Renewable Distributed Energy Resources Research Articles

A Game-Theoretic Framework for Resilient and Distributed Generation Control of Renewable Energies in Microgrids

The integration of microgrids that depend on the renewable distributed energy resources with the current power systems is a critical issue in the smart grid. In this paper, we propose a non-cooperative game-theoretic framework to study the strategic behavior of distributed microgrids that generate renewable energies and characterize the power generation solutions by using the Nash equilibrium concept. Our framework not only incorporates economic factors but also takes into account the stability and efficiency of the microgrids, including the power flow constraints and voltage angle regulations. We develop two decentralized update schemes for microgrids and show their convergence to a unique Nash equilibrium. Also, we propose a novel fully distributed PMU-enabled algorithm which only needs the information of voltage angle at the bus. To show the resiliency of the distributed algorithm, we introduce two failure models of the smart grid. Case studies based on the IEEE 14-bus system are used to corroborate the effectiveness and resiliency of the proposed algorithms.

An Adaptive-Then-Combine Dynamic State Estimation Considering Renewable Generations in Smart Grids

The penetration of renewable distributed energy resources, such as wind turbine, has been dramatically increased in distribution networks. Due to the intermittent property, the wind power generation patterns vary, which may risk distribution network operations. So, it is intrinsically necessary to monitor wind turbines in a distributed way. This paper presents an adaptive-then-combine distributed dynamic approach for monitoring the grid under lossy communication links between the wind turbines and energy management system. First, the wind turbine is represented by a state-space linear model, with sensors deployed to obtain the system state information. Based on the mean squared error principle, an adaptive approach is proposed to estimate the local state information. The global estimation is designed by combining estimation results with weighting factors which are calculated by minimizing the estimation error covariance based on semidefinite programming. Finally, the convergence analysis indicates that the estimation error is gradually decreased, so the estimated state converges to the actual state. The efficacy of the developed approach is verified using the wind turbine and the IEEE 6-bus distribution system.

Coupled active and reactive market in smart distribution system considering renewable distributed energy resources and demand response programs

Summary In this paper a new framework is introduced to develop a coupled active and reactive market in distribution networks. Distributed energy resources (DERs) such as synchronous machine–based distributed generations and wind turbines offer their active and reactive powers to the proposed market. For the considered DERs, multicomponent reactive power bidding structures are introduced based on their capability curves. Also, the hourly speed variations of wind turbines are considered in the proposed model. A distribution company buys active and reactive powers from a wholesale market and sells them via this market. The demand side is active, and responsive loads or aggregators can participate in the market using a demand bidding/buyback program. The objective function of the proposed market is to minimize the active and reactive power costs of DERs and distribution companies, the penalty cost of CO2 emission, and the cost of running a demand bidding/buyback program. The effectiveness of the proposed method is examined on a 22-bus 20-kV radial distribution test system.

Controlling the renewable microgrid using semidefinite programming technique

Given the significant concerns regarding carbon emissions from fossil fuels, global warming and energy crisis, renewable distributed energy resources (DERs) are going to be integrated in smart grids, which will make the energy supply more reliable and decrease the costs and transmission losses. Unfortunately, one of the key technical challenges in power system planning, control and operation with DERs is the voltage regulation at the distribution level. This problem stimulates the deployment of smart sensors and actuators in smart grids so that the voltage can be stabilized. The observation from the microgrid incorporating DERs is transmitted to the control center via wireless communication systems. In other words, the proposed communication infrastructure provides an opportunity to address the voltage regulation challenge by offering the two-way communication links for microgrid state information collection, estimation and stabilization. Based on the communication infrastructure, we propose a least square based Kalman filter algorithm for state estimation and an optimal feedback control framework for stabilizing the microgrid states. Specifically, we propose to optimize the performance index by using semidefinite programming techniques in the context of smart grid applications. At the end, the efficacy of the developed approaches is demonstrated using a microgrid incorporating multiple DERs.

ENGLISH

Micro-grid is a combination of multiple distributed generators (DGs) and/or storage units which provide energy to comparatively small local communities Micro-grid (MG) is formed by renewable sources. MG is a small scale network of low voltage distributed renewable energy resources (DER).This paper reviews the optimal energy management for a MG under various constraints. This paper emphasize on the different methods adopted by various authors to optimize fuel cost, manage peak load and reduce gas emissions by scheduling generation of DERs in each hour or for particular time ‘t’. MG model includes battery as a storage device; hence the battery life also becomes one of the constraints. Mainly DERs are wind and solar source and are dependent on climatic conditions. The authors have used deterministic method to address aforesaid costaints.

