Stochastic Optimization of Microgrids With Hybrid Energy Storage Systems for Grid Flexibility Services Considering Energy Forecast Uncertainties

García-Torres, Félix; Bordons, Carlos; Tobajas, Javier; Real-Calvo, Rafael; Santiago, I.; Grieu, Stéphane

doi:10.1109/tpwrs.2021.3071867

Cited by 87 publications

(34 citation statements)

References 25 publications

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“…Hence, it can be easily scaled to a larger problem without impacting the computation time. The computation time of the proposed algorithm for OPF is comparable to the algorithms proposed in [21], [22]. The authors of [21] have implemented the algorithm for a 37-bus distribution network, which takes approximately 5 seconds.…”

Section: A Reserve Sharing Comparative Analysismentioning

confidence: 91%

“…The authors of [21] have implemented the algorithm for a 37-bus distribution network, which takes approximately 5 seconds. The authors of [22] have implemented the algorithm for a microgrid, and takes approximately 10-15 seconds. However, improvement in the computation time and its comparison is not the goal of this work.…”

Section: A Reserve Sharing Comparative Analysismentioning

confidence: 99%

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Three-stage Power Flow & Flexibility Reserve Co-Optimization for Converter Dominated Distribution Network Lookahead Model using Blockchain & S-ADMM — II: Case Study

Shah¹,

Wies²

2022

Preprint

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<p>In Part I of this work, we presented a three-stage framework for solving stochastic non-convex optimal power flow problems using a parameterized deterministic look-ahead policy and minimizing the cost of scheduling flexibility reserves using blockchain and smart contracts. Here, in Part II, a case study with two balancing authority (BA) areas is presented to show the effectiveness of the proposed algorithm. The BA area is modeled by the collection of generation, transmission, and distribution networks. Next, the reserve sharing strategy between two or more BA areas is presented to collectively maintain and supply the flexibility reserves. The reserve sharing will help reduce the total flexibility reserve scheduling costs in the BA areas. And finally, the advantage of updating the flexibility reserve schedule at each time step using a smart contract, by tabulating the flexibility metrics “variation in generation capacity (VIGC)” and uncertainty quantification of epistemic and aleatory uncertainties in variable distributed energy resources (DERs) generation and loads, is also presented.</p>

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Section: A Reserve Sharing Comparative Analysismentioning

confidence: 91%

Section: A Reserve Sharing Comparative Analysismentioning

confidence: 99%

Three-stage Power Flow & Flexibility Reserve Co-Optimization for Converter Dominated Distribution Network Lookahead Model using Blockchain & S-ADMM — II: Case Study

Shah¹,

Wies²

2022

Preprint

View full text Add to dashboard Cite

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“…Dynamic pricing plans are discussed in [33]. The paper [34] describes a stochastic optimization framework for microgrids providing flexible services to System Operators (SOs), which includes energy and battery degradation costs during flexible service operations. The paper [35] proposes a two-variable energy management model for energy overall consumption improvement.…”

Section: Literature Reviewmentioning

confidence: 99%

Flower Greenhouse Energy Management to Offer Local Flexibility Markets

et al. 2022

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Electricity access is strongly linked to human growth. Despite this, a portion of the world’s population remains without access to energy. In Colombia, rural communities have energy challenges due to the National Interconnected System’s (NIS) lack of quality and stability. It is common to find that energy services in such locations are twice as costly as in cities and are only accessible for a few hours every day due to grid overload. Implementing market mechanisms that enable handling imbalances through the flexible load management of main loads within the grid is vital for improving the rural power grid’s quality. In this research, the energy from the rural grid is primarily employed to power a heating, ventilation, and air-conditioning (HVAC) system that chills flowers for future commerce. This load has significant consumption within the rural grid, so handling HVAC consumption in a suitable form can support the grid to avoid imbalances and improve the end-user access to energy. The primary responsibilities of the flower greenhouse operator are to reduce energy costs, maximize flexibility, and maintain a proper indoor temperature. Accordingly, this research proposes a flexible energy market based on the bi-level mixed-integer linear programming problem (Bi-MILP), involving the Agricultural Demand Response Aggregator (ADRA) and the flower greenhouse. ADRA is responsible for assuring the grid’s stability and quality and developing pricing plans that promote flexibility. A flower greenhouse in Colombia’s Boyacá department is used as an application for this research. This study looked at the HVAC’s flexibility under three different pricing schemes (fixed, time-of-use, and hourly) and graded the flower greenhouse’s flexibility as a reliable system.

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“…The more interesting comparison is with the worst-case feasible market clearing outcome when there is sufficient liquidity in the whole network, but insufficient liquidity per node (3). Thus, the flexibility may not be provided at the same node, and the additional loading may result in congestion or voltage limit violations.…”

Section: E Upper Bound On Sub-optimality Gapmentioning

confidence: 99%

Network-Aware Flexibility Requests for Distribution-Level Flexibility Markets

Prat¹,

Dukovska²,

Nellikkath³

et al. 2021

Preprint

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Local flexibility markets will become a central tool for distribution system operators (DSOs), who need to ensure a safe grid operation against increased costs and public opposition for new network investments. Despite extended recent literature on local flexibility markets, little attention has been paid on how to determine the flexibility request that the DSOs shall submit to such markets. Considering the constraints that the network introduces (e.g. line and voltage limits), so far it has been unclear how the DSO shall determine how much flexibility it requires and at which network locations. Addressing an open question for several DSOs, this paper introduces a method to design network-aware flexibility requests from a DSO perspective. We consider uncertainty, which could be the result of fluctuating renewable production or demand, and we compare our approach against a stochastic market clearing mechanism, which serves as a benchmark, deriving analytical conditions for their performance. We demonstrate our methods on a real German distribution grid.

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Stochastic Optimization of Microgrids With Hybrid Energy Storage Systems for Grid Flexibility Services Considering Energy Forecast Uncertainties

Cited by 87 publications

References 25 publications

Three-stage Power Flow & Flexibility Reserve Co-Optimization for Converter Dominated Distribution Network Lookahead Model using Blockchain & S-ADMM — II: Case Study

Three-stage Power Flow & Flexibility Reserve Co-Optimization for Converter Dominated Distribution Network Lookahead Model using Blockchain & S-ADMM — II: Case Study

Flower Greenhouse Energy Management to Offer Local Flexibility Markets

Network-Aware Flexibility Requests for Distribution-Level Flexibility Markets

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