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"Distributed generation"
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Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm
The scope of this study is the optimal siting and sizing of distributed generation within a power distribution network considering uncertainties. A probabilistic power flow (PPF)-embedded genetic algorithm (GA)-based approach is proposed in order to solve the optimisation problem that is modelled mathematically under a chance constrained programming framework. Point estimate method (PEM) is proposed for the solution of the involved PPF problem. The uncertainties considered include: (i) the future load growth in the power distribution system, (ii) the wind generation, (iii) the output power of photovoltaics, (iv) the fuel costs and (v) the electricity prices. Based on some candidate schemes of different distributed generation types and sizes, placed on specific candidate buses of the network, GA is applied in order to find the optimal plan. The proposed GA with embedded PEM (GA–PEM) is applied on the IEEE 33-bus network by considering several scenarios and is compared with the method of GA with embedded Monte Carlo simulation (GA–MCS). The main conclusions of this comparison are: (i) the proposed GA–PEM is seven times faster than GA–MCS, and (ii) both methods provide almost identical results.
Journal Article
Impact of Distributed Generators Penetration Level on the Power Loss and Voltage Profile of Radial Distribution Networks
The Distributed Generator types have different combinations of real and reactive power characteristics, which can affect the total power loss and the voltage support/control of the radial distribution networks (RDNs) in different ways. This paper investigates the impact of DG’s penetration level (PL) on the power loss and voltage profile of RDNs based on different DG types. The DG types are modeled depending on the real and reactive power they inject. The voltage profiles obtained under various circumstances were fairly compared using the voltage profile index (VPI), which assigns a single value to describe how well the voltages match the ideal voltage. Two novel effective power voltage stability indices were developed to select the most sensitive candidate buses for DG penetration. To assess the influence of the DG PL on the power loss and voltage profile, the sizes of the DG types were gradually raised on these candidate buses by 1% of the total load demand of the RDN. The method was applied to the IEEE 33-bus and 69-bus RDNs. A PL of 45–76% is achieved on the IEEE 33-bus and 48–55% penetration on the IEEE 69-bus without an increase in power loss. The VPI was improved with increasing PL of DG compared to the base case scenario.
Journal Article
Protection in DC microgrids: a comparative review
A direct current (DC) microgrid has become a superior power system in recent years due to the development of DC loads and higher efficiency of DC systems. One of the challenging problems on DC microgrids operation is protection, and it is still a particular concern associated with the challenges of developing a proper protection scheme owing to its characteristics and lack of standards in DC protection. Due to the significant increasing interest on DC microgrid; this study investigates protection problems and schemes that need to be addressed in modern power systems involving DC microgrids. This study analyses and presents a comprehensive review of the most recent growth in the DC microgrids protection. Additionally, the fault characteristics of DC microgrids, the impact of constant power loads, the protection devices and several proposed methods to overcome the protection problems are discussed. The differences between the proposed protection methods for the DC microgrids are also discussed.
Journal Article
Optimal allocation of solar and wind distributed generation using particle swarm optimization technique
Power demand in the current days is increasing more and more where the conventional power generation systems are failing to meet these power demands due to less availability of non-renewable resources. Hence, many of the researchers are working on the distributed generation (DG) by using renewable resources like wind and solar. The penetration towards wind, solar DG faced challenging situations during power generation due to uncertainty in the wind speed and solar radiation. Recent studies have predicted that the combination of both solar and wind can lead to better performance. However, the sizing and placement of DG systems is necessary to achieve efficiency otherwise the systems may lead to adverse effects in distribution networks. This paper introduced the solar DG, wind DG and hybrid (solar and wind) DG system. The particle swarm optimization technique is used to size and place the DG because of its parallel search capability. Also, the combination of wind-solar DG gives better DG sizing in the respective DG location. The voltage profile of these DG systems has shown better results for the efficient power system. In comparison to conventional DG systems, the suggested hybrid DG system is capable of minimizing power loss and maintaining voltage profile.
Journal Article
Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review
For over a decade, distributed generations (DGs) have sufficiently convinced the researchers that they are the economic and environment-friendly solution that can be integrated with the centralized generations. The optimal planning of distributed generations requires the appropriate location and sizing and their corresponding control with various power network types to obtain the best of the technical, economical, commercial, and regulatory objectives. Most of these objectives are conflicting in nature and require multi-objective solutions. Therefore, this paper brings a comprehensive literature review and a critical analysis of the state of the art of the optimal multi-objective planning of DG installation in the power network with different objective functions and their constraints. The paper considers the adoption of optimization techniques for distributed generation planning in radial distribution systems from different power system performance viewpoints; it considers the use of different DG types, distribution models, DG variables, and mathematical formulations; and it considers the participation of different countries in the stated DG placement and sizing problem. Moreover, the summary of the literature review and critical analysis of this article helps the researchers and engineers to explore the research gap and to find the future recommendations for the robust optimal planning of the DGs working with various objectives and algorithms. The paper considers the adoption of uncertainties on the load and generation side, the introduction of DGs with energy storage backups, and the testing of DG placement and sizing on large and complex distribution networks.
Journal Article
Multi-objective stochastic optimal planning method for stand-alone microgrid system
To achieve economic and environmental benefit for the stand-alone microgrid consisting of diesel generators, wind turbine generators, photovoltaic generation system and lead-acid batteries, a multi-objective stochastic optimal planning method and a stochastic chance-constrained programming model are presented. In the model, the optimal objective is to simultaneously minimise the total net present cost and carbon dioxide emission in life cycle; the type and capacity of distributed generation units have been selected as the optimal variables; the loss of capacity is adopted as probability index constraint; the coordinated operation strategies between diesel generators and battery, the multi-unit operation constraints of diesel generators and the reserve capacity have been considered in the hard-circle operation strategy. Considering the uncertainties of wind speed, clearness index and load demand, Markov process transition probability matrix is adopted to synthesise those time series data. Optimal planning for an island microgrid system has been carried out by the planning system for microgrid (PSMG), a self-developed optimal planning software based on the multi-objective stochastic optimal planning method for stand-alone microgrid system.
Journal Article