scholarly journals Characterizing the Effect of Conservation Voltage Reduction on the Hosting Capacity of Inverter-Based Distributed Energy Resources

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1517
Author(s):  
Alexandre B. Nassif ◽  
Ming Dong

The increased adoption of inverter-based distributed energy resources in the form of the mass deployment of renewable generation systems has been a focal goal of many jurisdictions worldwide. Actions taken by local governments have included adapted regulations, financial subsidies, and a variety of grants. This has spurred the proliferation of solar generation among residential customers in virtually all provinces of the United States and Canada. Needless to say, these small generators are interfaced with DC–AC inverters, which have evolved tremendously since the formation of working groups targeting the impact of inverter-based generation on the grid. Among the first rules and standards are California’s ISO Rule 21 and the UL1741 SA, which were published in September 2017. IEEE followed suit in 2018 with the revision of IEEE 1547, inspiring virtually all jurisdictions to either adopt these standards or adapt them as their own variants. Among many features, these standards mandate inverters to be fitted with autonomous performance functions, including the constant power factor, voltage-reactive power (Volt-VAR), voltage-active power (Volt-Watt), and grid support functions, as well as provisions for compatibility with control centers. These functions have been demonstrated to increase the nameplate hosting capacity. At the same time, grid modernization strategies have become more prevalent, one of which is the use of conservation voltage reduction. This grid modernization initiative has a great impact on the hosting capacity. Conversely, the increased penetration of distributed energy resources has a negative effect on the conservation voltage reduction, but surprisingly to only a limited extent. The characterization of these impacts is addressed in this paper, with a focus on a case with very high DER penetration and with very long daily sunlight hours.

2021 ◽  
Vol 13 (13) ◽  
pp. 7119
Author(s):  
Abbas Rabiee ◽  
Ali Abdali ◽  
Seyed Masoud Mohseni-Bonab ◽  
Mohsen Hazrati

In this paper, a robust scheduling model is proposed for combined heat and power (CHP)-based microgrids using information gap decision theory (IGDT). The microgrid under study consists of conventional power generation as well as boiler units, fuel cells, CHPs, wind turbines, solar PVs, heat storage units, and battery energy storage systems (BESS) as the set of distributed energy resources (DERs). Additionally, a demand response program (DRP) model is considered which has a successful performance in the microgrid hourly scheduling. One of the goals of CHP-based microgrid scheduling is to provide both thermal and electrical energy demands of the consumers. Additionally, the other objective is to benefit from the revenues obtained by selling the surplus electricity to the main grid during the high energy price intervals or purchasing it from the grid when the price of electricity is low at the electric market. Hence, in this paper, a robust scheduling approach is developed with the aim of maximizing the total profit of different energy suppliers in the entire scheduling horizon. The employed IGDT technique aims to handle the impact of uncertainties in the power output of wind and solar PV units on the overall profit.


Author(s):  
Monika Gaba ◽  
Saurabh Chanana

Abstract Demand response (DR), an integral part of the smart grid, has great potential in handling the challenges of the existing power grid. The potential of different DR programs in the energy management of residential consumers (RCs) and the integration of distributed energy resources (DERs) is an important research topic. A novel distributed approach for energy management of RCs considering the competitive interactions among them is presented in this paper. The impact of participation of RC’s in price-based (PB) and incentive-based (IB) DR programs is investigated using game theory. For this, an energy management optimization problem (EMOP) is formulated to minimize electricity cost. The utility company employs electricity price as a linear function of aggregated load in the PB DR program and an incentive rate in the IBDR program. RCs are categorized into active and passive users. Active users are further distinguished based on the ownership of energy storage devices (SD) and dispatchable generation units (DGU). EMOP is modeled using a non-cooperative game, and the distributed proximal decomposition method is used to obtain the Nash equilibrium of the game. The results of the proposed approach are analyzed using different case studies. The performance of the proposed approach is evaluated in terms of aggregated cost and system load profile. It has been observed that participation in PB and IBDR program benefits both the utility and the consumers.


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