level problem so that it minimizes the expected operating cost of generation units constrained to a linearized AC-NCUC model. The scenario-based stochastic programming (SBSP) models the uncertainties of loads and WF power generation. Then, the master/slave decomposition method solves the bilevel problem to achieve an optimal solution at a low computational time. Also, since the lower-level problem is mixed-integer linear programming, the Benders decomposition algorithm is adopted to solve this problem. Finally, the suggested approach is implemented on IEEE test networks in GAMS software, and numerical results confirm the efficiency of the coordinated VPP management in DA energy and reserve markets and its capabilities in improving network operation.

A Case Study of a Virtual Power Plant (VPP) as a Data Acquisition Tool for PV Energy Forecasting

This article describes problems related to the operation of a virtual micro power plant at the Faculty of Electrical Engineering (FEE), Czestochowa University of Technology (CUT). In the era of dynamic development of renewable energy sources, it is necessary to create alternative electricity management systems for existing power systems, including power transmission and distribution systems. Virtual power plants (VPPs) are such an alternative. So far, there has been no unified standard for a VPP operation. The article presents components that make up the VPP at the FEE and describes their physical and logical structure. The presented solution is a combination of several units operating in the internal power grid of the FEE, i.e., wind turbines, energy storage (ES), photovoltaic panels (PV) and car charging stations. Their operation is coordinated by a common control system. One of the research goals described in the article is to optimize the operation of these components to minimize consumption of the electric energy from the external supply network. An analysis of data from the VPP management system was carried out to create mathematical models for prediction of the consumed power and the power produced by the PVs. These models allowed us to achieve the assumed objective. The article also presents the VPP data processing results in terms of detecting outliers and missing values. In addition to the issues discussed above, the authors also proposed to apply the Prophet model for short-term forecasting of the PV farm electricity production. It is a statistical model that has so far been used for social and business research. The authors implemented it effectively for technical analysis purposes. It was shown that the results of the PV energy production forecasting using the Prophet model are acceptable despite occurrences of missing data in the investigated time series.

Optimal Virtual Power Plant Management for Multiple Grid Support Services

A hierarchical control architecture is proposed for the optimal day-ahead commitment of multiple grid support services within a virtual power plant (VPP). The day-ahead optimization considers pricing and cost data to determine the commitment schedule, and a robust Model Predictive Control (MPC) approach is included to minimize the unbalance fees during real-time operations. The multi-level control has been demonstrated experimentally using a hybrid test system, where the VPP is formed of a commercial 240 kW, 180 kWh battery energy storage system (BESS), while the additional assets are modelled in a real-time digital simulator (RTDS). Two case studies are analyzed: the first assumes a purely-electrical VPP, with a single connection to the public network; the second involves a multi-energy approach, with the introduction of a gas-supplied Combined Heat and Power unit (CHP). Both winter and summer price scenarios are tested. The results show the superiority of the multiple-service operation compared to providing a single grid support service. For example, the net revenue is increased by 30% (winter) and 7% (summer) when compared to just frequency regulation, and by +99% (winter) and 30% (summer) when compared to only energy arbitrage.

Virtual Power Plant Management in Smart Grids with XMPP Based IEC 61850 Communication

Communication plays a key role in the effective management of virtual power plants (VPPs). For effective and stable operation of VPPs, a reliable, secure, and standardized communication infrastructure is required. In the literature, efforts were made to develop this based on industry standards, such as the IEC 60870-5-104, OpenADR 2.0b and IEC 61850. Due to its global acceptance and strong object-oriented information models, IEC 61850 standard-based communication is preferred for smart grid operations, including VPPs. However, communication models based on IEC 61850 present cybersecurity and scalability challenges. To address this issue, this paper presents an eXtensible Message Presence Protocol (XMPP)-based IEC 61850 communication for VPPs. Firstly, a full mapping of IEC 61850 messages for VPP energy management is carried out. Secondly, XMPP-based single- and multiple-domain communications are demonstrated. Finally, a federation concept has been added to facilitate communication in multi-domain communication networks. These models show that a standard communication model can be implemented with IEC 61850 and XMPP, not only for VPPs but other wide-area communication implementations in smart grids. This not only facilitates plug-and-play (PnP) with easy component additions but secures smart grid communication against cyber-attacks.

Planning of Electric Power Systems Considering Virtual Power Plants with Dispatchable Loads Included: An Inexact Two-Stage Stochastic Linear Programming Model

In this study, an inexact two-stage stochastic linear programming (ITSLP) method is proposed for supporting sustainable management of electric power system under uncertainties. Methods of interval-parameter programming and two-stage stochastic programming were incorporated to tackle uncertainties expressed as interval values and probability distributions. The dispatchable loads are integrated into the framework of the virtual power plants, and the support vector regression technique is applied to the prediction of electricity demand. For demonstrating the effectiveness of the developed approach, ITSLP is applied to a case study of a typical planning problem of power system considering virtual power plants. The results indicate that reasonable solutions for virtual power plant management practice have been generated, which can provide strategies in mitigating pollutant emissions, reducing system costs, and improving the reliability of power supply. ITSLP is more reliable for the risk-aversive planners in handling high-variability conditions by considering peak-electricity demand and the associated recourse costs attributed to the stochastic event. The solutions will help decision makers generate alternatives in the event of the insufficient power supply and offer insight into the tradeoffs between economic and environmental objectives.

Virtual Power Plant Management considering Energy Storage Systems and Multiple Power Sources

The general strategy of CPFL - Piratininga Power and Light Company in R&D for distributed generation (DG) is making the connection to grid-connected company in DG (not diesel) in CPFL network. The CPFL started in 2002 a strategic line for studying DG and given sources for CPFL in operation, planning, market and standards in dealing with this type of incoming technology. This line also develops equipment of DG, for large-scale application. The overall goal is the CPFL be, in Brazil, the company best positioned to meet the challenges of DG and have knowledge of technologies and equipment to sell energy through DG, having as sources the sun, natural gas, ethanol, biomass etc. This process there is already a spill over, Hytron and Unitec as first industrial partners. This paper presents developments occurred until now in this project with the main CPFL guidelines for DG.

Virtual power plant management considering energy storage systems

The increasing awareness of climate change and of limited fossil resources is pushing the electric power system toward a paradigm change. Renewable Energy Sources (RES) such as wind and sun will provide a higher and higher contribution to the electric power generation. Coordinating and controlling multiple small power plants, Energy Storage Systems (ESS) and controllable loads with a central Energy Management System (EMS) make it possible to form Virtual Power Plants (VPP). In the paper will be shown how a VPP offers a solution to increase the integration of the energy produced by RES into the electric network. Especially the paper focuses on the energy storage dimensioning within a VPP structure. The sensitivity analysis shows how the power generated the RES share as well as the RES technology influence the optimal storage capacity.