Optimal day-ahead operational planning of microgrids

Hosseinnezhad, Vahid; Rafiee, Mansour; Ahmadian, Mohammad Taghi; Siano, Pierluigi

doi:10.1016/j.enconman.2016.07.076

Cited by 29 publications

(27 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Selected key contributions. [48] 2012-09-28 Integration of dynamic topology option into economic microgrid operation [49] 2014-04-09 Optimal scheduling of DER considering the risk of outages [27] 2014-09-26 Interaction of microgrids with and without independent islanding capabilities [50] 2016-06-13 Value of reconfigurable microgrids in integrating Electric Vehicles (EVs) [20] 2016-08-10 Resilient scheduling of microgrids affected by uncertainty [51] 2016-08-26 Multi-objective scheduling of microgrids considering normal operation costs and the risk of load curtailment [52] 2016-10-15 Microgrid scheduling considering operating costs, emissions, and reserve requirements [53] 2017-08-17 Robust formulation of the optimal proactive scheduling problem for microgrids [28] 2017-12-13 Risk-based strategies for multi-microgrid scheduling considering stochastic RESs [54] 2018-02-16 Optimal scheduling for hybrid AC/DC multi-microgrids [55] 2018-02-20 Integration of Demand Response (DR) programs and grid reconfiguration into microgrid asset scheduling [56] 2018-03-26 Resilient asset scheduling in reconfigurable microgrids [57] 2018-05-11 Security-constrained dispatch for microgrids using multi-objective optimization [58] 2018-08-17 Resiliency enhancements by optional scheduling of networked microgrids [59] 2018-12-28 Impact of scheduling discrepancies on interconnected microgrids [60] 2019-04-18 Microgrid scheduling combining flexible time frame DER scheduling and single time interval-based optimal dispatch [61] 2019-07-02 Resilient scheduling of networked multi-microgrids using a three-stage approach [62] 2019-08-07 Proactive, resilient scheduling of interconnected microgrids [63] 2019-08-16 Distributed energy management of interconnected microgrids considering adversarial actions [64] 2020-01-06 Optimal, resilient operation of dynamic multi-microgrids…”

Section: Results and Discussion Of The Systematic Reviewmentioning

confidence: 99%

“…Each of the key contributions models a set of controllable and uncontrollable microgrid assets. Some of them use generic models such as generic unschedulable DERs (e.g., [27,52,64]) while others specifically model the properties of some assets such as Wind Turbines (WTs) including their turbine characteristics (e.g., [28,58]). Table 3 summarizes modeled DER parameters and classifies common DER constraints.…”

Section: Modeling Approaches and Modeled Assetsmentioning

confidence: 99%

See 1 more Smart Citation

The Spectrum of Proactive, Resilient Multi-Microgrid Scheduling: A Systematic Literature Review

2020

View full text Add to dashboard Cite

Multi-microgrids address the need for a resilient, sustainable, and cost-effective electricity supply by providing a coordinated operation of individual networks. Due to local generation, dynamic network topologies, and islanding capabilities of hosted microgrids or groups thereof, various new fault mitigation and optimization options emerge. However, with the great flexibility, new challenges such as complex failure modes that need to be considered for a resilient operation, appear. This work systematically reviews scheduling approaches which significantly influence the feasibility of mitigation options before a failure is encountered. An in-depth analysis of identified key contributions covers aspects such as the mathematical apparatus, failure models and validation to highlight the current methodical spectrum and to identify future perspectives. Despite the common optimization-based framework, a broad variety of scheduling approaches is revealed. However, none of the key contributions provides practical insights beyond lab validation and considerable effort is required until the approaches can show their full potential in practical implementations. It is expected that the great level of detail guides further research in improving and validating existing scheduling concepts as well as it, in the long run, aids engineers to choose the most suitable options regarding increasingly resilient power systems.

