Optimal Planning of Microgrid-Integrated Battery Energy Storage

Battery energy storage (BES) is a core component in reliable, resilient, and cost-effective operation of microgrids. When appropriately sized, BES can provide the microgrid with both economic and technical benefits. Besides the BES size, it is found that there are mainly three planning parameters that impact the BES performance, including the BES integration configuration, technology, and depth of discharge. In this dissertation, the impact of each one of these parameters on the microgrid-integrated BES planning problem is investigated. Three microgrid-integrated BES planning models are developed to individually find the optimal values for the aforementioned parameters. These three microgrid-integrated BES planning models are then combined and extended, by including the impact of microgrid islanding incidents on the BES planning solution, to develop a comprehensive planning model that can be used by microgrid planners to simultaneously determine the installed BES optimal size, integration configuration, technology, and maximum depth of discharge. Besides applications in microgrids, this dissertation investigates the integration of BES to provide other types of support in distribution networks such as load management of commercial and industrial customers, distribution network expansion, and solar PV ramp rate control

Control and Stability of Residential Microgrid with Grid-Forming Prosumers

The rise of the prosumers (producers-consumers), residential customers equipped with behind-the-meter distributed energy resources (DER), such as battery storage and rooftop solar PV, offers an opportunity to use prosumer-owned DER innovatively. The thesis rests on the premise that prosumers equipped with grid-forming inverters can not only provide inertia to improve the frequency performance of the bulk grid but also support islanded operation of residential microgrids (low-voltage distribution feeder operated in an islanded mode), which can improve distribution grids’ resilience and reliability without purposely designing low-voltage (LV) distribution feeders as microgrids. Today, grid-following control is predominantly used to control prosumer DER, by which the prosumers behave as controlled current sources. These grid-following prosumers deliver active and reactive power by staying synchronized with the existing grid. However, they cannot operate if disconnected from the main grid due to the lack of voltage reference. This gives rise to the increasing interest in the use of grid-forming power converters, by which the prosumers behave as voltage sources. Grid-forming converters regulate their output voltage according to the reference of their own and exhibit load sharing with other prosumers even in islanded operation. Making use of grid-forming prosumers opens up opportunities to improve distribution grids’ resilience and enhance the genuine inertia of highly renewable-penetrated power systems. Firstly, electricity networks in many regional communities are prone to frequent power outages. Instead of purposely designing the community as a microgrid with dedicated grid-forming equipment, the LV feeder can be turned into a residential microgrid with multiple paralleled grid-forming prosumers. In this case, the LV feeder can operate in both grid-connected and islanded modes. Secondly, gridforming prosumers in the residential microgrid behave as voltage sources that respond naturally to the varying loads in the system. This is much like synchronous machines extracting kinetic energy from rotating masses. “Genuine” system inertia is thus enhanced, which is fundamentally different from the “emulated” inertia by fast frequency response (FFR) from grid-following converters. Against this backdrop, this thesis mainly focuses on two aspects. The first is the small-signal stability of such residential microgrids. In particular, the impact of the increasing number of grid-forming prosumers is studied based on the linearised model. The impact of the various dynamic response of primary sources is also investigated. The second is the control of the grid-forming prosumers aiming to provide sufficient inertia for the system. The control is focused on both the inverters and the DC-stage converters. Specifically, the thesis proposes an advanced controller for the DC-stage converters based on active disturbance rejection control (ADRC), which observes and rejects the “total disturbance” of the system, thereby enhancing the inertial response provided by prosumer DER. In addition, to make better use of the energy from prosumer-owned DER, an adaptive droop controller based on a piecewise power function is proposed, which ensures that residential ESS provide little power in the steady state while supplying sufficient power to cater for the demand variation during the transient state. Proposed strategies are verified by time-domain simulations

Self-healing distribution expansion planning considering distributed energy resources, electric vehicles parking lots and energy storage systems