Distributed Coordination of Electric Vehicles Providing V2G Services

The aim of this paper is to propose a distributed electric vehicle (EV) coordination management which exploits the potentials of the bidirectional power flow between the grid and the EV. In the literature, the proposed distributed price-based EV coordination mechanisms aiming to achieve a valley-filling concept consider electric vehicles as mere manageable loads, which are served during valley hours given the EV energy requirements and mobility pattern. In this paper, a distributed EV coordination mechanism is proposed that utilizes 1) the flexibility of EV demand in order to efficiently allocate it during the valley period and hours with high distributed renewable energy production and 2) the vehicle-to-grid (V2G) EV capability in order to minimize the network load variance. The aim of the proposed EV coordination mechanism is to: 1) exploit the synergies between the renewable distributed energy resources (DER) and EV charging needs in order to increase the EV/RES penetration level of the grid without the need for further network investments and 2) exploit the bidirectional EV battery operation for more efficient network operation in terms of voltage profile and network losses. The proposed EV coordination mechanism is assessed through simulations of a realistic rural MV distribution network.

Load management in a residential energy hub with renewable distributed energy resources

This paper presents a residential energy hub model for a smart multi-carrier energy home consisting of plug-in hybrid electric vehicle (PHEV), combined heat and power (CHP), solar panels, and electrical storage system (ESS). The energy hub inputs are electricity and natural gas that provide electrical and heat demands at the output ports. In this paper, an optimization-based program is proposed to determine the optimal operation mode of the energy hub, to manage the energy consumption of responsive appliances, to schedule charging/discharging of PHEV and the storage system, and to coordinate solar panels operation with household responsive demand in response to day-ahead time-varying tariffs of electricity. The objective function is to minimize customer payment cost considering vehicle to grid (V2G) capability. Different case studies are conducted to probe the effectiveness of the proposed method and study the impacts of different electrical time-differentiated tariffs on the optimization results on daily and yearly basis.

Unbalanced Active Distribution Analysis with Renewable Distributed Energy Resources

This paper presents unbalanced active distribution system analysis with renewable distributed Energy Resources (DER). The renewable DER models have been considered are photovoltaic (PV) and Wind Turbine generation (WTG). The three-phase distribution load flow on the basis of the symmetrical components have been used in the analysis. The unbalanced active distribution system has been analized using IEEE 13 node feeder and IEEE 8500 node feeder with renewable DER units. The variation of wind speed (m/s) for WTG, solar radiation (W/m²) and temperature (°C) for PV have been simulated. The simulation results show that the proposed DER model can be used to analysis renewable DER impacts in unbalanced distribution system. The integration of renewable DER units into an existing distribution network can improve the voltage profile and reduce total system losses. The simulation results show that DERs size and location are important factors to improve voltage profile and line loss reduction.

Real-Time Implementation of Multiagent-Based Game Theory Reverse Auction Model for Microgrid Market Operation

This paper presents a real-time implementation of a multiagent-based game theory reverse auction model for microgrid market operations featuring conventional and renewable distributed energy resources (DER). Studies were conducted on a grid connected microgrid consisting of a synchronous generator, two inverter-based generation units, and a combined load. The multiagent-based platform was applied to monitor, control, and perform the reverse auction process of DERs. A competitive game-theory reverse auction model was investigated to schedule the DER unit commitment with an hour-ahead market approach for the 24 h of the day. The proposed methodology was realistically implemented and operated at the Florida International University smart grid test system. The investigation shows that the proposed algorithm and the industrial hardware-based infrastructure can be implemented in the existing electric utility grid as new assets of the system are added.

Coordinated scheduling of energy resources for distributed DHCs in an integrated energy grid

As more and more distributed renewable energy resources connected to electric power grids, the conventional power system evolves into an integrated energy grid (lEG) in order to satisfy various types of energy demands. This paper proposes a model of the coordinated scheduling of energy resources (CSoERs) for distributed district heating and cooling systems (DHCs) in an lEG. The model takes into consideration both the dispatchable grid-connected generators and distributed renewable energy resources, such as wind energy, solar energy and natural gas. The objective is to minimize the operation costs in the lEG in order to satisfy not only the electrical loads but also the heating loads and cooling loads. Furthermore, an energy storage system for heating loads and cooling loads is also developed in the DHCs to improve the operation reliability in the distributed DHCs. Detailed simulation studies are carried out to verify the effectiveness of the CSoERs under two different operation scenarios: grid-connected scenario and stand-alone scenario. Simulation results demonstrate that the performance of the CSoERs contributes to significant energy saving and reliability operation in both grid-connected scenario and standalone scenario in the lEG.

IES Distinguished Lecture ?When e-Transportation Meets Distributed Renewable Energy Resources? [Society News

IES Distinguished Lecture ?When e-Transportation Meets Distributed Renewable Energy Resources? [Society News

An overview of distributed microgrid state estimation and control for smart grids.

Given the significant concerns regarding carbon emission from the fossil fuels, global warming and energy crisis, the renewable distributed energy resources (DERs) are going to be integrated in the smart grid. This grid can spread the intelligence of the energy distribution and control system from the central unit to the long-distance remote areas, thus enabling accurate state estimation (SE) and wide-area real-time monitoring of these intermittent energy sources. In contrast to the traditional methods of SE, this paper proposes a novel accuracy dependent Kalman filter (KF) based microgrid SE for the smart grid that uses typical communication systems. Then this article proposes a discrete-time linear quadratic regulation to control the state deviations of the microgrid incorporating multiple DERs. Therefore, integrating these two approaches with application to the smart grid forms a novel contributions in green energy and control research communities. Finally, the simulation results show that the proposed KF based microgrid SE and control algorithm provides an accurate SE and control compared with the existing method.

