Distributed Generation Plants Research Articles

Противоаварийное управление установками распределенной * генерации

The article presents the results of investigations aimed at elaborating emergency control methods in the power supply systems equipped with distributed generation plants. The control outputs aimed at bringing the operation mode into the stability region were produced by changing the vector of controlled parameters along the specified trajectory and also along a trajectory corresponding to the shortest path from the point of initial mode to the limit hypersurface. The quality of dynamic processes in implementing the control outputs was ensured by coordinated tuning of the automatic excitation controllers (AEC) and automatic rotation frequency controllers (AFRC). It is shown proceeding from computer simulation results that the system can be efficiently brought into the stability region on the basis of limit mode equations by using a startup algorithm that brings the mode to the stability region’s nearest boundary. By using fuzzy technologies to control the tuning of AEC and AFRC it is possible to organize high-quality dynamic transition during unloading of generator in the post-emergency operation mode.

Effect of distributed generation plants’ automatic controllers on power quality factors

Currently, energy generation industry transition to a new technological platform based on smart electrical energy systems (EES) is underway, with EES equipped with active-adaptive mains. This platform involves a large-scale use of digital devices and significant electrical energy (EE) generation using distributed generation (DG) plants which are to be created by power consumers. These plants can operate as parts of existing grids, or be pooled in network clusters. To implement smart EES, the development of new approaches is required for production, distribution and EE consumption modes management. The article is dedicated to the issues of DG plants application to raise efficiency of non-traction consumers power supply systems. In this case, a special attention was paid to enhancing the electrical energy quality via application of the DG plant which is controlled by concordantly set generator automatic voltage regulator (AVR) and automatic speed governor (ASG). For optimization and harmonization of AVR and ASG settings a method of nonparametric identification of the ‘turbine-generator’ system was used which can be represented as complex activation functions of main channels and crosslinks of regulators and the generator. The study was carried out in Matlab environment on a created railroad power supply system model. The studies conducted helped to detect that application of DG plants with concordantly set AVR and ASG makes it possible to enhance power quality for non-traction consumers and ensure dynamic stability and resilience of railroad line power supply system.

Моделирование режимов работы систем электроснабжения с установками распределенной генерации и мощной асинхронной нагрузкой

Моделирование режимов работы систем электроснабжения с установками распределенной генерации и мощной асинхронной нагрузкой

Operational constrained nonlinear modeling and identification of active distribution networks

This paper proposes a methodology for the identification of equivalent models of active distribution networks. Due to the increasing installation of distributed generation plants, distribution networks are acquiring an “active” role in the management of the overall power system. In this context, equivalent modeling is becoming essential for allowing transmission system operators to expand the system observability and improve the interoperability with distribution system operators. The present paper proposes a nonlinear model and an identification procedure able to take into account the prior knowledge of a given active distribution network. The result is an equivalent model, which can be easily adapted for reproducing the dynamical behavior of the network with different configurations. The proposed approach is validated through a simulation study on a Benchmark Medium Voltage Active Network.

Grid Voltage Sensorless Control of Single Phase Grid Tied Inverter for Renewable Energy Systems Applications

This paper introduces a grid voltage sensorless control scheme using damped resonant compensator for single phase grid interactive inverter interfacing renewable energy-based distributed generation plants with the grid. Elimination of grid voltage sensor reduces the cost and enhances the system reliability. A delay compensated model predictive current controller is also implemented with the estimation scheme to achieve the grid side control task, which includes reduction in harmonic contamination in the injected current and regulating the power factor during dynamic conditions like change in power demands and grid voltage distortions. The grid synchronization process is accomplished without a phase locked loop using the estimated grid voltage signal. A 1 kW grid tied single phase inverter is modeled and simulated for performance validation of the control scheme. The proposed control strategy is also corroborated by hardware implementation using ds1104 real time controller.

Lifetime, cost and fuel efficiency in diesel projects for rural electrification in Venezuela

From 2000–2016, 600 million people in developing countries accessed electricity through fossil-fuel-based technologies, both in isolated and grid-connected schemes. Although an increase in the use of renewable energy sources is expected, 40% of the new connections until 2030 will be through conventional technologies, including diesel. Diesel generator sets can be carried out using three different strategies: (1) off-grid, (2) support to national grid extension or (3) support to distributed generation plants in rural zones. Advantages and inconveniences of each strategy have not clearly been stated yet. The objective is to evaluate and compare the 3 strategies to improve future projects. Therefore, cases from Venezuela have been studied. Historical generation and operational data are analyzed, as well as in situ visits, surveys and interviews. Although Venezuela is an oil producer country, contrasts with the world energy matrix since its fossil fuel-based generation is less than a half of the global average. Results show the advantages of each strategy are conditioned by geographical, climatic and logistical factors, while benefits of the support to national grid extension strategy have been highlighted. These results can assist rural electrification promoters to effectively determine the most appropriate diesel projects strategy.

