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1. Evaluating Coupling Models for Cloud Datacenters and Power Grids

   https://doi.org/10.1145/3447555.3464868  

   Lin, Liuzixuan ; Zavala, Victor M. ; Chien, Andrew A. ( June 2021 , InThe TwelfthACM International Conference on Future Energy Systems (e-Energy ’21),)

   Ardakanian, Omid ; Niesse, Astrid (Ed.)

   The rapid growth of datacenter (DC) loads can be leveraged to help meet renewable portfolio standard (RPS, renewable fraction)targets in power grids. The ability to manipulate DC loads over time(shifting) provides a mechanism to deal with temporal mismatch between non-dispatchable renewable generation (e.g. wind and solar) and overall grid loads, and this flexibility ultimately facilitates the absorption of renewables and grid decarbonization. To this end, we study DC-grid coupling models, exploring their impact on grid dispatch, renewable absorption, power prices, and carbon emissions.With a detailed model of grid dispatch, generation, topology, and loads, we consider three coupling approaches: fixed, datacenter-local optimization (online dynamic programming), and grid-wide optimization (optimal power flow). Results show that understanding the effects of dynamic DC load management requires studies that model the dynamics of both load and power grid. Dynamic DC-grid coupling can produce large improvements: (1) reduce grid dispatch cost (-3%), (2) increase grid renewable fraction (+1.58%), and (3) reduce DC power cost (-16.9%).It also has negative effects: (1) increase cost for both DCs and non-DC customers, (2) differentially increase prices for non-DC customers, and (3) create large power-level changes that may harm DC productivity. 

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2. Pricing Multi-Interval Dispatch under Uncertainty Part I: Dispatch-Following Incentives

   https://doi.org/10.1109/TPWRS.2021.3055730  

   Guo, Ye ; Chen, Cong ; Tong, Lang ( January 2021 , IEEE Transactions on Power Systems)

   null (Ed.)

   Pricing multi-interval economic dispatch of electric power under operational uncertainty is considered in this two- part paper. Part I investigates dispatch-following incentives of profit-maximizing generators and shows that, under mild conditions, no uniform-pricing scheme for the rolling-window economic dispatch provides dispatch-following incentives that avoid discriminative out-of-the-market uplifts. A nonuniform pricing mechanism, referred to as the temporal locational marginal pricing (TLMP), is proposed. As an extension of the standard locational marginal pricing (LMP), TLMP takes into account both generation and ramping-induced opportunity costs. It eliminates the need for the out-of-the-market uplifts and guarantees full dispatch-following incentives regardless of the accuracy of the demand forecasts used in the dispatch. It is also shown that, under TLMP, a price-taking market participant has incentives to bid truthfully with its marginal cost of generation. Part II of the paper extends the theoretical results developed in Part I to more general network settings. It investigates a broader set of performance measures, including the incentives of the truthful revelation of ramping limits, revenue adequacy of the operator, consumer payments, generator profits, and price volatility under the rolling-window dispatch model with demand forecast errors. 

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3. Economic-Emission Dispatch Problem in Power Systems with Carbon Capture Power Plants

   https://doi.org/10.1109/tia.2021.3079329  

   Akbari-Dibavar, Alireza ; Mohammadi-ivatloo, Behnam ; Zare, Kazem ; Khalili, Tohid ; Bidram, Ali ( May 2021 , IEEE Transactions on Industry Applications)

   null (Ed.)

   Despite the increasing level of renewable power generation in power grids, fossil fuel power plants still have a significant role in producing carbon emissions. The integration of carbon capturing and storing systems to the conventional power plants can significantly reduce the spread of carbon emissions. In this paper, the economic-emission dispatch of combined renewable and coal power plants equipped with carbon capture systems is addressed in a multi-objective optimization framework. The power systems flexibility is enhanced by hydropower plants, pumped hydro storage, and demand response program. The wind generation and load consumption uncertainties are modeled using stochastic programming. The DC power flow model is implemented on a modified IEEE 24-bus test system. Solving the problem resulted in an optimal Pareto frontier, while the fuzzy decision-making method found the best solution. The sensitivity of the objective functions concerning the generation-side is also investigated. 

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4. Pricing Energy in the Presence of Renewables

   https://doi.org/10.23919/ACC.2018.8431899  

   Zeinalzadeh, Ashkan ; Ghavidel, Donya ; Gupta, Vijay ( June 2018 , 2018 Annual American Control Conference (ACC))

   The intermittent nature of renewable energy generation implies that renewable producers rely on non-renewable producers to ensure the aggregate power delivered meets the promised quality of service. Therefore, the intermittent nature of renewable energy generation affects the committed power and market price of energy. We consider an electricity market where renewable and non-renewable generators bid by proposing their asking price per unit of energy to an independent system operator (ISO). The ISO solves a dispatch optimization problem to minimize the cost of purchased energy on behalf of the consumers. We incorporate the notion of net-load variance using the Conditional Value-at-Risk (CVAR) measure in the dispatch optimization problem to ensure that the generators are able to meet the load within a desired confidence level. We analytically derive the market clearing price of energy and dispatched powers as a function of CVAR and show that a higher penetration of renewable energies may increase the market clearing price of energy. Finally, we present descriptive simulations to illustrate the impact of renewable energy penetration on the market price of energy. 

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5. Uncertainty Cost of Stochastic Producers: Metrics and Impacts on Power Grid Flexibility

   https://doi.org/10.1109/TEM.2020.2970729  

   Pourahmadi, F. ; Hosseini, S.H. ; Dehghanian, P. ; Shittu, E. ; Fotuhi-Firuzabad, M. ( February 2021 , IEEE transactions on engineering management)

   null (Ed.)

   The widespread presence of contingent generation, when coupled with the resulting volatility of the chronological net-load (i.e., the difference between stochastic generation and uncertain load) in today's modern electricity markets, engender the significant operational risks of an uncertain sufficiency of flexible energy capacity. In this article, we address several operational flexibility concerns that originate from the increase in generation variability captured within a security-constrained unit commitment (SCUC) formulation in smart grids. To quantitatively assess the power grid operational flexibility capacity, we first introduce two reference operation strategies based on a two-stage robust SCUC, one through a fixed and the other via an adjustable uncertainty set, for which the state-of-the-art techniques may not be always feasible, efficient, and practical. To address these concerns and to account for the effects of the uncertainty cost resulting from dispatch limitations of flexible resources, a new framework centered on the adjustable penetration of stochastic generation is proposed. Our hypothesis is that if the SCUC is scheduled with an appropriate dispatch level of stochastic generation, the system uncertainty cost will decrease, and subsequently, the system's ability to accommodate additional uncertainty will improve. Numerical simulations on a modified IEEE 73-bus test system verify the efficiency of the suggested assessment techniques. 

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