This paper addresses an iterative optimization model for self-healing distribution expansion planning considering distributed energy resources, electric vehicles' parking lots, and energy storage systems. The main contribution of this model is that the smart devices of smart homes are modeled and the impacts of their commitments are explored in the expansion planning exercise. The proposed algorithm is another contribution of this paper that consists of tri-stage optimization processes. In the first stage, the optimal commitment of smart devices of smart homes is solved considering the worst-case external shock impacts on the consumers' comfort levels. Then, the optimal expansion planning of the distribution system is determined in the second stage problem. Finally, in the third stage, the optimal topology and dispatch of distributed energy resources are determined for the external shock conditions. The effectiveness of the proposed algorithm was assessed for the modified 123-bus system. Based on the simulation results, the aggregated costs of the 123-bus system were reduced by about 42.62 % using the proposed framework. Further, the expected energy not supplied costs of the system were reduced from 113 million monetary units to 0.284 million monetary units based on the fact that the model endeavored to minimize the interruption of critical loads.© 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)fi=vertaisarvioitu|en=peerReviewed

Dynamic and multi-stage capacity expansion planning in microgrid integrated with electric vehicle charging station

This paper investigates the long-term dynamic capacity expansion planning in the microgrids. The microgrid is supplied by various capacity resources including wind, solar, micro gas turbine, and energy storage system. The microgrid also supplies an electric vehicle charging station. The electric vehicles in the charging station work as vehicle-to-grid and they are able to send energy to the microgrid or regulate their charging time and rate. As a result, the charging station may appear as a flexible load or generating unit. The capacity expansion planning in the microgrid is performed to expand the capacity of micro turbine, solar panels, wind turbine, and battery energy storage system. This capacity expansion is performed for six-years planning horizon through long term plan. The short-term plan is simultaneously conducted to optimize the hourly operation of micro turbine, energy storage system, and electric vehicle charging station. Short-term operation of dispatchable resources reduces the planning cost to 28% and properly contributions to the long-term plan for minimizing the costs. The largest expansion is performed on wind system by 200% expansion that covers about 53% of the expansion cost. The model also needs further resources when facing the uncertainties and such reinforcement increases the cost by about 58%. 2020 Elsevier LtdScopus2-s2.0-8508157939

A Resilient and Optimal Microgrid Scheduling Portfolio in Linear Programming Platform

In recent year, alarming rate of natural disasters around the world have demanded the need for operative solution in field of power generation, to control polluted energy sources which are major cause of global warming. Microgrid facilitates penetration of renewable energy sources into the existing distribution systems to reduce the overall carbon footprint of the globe by reducing the dependency on the main grid. Efficient but linear microgrid resource scheduling algorithms are gaining interest in present time due to its simplicity and fast computation. This research paper aims to serve the purposes by designing a mixed integer linear programming based microgrid scheduling problem while various types of scenario, minimize the electricity cost for the utilities also maintain the generation and load balance. The strategy is implemented on a small microgrid  to prove its efficacy .In this paper mainly optimal scheduling of microgrid has been done in various scenario, and obtained there global minimum electricity cost to the help of mixed integer linear programming (MILP) algorithm.  Microgrid is a small scale type of power grid, which provides the energy locally, its offers integration between distributed energy resources and the locally connected loads. Microgrid able to be operated with the main grid and in standalone mode also ability to transitions between these two modes, the mode of operation of microgrid is depends on the system operating condition. The reliability of power grid is improving more when it’s integrated with the Microgrid and works together. Power exchange with the upper stream grid is done through the point of common coupling (PCC). Microgrid having renewable energy resources i.e. PV, Wind and non-renewable energy resources, DG, FC, and MC connected with the Battery storage type system and locally connected loads. So it is a very reliable scenario, main grid with the microgrid, it is more beneficial, economy and stable types of system. Keywords: Optimal Microgrid Scheduling, Linear Programming DOI: 10.7176/APTA/76-05 Publication date:March 31st 2019

Impact of Electric Vehicle Charging Strategy on the Long-Term Planning of an Isolated Microgrid

[EN] Isolated microgrids, such as islands, rely on fossil fuels for electricity generation and include vehicle fleets, which poses significant environmental challenges. To address this, distributed energy resources based on renewable energy and electric vehicles (EVs) have been deployed in several places. However, they present operational and planning concerns. Hence, the aim of this paper is to propose a two-level microgrid problem. The first problem considers an EV charging strategy that minimizes charging costs and maximizes the renewable energy use. The second level evaluates the impact of this charging strategy on the power generation planning of Santa Cruz Island, Galapagos, Ecuador. This planning model is simulated in HOMER Energy. The results demonstrate the economic and environmental benefits of investing in additional photovoltaic (PV) generation and in the EV charging strategy. 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