Decentralized Optimal Control of a Microgrid with Solar PV, BESS and Thermostatically Controlled Loads

Zhuo, Wenhao; Savkin, Andrey V.; Meng, Ke

doi:10.3390/en12112111

Cited by 19 publications

(18 citation statements)

References 19 publications

(49 reference statements)

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“…The deployment of DGs may also provide a wide range of technical benefits if their size, location, and operation are properly optimized [70]. Furthermore, DGs may contribute to network losses reduction if installed close to the load centers [89][90][91][92][93], improve voltage profile as reported in References [94][95][96][97], enhance systems' reliability [98][99][100], and provide computational flexibility for system controllability especially pertaining to generation [101][102][103] and demand-side management [104][105][106].…”

Section: Distributed Generationmentioning

confidence: 99%

A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources

et al. 2020

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The smart grid is an unprecedented opportunity to shift the current energy industry into a new era of a modernized network where the power generation, transmission, and distribution are intelligently, responsively, and cooperatively managed through a bi-directional automation system. Although the domains of smart grid applications and technologies vary in functions and forms, they generally share common potentials such as intelligent energy curtailment, efficient integration of Demand Response, Distributed Renewable Generation, and Energy Storage. This paper presents a comprehensive review categorically on the recent advances and previous research developments of the smart grid paradigm over the last two decades. The main intent of the study is to provide an application-focused survey where every category and sub-category herein are thoroughly and independently investigated. The preamble of the paper highlights the concept and the structure of the smart grids. The work presented intensively and extensively reviews the recent advances on the energy data management in smart grids, pricing modalities in a modernized power grid, and the predominant components of the smart grid. The paper thoroughly enumerates the recent advances in the area of network reliability. On the other hand, the reliance on smart cities on advanced communication infrastructure promotes more concerns regarding data integrity. Therefore, the paper dedicates a sub-section to highlight the challenges and the state-of-the-art of cybersecurity. Furthermore, highlighting the emerging developments in the pricing mechanisms concludes the review.

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Section: Distributed Generationmentioning

confidence: 99%

A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources

et al. 2020

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“…Given proper control of storage units and communications with the electricity market, the non-dispatchable renewable power can be smoothed and used on demand, therefore reducing the difficulty of power scheduling in the main grid operation [3]. In many studies that focus on the control of renewable power systems [4][5][6][7][8][9][10][11][12][13][14][15], the battery energy storage system (BESS) is essential for controlling the actual power dispatched to the local customers and the grid. Utilizing forecasting data on renewable power and power demand to arrange BESS actions over different periods, the power constraints in the microgrid and the operating parameters in the main grid can be satisfied.…”

Section: Motivationsmentioning

confidence: 99%

“…Many control strategies and optimization methods, including model predictive control (MPC) [5,8,14,15], dynamic programming (DP) [3,4,7,16], sliding mode control (SMC) [17,18], reinforcement learning (RL) [9,10], particle swarm optimization (PSO) [11,[19][20][21], and mixed-integer linear programming (MILP) [6,13,15], have been proposed for renewable power control under different conditions. The use of MPC is mainly due to forecasting errors.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The number of charge-discharge cycles that the battery can experience will be counted, and the effects of stress factors, such as temperature, depth of discharge (DOD), average state of charge (SOC), and operating currents on the rate of life cycle loss can be investigated. It should be pointed out that most of the cost models of BESS in previously reviewed studies are either not considered [3,[5][6][7][8][9][10][14][15][16] in the optimization problem, or simple models that without consideration on the cycling model under different stress factors [4,11,13].…”

Section: Literature Reviewmentioning

confidence: 99%

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Profit Maximizing Control of a Microgrid with Renewable Generation and BESS Based on a Battery Cycle Life Model and Energy Price Forecasting

Zhuo

Savkin

2019

Energies

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In this paper, an optimal control strategy is presented for grid-connected microgrids with renewable generation and battery energy storage systems (BESSs). In order to optimize the energy cost, the proposed approach utilizes predicted data on renewable power, electricity price, and load demand within a future period, and determines the appropriate actions of BESSs to control the actual power dispatched to the utility grid. We formulate the optimization problem as a Markov decision process and solve it with a dynamic programming algorithm under the receding horizon approach. The main contribution in this paper is a novel cost model of batteries derived from their life cycle model, which correlates the charge/discharge actions of batteries with the cost of battery life loss. Most cost models of batteries are constructed based on identifying charge–discharge cycles of batteries on different operating conditions, and the cycle counting methods used are analytical, so cannot be expressed mathematically and used in an optimization problem. As a result, the cost model proposed in this paper is a recursive and additive function over control steps that will be compatible with dynamic programming and can be included in the objective function. We test the proposed approach with actual data from a wind farm and an energy market operator.

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“…In the centralized microgrid control, the central control unit coordinates the microgrid control and protection functions by sending operating commands to the local control units and circuit breakers [8,9]. In the decentralized microgrid control structures, each component is independently controlled by its local control unit, and does not coordinate with other local control units [10,11]. Typically, due to the widespread topology of power system networks and electrical coupling between power system components, microgrid implementations are a combination of centralized and decentralized control structures.…”

Section: Introductionmentioning

confidence: 99%

Real Time-Based under Frequency Control and Energy Management of Microgrids

2020

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In this paper, an efficient under frequency control and the energy management of a distributed energy resources (DERs)-based microgrid is presented. The microgrid is composed of a photovoltaic (PV), double-fed induction generator (DFIG)-based wind and diesel generator with critical and non-critical loads. The system model and the control strategy are developed in a real time digital simulator (RTDS). The coordination and power management of the DERs in both grid-connected and islanded operation modes are implemented. During power imbalances and frequency fluctuations caused by fault or islanding, an advanced automatic load shedding control is implemented to regulate and maintain the microgrid frequency at its rated value. One distinct feature implemented for the load shedding operation is that highly unbalanced critical loads are connected to the microgrid. The diesel generator provides the required inertia in the islanded mode to maintain the microgrid rated frequency by operating in the isochronous mode. The International Council on Large Electric Systems (CIGRE) medium voltage (MV) test bench system is used to implement the DERs and their controller. The proposed control approach has potential applications for the complete operation of microgrids by properly controlling the power, voltage and frequency in both grid-connected and island modes. The real time digital simulator results verify the effectiveness and superiority of the proposed control scheme in grid connected, island and fault conditions.

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Decentralized Optimal Control of a Microgrid with Solar PV, BESS and Thermostatically Controlled Loads

Cited by 19 publications

References 19 publications

A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources

A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources

Profit Maximizing Control of a Microgrid with Renewable Generation and BESS Based on a Battery Cycle Life Model and Energy Price Forecasting

Real Time-Based under Frequency Control and Energy Management of Microgrids

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