show abstract

Section: Results and Discussion Of The Systematic Reviewmentioning

confidence: 99%

Section: Modeling Approaches and Modeled Assetsmentioning

confidence: 99%

The Spectrum of Proactive, Resilient Multi-Microgrid Scheduling: A Systematic Literature Review

2020

View full text Add to dashboard Cite

show abstract

“…The procedure of the framework is realized for the normal operation mode. The operating costs of the distribution network are minimized in the normal operation mode by the optimal scheduling and dispatching of controllable DGs based on the model presented in [22]. In addition, the probabilistic and intermittent characteristics of renewable DG units, including an hourly variation of the demand and power market prices in the power system, have been considered within the scope of our optimal scheduling framework [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Optimal Operational Scheduling of Reconfigurable Microgrids in Presence of Renewable Energy Sources

2019

View full text Add to dashboard Cite

Passive distribution networks are being converted into active ones by incorporating distributed means of energy generation, consumption, and storage, and the formation of so-called microgrids (MGs). As the next generation of MGs, reconfigurable microgrids (RMGs) are still in early phase studies, and require further research. RMGs facilitate the integration of distributed generators (DGs) into distribution systems and enable a reconfigurable network topology by the help of remote-controlled switches (RCSs). This paper proposes a day-ahead operational scheduling framework for RMGs by simultaneously making an optimal reconfiguration plan and dispatching controllable distributed generation units (DGUs) considering power loss minimization as an objective. A hybrid approach combining conventional particle swarm optimization (PSO) and selective PSO (SPSO) methods (PSO&SPSO) is suggested for solving this combinatorial, non-linear, and NP-hard complex optimization problem. PSO-based methods are primarily considered here for our optimization problem, since they are efficient for power system optimization problems, easy to code, have a faster convergence rate, and have a substructure that is suitable for parallel calculation rather than other optimization methods. In order to evaluate the suggested method’s performance, it is applied to an IEEE 33-bus radial distribution system that is considered as an RMG. One-hour resolution of the simultaneous network reconfiguration (NR) and the optimal dispatch (OD) of distributed DGs are carried out prior to this main study in order to validate the effectiveness and superiority of the proposed approach by comparing relevant recent studies in the literature.

show abstract

“…Particle swarm optimization and weighted aggregation are used in [16] to approximate the Pareto 110 front for energy cost and environment comfort. The Pareto front is approximated using the -constraint method in [17], balancing the total cost and the energy obtained from distributed generators in isolated sites, and in [18] and [19] minimizing both pollutant emission and operating cost.…”

Section: Introductionmentioning

confidence: 99%

“…We discuss the fair allocation of resources in Section 4.5. Constraints (18) and (19) account for the building response in the case of a DR request:…”

mentioning

confidence: 99%

Optimal collaborative demand-response planner for smart residential buildings

Gomez-Herrera

Anjos

2018

Energy

View full text Add to dashboard Cite

This work presents a collaborative scheme for the end-users in a smart building with multiple housing units. This approach determines a day-ahead operational plan that provides demand-response services by taking into account the amount of energy consumed per household, the use of shared storage and solar panels, and the amount of shifted load. We use a biobjective optimization model to trade off total user satisfaction versus total cost of energy consumption. The optimization works in combination with a price structure based on time and level of use that encourages load shifting and benefits the participants. Computational experiments and an extensive sensitivity analysis validate the performance of the proposed approach and help to clarify its strengths, its limits, and the requirements for ensuring the desired outcome.

show abstract

Optimal day-ahead operational planning of microgrids

Cited by 29 publications

References 34 publications

The Spectrum of Proactive, Resilient Multi-Microgrid Scheduling: A Systematic Literature Review

The Spectrum of Proactive, Resilient Multi-Microgrid Scheduling: A Systematic Literature Review

Optimal Operational Scheduling of Reconfigurable Microgrids in Presence of Renewable Energy Sources

Optimal collaborative demand-response planner for smart residential buildings

Contact Info

Product

Resources

About