Smart integration of photovoltaic production, heat pump and thermal energy storage in residential applications

The optimal design of distributed generation systems is of foremost importance to reduce fossil fuel consumption and mitigate the environmental impact of human activities in urban areas. Moreover, an efficient and integrated control strategy is needed for each of the components of a distributed generation plant, in order to reach the expected economic and environmental performances.In this paper, the transition from natural gas to electricity-based heating is evaluated for residential applications, considering the interplay between photovoltaic electricity produced on site and the thermal energy storage, to grant the optimal management of heating devices. The energy demand of an apartment building, under different climatic conditions, is taken as a reference and four power plant solutions are assessed in terms of energy cost and pollution reduction potential, compared to a baseline plant configuration. The performance of each power plant is analyzed assuming an optimized control strategy, which is determined through a graph-based methodology that was previously developed and validated by the authors. Outcomes from our study show that, if heat pumps are used instead of natural gas boilers, energy costs are reduced up to 41%, while CO2 emissions are reduced up to 73%, depending on the climatic conditions.Our results provide a sound basis for considering the larger penetration of photovoltaic plants as an effective solution towards cleaner and more efficient heating technologies for civil applications. The simultaneous utilization of heat pumps (as substitutes of boilers) and photovoltaic panels yields a positive synergy that nullifies the local pollution, drastically cuts the CO2 emission, and guarantees the economical sustainability of the investment in renewable energy sources without subsidiary mechanisms.

A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response

Conventionally, community energy management system (CEMS) is provided with the information of surplus and shortage amounts only at each time interval. This limited information may lead to an increase in the operational cost of the multimicrogrid (MMG) systems. This paper suggests informing the CEMS about the adjustable power also, in addition to the surplus and shortage information. This additional information will result in a variety of options for the CEMS to fulfill the load demands of its network. CEMS will choose among various available options, which include trading with the power grid, buying from a controllable distributed generation plant, buying from a community battery energy storage system (CBESS), or controlling the adjustable power: increasing or decreasing the generation of controllable units. CBESS can either be controlled by CEMS or can act as an autonomous entity. The effects of both the operational options have been analyzed and economically efficient mode is suggested for MMG systems. Demand response (DR) is also considered in the proposed model. The incorporation of DR will ensure the supply reliability of the MMG system in addition to the reduction in operational cost. In contrast to the conventional single or two-step multimicrogrid optimization algorithms, a multistep hierarchical optimization algorithm based on a multiagent system is proposed in this paper. Easy to implement and computationally inexpensive mixed integer linear programming models are developed for each step.

Meta-heuristic optimization for a high-detail smart management of complex energy systems

Distributed generation and, in particular, cogeneration and trigeneration are generally considered viable solutions to reduce energy consumption and mitigate the environmental impact of developed economies. Nonetheless, such systems need to be carefully designed and managed to effectively meet all the economic and environmental expectations. The design of a distributed generation plant and the choice of its proper management policy are complex tasks that require effective support methodologies and tools.In this paper, we develop a methodology to determine the optimal control strategy for a trigeneration plant. The model enforces mass end energy balances and accounts for the nonlinear and the basic dynamic behavior of each energy converter, for the time varying energy prices and environmental conditions, for maintenance and cold start costs, and for the possibility to store energy. We built on a methodology previously developed and we dramatically broaden its field of application to complex smart grids with a very high temporal detail, by cutting down its computational costs. To this aim, we implement an heuristic procedure that reduces the computational complexity of the non linear optimization problem. The total cash flow, the primary energy consumption, the plant efficiency, and the CO2 emissions, besides the instantaneous set-point of the plant, are among the most relevant results of the model.The model is first validated through 11 test-cases specifically designed to stress the possible weaknesses of the heuristic procedure. The validation evidences that the proposed procedure does not introduce further approximations to the mathematical model. The global optimum is retrieved for all the considered cases. Afterwards, we apply the proposed methodology to a realistic energy management scenario: the assessment of a fuel cell based trigeneration plant for a civil building for a whole year. The discussion highlights the effectiveness of the proposed method for different applications including the optimization of the control strategy for existing plants, the design of new distributed generation systems, the assessment of innovative energy conversion technologies, and the evaluation of national energy policies.

