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Guaranteeing Service in Connected Microgrids: Storage Planning and Optimal Power Sharing Policy

Arnab Dey, Vivek Khatana, Ankur Mani, Murti V. Salapaka

Abstract

The integration of renewable energy sources (RES) into power distribution grids poses challenges to system reliability due to the inherent uncertainty in their power production. To address this issue, battery energy sources (BESs) are being increasingly used as a promising solution to counter the uncertainty associated with RES power production. During the overall system planning stage, the optimal capacity of the BES has to be decided. In the operational phase, policies on when to charge the BESs and when to use them to support loads must be determined so that the BES remains within its operating range, avoiding depletion of charge on one hand and remaining within acceptable margins of maximum charge on the other. In this paper, a stochastic control framework is used to determine battery capacity, for microgrids, which ensures that during the operational phase, BESs' operating range is respected with pre-specified high probability. We provide an explicit analytical expression of the required BESs energy capacity for a single microgrid with RES as the main power source. Leveraging insights from the single microgrid case, the article focuses on the design and planning of BESs for the two-microgrid scenario. In this setting, microgrids are allowed to share power while respecting the capacity constraints imposed by the power lines. We characterize the optimal power transfer policy between the microgrids and the optimal BES capacity for multiple microgrids. This provides the BES savings arising from connecting the microgrids.

Guaranteeing Service in Connected Microgrids: Storage Planning and Optimal Power Sharing Policy

Abstract

The integration of renewable energy sources (RES) into power distribution grids poses challenges to system reliability due to the inherent uncertainty in their power production. To address this issue, battery energy sources (BESs) are being increasingly used as a promising solution to counter the uncertainty associated with RES power production. During the overall system planning stage, the optimal capacity of the BES has to be decided. In the operational phase, policies on when to charge the BESs and when to use them to support loads must be determined so that the BES remains within its operating range, avoiding depletion of charge on one hand and remaining within acceptable margins of maximum charge on the other. In this paper, a stochastic control framework is used to determine battery capacity, for microgrids, which ensures that during the operational phase, BESs' operating range is respected with pre-specified high probability. We provide an explicit analytical expression of the required BESs energy capacity for a single microgrid with RES as the main power source. Leveraging insights from the single microgrid case, the article focuses on the design and planning of BESs for the two-microgrid scenario. In this setting, microgrids are allowed to share power while respecting the capacity constraints imposed by the power lines. We characterize the optimal power transfer policy between the microgrids and the optimal BES capacity for multiple microgrids. This provides the BES savings arising from connecting the microgrids.
Paper Structure (18 sections, 4 theorems, 67 equations, 5 figures)

This paper contains 18 sections, 4 theorems, 67 equations, 5 figures.

Table of Contents

  1. Introduction
  2. System Description
  3. Problem Formulation
  4. Solution Methodology
  5. Analysis of the chance constraint
  6. Battery Capacity Determination
  7. Optimality gap
  8. Battery Sizing and Power Sharing Policy for Connected multi-microgrids
  9. Problem formulation
  10. Solution methodology
  11. Power Transfer Policy Determination
  12. Battery Capacity Determination
  13. Experimental Results
  14. Conclusion
  15. Proof of Lemma \ref{['lem:gaussian_tail_bound']}
  16. ...and 3 more sections

Key Result

Lemma 1

Let where $\alpha \in [0,1]$ and $N\geq 0$. Then, we have, for all $N$ and $\alpha$.

Figures (5)

  • Figure 1: Microgrid architecture
  • Figure 2: Connected two microgrid architecture
  • Figure 3: (a) Wind, load variation, and GFM battery power for $5$ hours in real-time in the IEEE-$33$ bus single MG system. (b) The battery does not get fully charged or get depleted throughout the time horizon.
  • Figure 4: Two MG system: Battery capacity of each MG is $10$ kWh with a power line capacity of $15$ kW. Out of $5000$ realizations of the available energy in the batteries of MG-1 and MG-2, only 0.4% realizations, hits either the upper limit of $10$ kWh or the lower limit of $0$ kWh.
  • Figure 5: Required BES capacity for each MG decreases, under the optimal power transfer control policy, as power line capacity increases.

Theorems & Definitions (8)

  • Lemma 1
  • proof
  • Theorem 1
  • proof
  • Theorem 2
  • proof
  • Proposition 1
  • proof