scholarly journals Integration of Flexibility from Distributed Energy Resources: Mapping the Innovative Italian Pilot Project UVAM

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1910
Author(s):  
Jan Schwidtal ◽  
Marco Agostini ◽  
Fabio Bignucolo ◽  
Massimiliano Coppo ◽  
Patrizia Garengo ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Electricity Market ◽  
Market Integration ◽  
Energy Transition ◽  
Pilot Project ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Distributed Resources ◽  
Fundamental Building Block

In light of the advancing energy transition and an increasing amount of intermittent renewable energy to be integrated, flexibility from distributed energy resources will be key. In this paper, the Italian UVAM (Unità Virtuali Abilitate Miste, i.e., virtually aggregated mixed units) project, one of the biggest pilots in Europe to serve this purpose, is critically reviewed and mapped after two years of operation. The pilot is analyzed on a global level as well as the individual participant level. Based on the extensive analysis of actual market data, different strategies of participating companies to obtain capacity in accordance with the pilot project’s design are identified. Furthermore, the specific bidding strategies of individual participating units on the balancing market are outlined. Alongside this, the overall pilot project’s market integration, in terms of offered and accepted bids, is depicted. The thorough data analysis, therefore, serves as an input and fundamental building block for future electricity market modeling. Comprehending specific data from the coronavirus disease 2019 (COVID-19) pandemic, provides insights for future high renewable-energy scenarios. Based on the analysis findings, valuable deliverables are devised for both policy-makers and decision-makers who aim to leverage the flexibility potential of distributed resources.

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.

Evaluation of Commercial Building Clusters With Energy Storage to Reduce Reliance on Electrical Utility Grids

2021 ◽  
Author(s):  
Gregory Kaminski ◽  
Philip Odonkor
Keyword(s):  
Energy Storage ◽  
Storage Systems ◽  
Storage System ◽  
Energy Resource ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Commercial Building ◽  
Distributed Energy ◽  
Distributed Resources ◽  
And Storage

Abstract The decreasing cost of implementation and increasing regulatory incentive to lower energy use have led to an increased adoption of distributed energy resources in recent years. This increased adoption has been further fueled by a surge in energy consciousness and the expansion of energy-saving products and technologies. To lower reliance on the electrical grid and fully realize the benefits of distributed energy resources, many consumers have also elected to use battery systems to store generated energy. For owners of multiple buildings, or multiple owners willing to share the operational cost, building clusters may be formed to more effectively take advantage of these distributed resources and storage systems. The implementation of these systems in existing buildings introduces the question of what makes a “good” building cluster. Furthermore, the scalable nature of distributed energy sources and storage systems create countless possibilities for system configuration. Through comparison of unique two-building clusters from a stock of five buildings with a given distributed energy resource (in this case, a solar photovoltaic panel array) and energy storage system, we develop a fundamental understanding of the underlying factors that allow building clusters to be less reliant on the utility grid and make better use of energy generation and storage systems.

Design of an Agent-Based Technique for Controlling Interconnected Distributed Energy Resource Transactions

2017 ◽  
Author(s):  
Samantha Janko ◽  
Nathan G. Johnson
Keyword(s):  
Electricity Market ◽  
Energy Resource ◽  
Electric Utility ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Electrical Network ◽  
Distributed Energy ◽  
Agent Based ◽  
Electricity Cost ◽  
Distributed Energy Resource

Electricity has traditionally been a commodity that is bought and sold through a rigid marketplace between an electric utility and a ratepayer. Today, however, the electricity market is rapidly evolving to be comprised of distributed energy resources and microgrids that change the structure of the technical and financial relationship between utilities and ratepayers. Regulation, a reduction in cost of renewable energy technologies, interoperability and improved communications, and public interest in green power are facilitating this transition. Microgrids require an additional layer of control, often use preprogrammed rule sets, and lack bi-directional self-awareness, self-management, and self-diagnostics necessary to dynamically adapt to changes on-site and in the grid. Research is needed in optimization and controls. This study explores the viability of self-organizing control algorithms to manage multiple distributed energy resources within a distribution network and reduce electricity cost to one or more ratepayers having such resources installed on-site. Such research provides insight into the transition from a traditional power distribution architecture into a flexible smart network that is better prepared for future technological advances, renewables integration, and customer-side control. Agent-based techniques are employed for least-cost optimization and implements these to manage transactions between three decentralized distributed energy resource systems within an electrical network.

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