A scenario-based optimization of Smart Energy Hub operation in a stochastic environment using conditional-value-at-risk

Besides increasing the installation of distributed generation plants, investigation on multi-carrier energy systems leads recent studies to focus on several aspects of Smart Energy Hub (S. E. Hub) systems. An S. E. Hub incorporates several modules which calculation of optimal size and operation of each have already attracted a great deal of research. Uncertainty in the modeling of these modules is an imperative factor that was not paid attention in S. E. Hub models properly. To build up a more precise framework for S. E. Hubs, here we present a stochastic model for real time electricity and natural-gas prices and electricity demands. In this paper, an S. E. Hub operates in order to minimize a weighted sum function consisting energy bill and penalty for emissions. To have more precise model, we use conditional value at risk (CVaR) technique to control the operational risk of an S. E. Hub when electricity and natural gas are converted to electrical, heating, and cooling energy in its output ports. The proposed optimization method is validated by simulating it on a real office building in Tehran, Iran.

Enhancing reliability of power supply systems with distributed generation plants

The article present results of studies aimed at emergency control methods development in power supply systems equipped with distributed generation plants. The main purpose of emergency control is ensuring postemergency mode dead-beat stability and high quality of dynamic transitions for electrical network load-shedding. Control actions were formed by changing the vector of controlled parameters along a path corresponding to the shortest distance to the hypersurface of the limit modes. The dynamic processes quality when implementing the control actions was ensured based on the special settings of excitation and frequency automatic regulators. Based on computer-aided modelling, it is shown that the effective in-troduction of a postemergency mode to the stability region can be performed based on generalized equations of the limit loads while using the start algorithm ensuring mode’s entering the stability region’s neighboring boundary. The application of the fuzzy control algorithms for tuning regulators allows formation of a qualitative dynamic transition while load-shedding distributed generation plants in the postemergency mode.

Network Reliability Analysis as a Tool to Guide Investment Decisions in Distributed Generation

Distributed Generation (DG) in any quantity is relevant to supplement the available energy capacity based on various locations, that is, whether a site specific or non-site specific energy technology. The evacuation infrastructure that delivers power to the distribution grid is designed with appropriate capacity in terms of size and length. The evacuation lines and distribution network however behave differently as they possess inherent characteristics and are exposed to varying external conditions. It is thus feasible to expect that these networks behave stochastically due to fault conditions and variable loads that destabilize the system. This in essence impacts on the availability of the evacuation infrastructure and consequently on the amount of energy delivered to the grid from the DG stations. Reliability of the evacuation point of a DG is however not a common or prioritized criteria in the decision process that guides investment in DG. This paper reviews a planned solar based DG plant in Uganda. Over the last couple of years, Uganda has seen a significant increase in the penetration levels of DG. With a network that is predominantly radial and experiences low reliability levels, one would thus expect reliability analysis to feature significantly in the assessment of the proposed DG plants. This is however not the case. This paper, uses reliability analysis to assess the impact of different evacuation options of the proposed DG plant on its dispatch levels. The evacuation options were selected based on infrastructure options in other locations with similar solar irradiances as the planned DG location. Outage data were collected and analyzed using the chi square method. It was found to be variable and fitting to different Probability Distribution Functions (PDF). Using stochastic methods, a model that incorporates the PDFs was developed to compute the reliability indices. These were assessed using chi square and found to be variable and fitting different PDFs as well. The viability of the project is reviewed based on Energy Not Supplied (ENS) and the anticipated project payback periods for any considered evacuation line. The results of the study are also reviewed for the benefit of other stakeholders like the customers, the utility and the regulatory body.

Application of energy routers in railway power supply systems

The development of electric power industry requires transition to the technological platform, encouraging implementation of smart grids. To set up these grids it is necessary to apply smart technologies of power supply system control modes, as well as interfaces, ensuring the connection of renewable energy sources. These interfaces may be represented by energy routers. The paper discusses the results of simulating emergency modes, caused by short circuits in 10 kV and 0.4 kV grids of non-traction users, connected via energy routers to the railway power supply system. The studies were performed in MATLAB system. Simulation results showed that the application of controlled energy routers for the non-traction user power supply completely removes electric power quality problems, allows for reliable integration of distributed generation plants into the power supply system, and limits short circuit currents and reduces the depth of the AC failure.

