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Energy Performance Analysis of Distributed Renewables: Pacific Northwest Smart Grid Demonstration

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 Publication date 2021
and research's language is English




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The Pacific Northwest Smart Grid Demonstration was an electricity grid modernization project conducted in the Northwest U.S. This paper presents the analysis of renewable generation at the Renewable Energy Park located in the City of Ellensburg, WA. The community energy park concept is an intriguing model for community investment in renewable resources,but the lessons in this paper should be considered.



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Electric vehicles (EVs) are an eco-friendly alternative to vehicles with internal combustion engines. Despite their environmental benefits, the massive electricity demand imposed by the anticipated proliferation of EVs could jeopardize the secure and economic operation of the power grid. Hence, proper strategies for charging coordination will be indispensable to the future power grid. Coordinated EV charging schemes can be implemented as centralized, decentralized, and hierarchical systems, with the last two, referred to as distributed charging control systems. This paper reviews the recent literature of distributed charging control schemes, where the computations are distributed across multiple EVs and/or aggregators. First, we categorize optimization problems for EV charging in terms of operational aspects and cost aspects. Then under each category, we provide a comprehensive discussion on algorithms for distributed EV charge scheduling, considering the perspectives of the grid operator, the aggregator, and the EV user. We also discuss how certain algorithms proposed in the literature cope with various uncertainties inherent to distributed EV charging control problems. Finally, we outline several research directions that require further attention.
Frequency fluctuations in power grids, caused by unpredictable renewable energy sources, consumer behavior and trading, need to be balanced to ensure stable grid operation. Standard smart grid solutions to mitigate large frequency excursions are based on centrally collecting data and give rise to security and privacy concerns. Furthermore, control of fluctuations is often tested by employing Gaussian perturbations. Here, we demonstrate that power grid frequency fluctuations are in general non-Gaussian, implying that large excursions are more likely than expected based on Gaussian modeling. We consider real power grid frequency measurements from Continental Europe and compare them to stochastic models and predictions based on Fokker-Planck equations. Furthermore, we review a decentral smart grid control scheme to limit these fluctuations. In particular, we derive a scaling law of how decentralized control actions reduce the magnitude of frequency fluctuations and demonstrate the power of these theoretical predictions using a test grid. Overall, we find that decentral smart grid control may reduce grid frequency excursions due to both Gaussian and non-Gaussian power fluctuations and thus offers an alternative pathway for mitigating fluctuation-induced risks.
This paper proposes a distributed framework for vehicle grid integration (VGI) taking into account the communication and physical networks. To this end, we model the electric vehicle (EV) behaviour that includes time of departure, time of arrival, state of charge, required energy, and its objectives, e.g., avoid battery degradation. Next, we formulate the centralised day ahead distribution market (DADM) which explicitly represents the physical system, supports unbalanced three phase networks with delta and wye connections, and incorporates the charging needs of EVs. The solution of the centralised market requires knowledge of EV information in terms of desired energy, departure and arrival times that EV owners are reluctant in providing. Moreover, the computational effort required to solve the DADM in cases of numerous EVs is very intensive. As such, we propose a distributed solution of the DADM clearing mechanism over a time-varying communication network. We illustrate the proposed VGI framework through the 13-bus, 33- bus, and 141-bus distribution feeders.
The deployment of distributed photovoltaics (PV) in low-voltage networks may cause technical issues such as voltage rises, line ampacity violations, and transformer overloading for distribution system operators (DSOs). These problems may induce high grid reinforcement costs. In this work, we assume the DSO can control each prosumers battery and PV system. Under such assumptions, we evaluate the cost of providing flexibility and compare it with grid reinforcement costs. Our results highlight that using distributed flexibility is more profitable than reinforcing a low-voltage network until the PV generation covers 145% of the network annual energy demand.
Having sufficient grid-forming sources is one of the necessary conditions to guarantee the stability in a power system hosting a very large share of inverter-based generation. The grid-forming function has been historically fulfilled by synchronous machines. However, with the appropriate control, it can also be provided by voltage source converters (VSC). This work presents a comparison between two technologies with grid-forming capability: the VSC with a grid-forming control coupled with an adequate energy storage system, and the synchronous condensers (SC). Both devices are compared regarding their inertial response, as well as their contribution to the system strength and short-circuit current for an equivalent capacity expressed in terms of apparent power and inertial reserve. Their behaviour following grid disturbances is assessed through time-domain simulations based on detailed electromagnetic transient (EMT) models. The results show that both devices achieve similar performance in the time-scale of seconds. For shorter time-windows, however, they present a different behavior: the SC ensures a better stiffness in the first tens of ms following the disturbance, while the VSC offers a faster resynchronization.
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