Моделирование процессов синхронизации и параллельной работы установок распределенной генерации с мощной промышленной сетью

Моделирование процессов синхронизации и параллельной работы установок распределенной генерации с мощной промышленной сетью

МЕТОД ПРОТИВОАВАРИЙНОГО УПРАВЛЕНИЯ УСТАНОВКАМИ РАСПРЕДЕЛЕННОЙ ГЕНЕРАЦИИ

МЕТОД ПРОТИВОАВАРИЙНОГО УПРАВЛЕНИЯ УСТАНОВКАМИ РАСПРЕДЕЛЕННОЙ ГЕНЕРАЦИИ

ПРИМЕНЕНИЕ НАКОПИТЕЛЕЙ ЭНЕРГИИ И УПРАВЛЯЕМЫХ УСТАНОВОК РАСПРЕДЕЛЕННОЙ ГЕНЕРАЦИИ ДЛЯ СНИЖЕНИЯ ПРОВАЛОВ НАПРЯЖЕНИЯ В СЕТЕВОМ ЭНЕРГЕТИЧЕСКОМ КЛАСТЕРЕ

ПРИМЕНЕНИЕ НАКОПИТЕЛЕЙ ЭНЕРГИИ И УПРАВЛЯЕМЫХ УСТАНОВОК РАСПРЕДЕЛЕННОЙ ГЕНЕРАЦИИ ДЛЯ СНИЖЕНИЯ ПРОВАЛОВ НАПРЯЖЕНИЯ В СЕТЕВОМ ЭНЕРГЕТИЧЕСКОМ КЛАСТЕРЕ

Distributed generation plants multi-agent controlling system

Distributed generation plants multi-agent controlling system

A Novel Voltage Sensitivity Approach for the Decentralized Control of DG Plants

Renewable distributed generation (DG) is likely to be actively controlled in future distribution networks to mitigate voltage issues resulting from high penetrations. This requires understanding the corresponding dependencies between voltage magnitudes and DG active/reactive power outputs. One approach to compute these dependencies is to use classical sensitivity methods such as those based on the Jacobian matrix inverse. However, updating the latter involves extensive remote monitoring. This paper presents a novel approach to produce voltage sensitivities applying the surface fitting technique on data based solely on the knowledge of network characteristics; making it suitable for decentralized DG control. To assess the benefits, comparisons with classical methods are carried out using the 16-bus UK GDS test network (1-min resolution simulations) considering a decentralized voltage control algorithm that simultaneously caters for the active and reactive power outputs of a single DG plant. The robustness of the proposed approach is also investigated considering changes in network parameters. Finally, the use of coordinated time delays is proposed to cater for multiple DG plants. Comparisons with a centralized optimization demonstrate that the combined use of the proposed voltage sensitivity approach and decentralized control algorithm is an effective and implementable candidate to actively manage renewable DG plants.

Power quality enhancement of single phase grid tied inverters with model predictive current controller

Recognition of renewable energy sources as alternative sources for power generation has augmented the number of distributed generation plants being incorporated into the conventional power distribution system. The single phase voltage source inverter allying the distributed generation plant with the grid has to address various issues related to the quality of current injected into the grid, output power factor, and power exchange between the plant and the grid. This paper focuses on the analysis, design, and implementation of a digital predictive current control technique known as model predictive current controller for the control of single phase power inverter integrating renewable energy based plant with the grid. The proposed controller is tested in diverse operating conditions and is compared with the existing proportional resonant current control scheme. The simulation and experimental results validate the efficacy of the proposed control technique.

Model predictive current controller for performance enhancement of grid-integrated single-phase photovoltaic distributed generation plants

Acknowledgement of renewable sources of energy as substitute energy sources for power production has expanded the number of distributed generation plants being incorporated into the conventional power distribution system. The single-phase voltage source inverter allying the photovoltaic plant with the grid has to address various issues identified with the quality of current injected into the grid, output power factor and power exchange between the plant and the grid. This paper concentrates on the investigation, design and implementation of a digital predictive current control technique known as the model predictive current controller for the control of single-phase photovoltaic distributed generation plants. The performance of the controller is evaluated under varied operating conditions. The proposed current controller is compared with the conventional proportional–integral controller in terms of its design methodology, steady state and dynamic response. The simulation and experimental results validates the effectiveness of the proposed model predictive current controller.