Microgrid state estimation and control for smart grid and Internet of Things communication network

Given the significant concerns regarding carbon emissions from fossil fuels, global warming and energy crises, the renewable distributed energy resources (DERs) are having to be integrated in the smart grid (SG). The SG can spread intelligence of the energy distribution and control system from the central unit to long-distance remote areas, thus enabling accurate state estimation (SE) and wide-area real-time monitoring of these intermittent energy sources. In contrast to the traditional methods of SE, a novel approach for SG SE is proposed based on concatenated coding structures, where the grid state is treated as a dynamic outer code and the recursive systematic convolutional code is seen as a concatenated inner code for protecting and redundancy in the system state. Furthermore, Kalman filter (KF)-based online DERs SE and a discrete-time linear quadratic regulation method are proposed to control these state deviations for the SG and the Internet of Things (IoTs) communication network, which can exploit the far-reaching connectivity and privacy of DERs messages. Simulation results show that the proposed algorithm achieves 3 dB performance improvement compared with the existing KF.

Distributed State Estimation Using RSC Coded Smart Grid Communications

Recently, the renewable distributed energy resources (DERs) have become more and more popular due to carbon-free energy sources and environment-friendly electricity generation. Unfortunately, these power generation patterns are mostly intermittent in nature and distributed over the electrical grid, which creates challenging problems in the reliability of the smart grid. Thus, the smart grid has a strong requisite for an efficient communication infrastructure to facilitate estimating the DER states. In contrast to the traditional methods of centralized state estimation (SE), we propose a distributed approach to microgrid SE based on the concatenated coding structure. In this framework, the DER state is treated as a dynamic outer code, and the recursive systematic convolutional (RSC) code is seen as a concatenated inner code for protection and redundancy in the system states. Furthermore, in order to properly monitor the intermittent energy source from any place, this paper proposes a distributed SE method. Particularly, the outputs of the local SE are treated as measurements, which are fed into the master fusion station. At the end, the global SE can be obtained by combining local SEs with corresponding weighting factors. The weighting factors can be calculated by inspiring the covariance intersection method. The simulation results show that the proposed method is able to estimate the system state properly.

Unit commitment in industrial microgrids with plug-in electric vehicles and photovoltaic generation

Industrial microgrids (IMGs) consist of factories with distributed energy resources (DERs) and electric loads that heavily rely on combined heat and power (CHP) systems. The new generations of IMGs are expected to also include renewable DERs and plug-in electric vehicles (PEVs) with different power ratings and charging characteristics. This paper proposes a profit-based security constrained unit commitment (PB-SCUC) formulation for IMGs with PEV charging and renewable DERs that includes both microgrid security and factories constraints as well as the PEV charging requirements. PB-SCUC will utilize the generators waste heat to fulfill thermal requirements and also consider the status of renewable DERs to decrease the overall cost of IMG. To demonstrate the effectiveness of PB-SCUC, detailed simulation results are presented and analyzed for an IMG consisting of 12 factories and 6 types of PEVs without/with photovoltaic generations operating in grid-connected and stand-alone modes. Copyright © 2014 John Wiley & Sons, Ltd.

Coordination of Generation Scheduling with PEVs Charging in Industrial Microgrids

Conventional industrial microgrids (IMGs) consist of factories with distributed energy resources (DERs) and electric loads that rely on combined heat and power (CHP) systems while the developing IMGs are expected to also include renewable DERs and plug-in electric vehicles (PEVs) with different vehicle ratings and charging characteristics. This paper presents an electricity and heat generation scheduling method coordinated with PEV charging in an IMG considering photovoltaic (PV) generation systems coupled with PV storages. The proposed method is based on dynamic optimal power flow (DOPF) over a 24-hour period and includes security-constrained optimal power flow (SCOPF), IMG's factories constraints, PV storage constraints and PEVs dynamic charging constraints. It will utilize the generators waste heat to fulfill thermal requirements while considering the status of renewable DERs to decrease the overall cost of IMGs. To demonstrate the effectiveness of the proposed method, detailed simulation results are presented and analyzed for an 18-bus IMG consisting of 12 factories and 6 types of PEVs without/with PV generation systems operating in grid-connected and stand-alone modes. The main contribution is including PEVs with dynamic constraints that have changed the nature of scheduling formulation from a simple hourly OPF to a dynamic OPF.

Absorbing the Rays: Advanced Inverters Help Integrate PV into Electric Utility Distribution Systems

PEPCO HOLDINGS, INC. (PHI) IS one of the largest energy delivery companies in the Mid-Atlantic region of the United States, serving about 1.9 million customers in Delaware, the District of Columbia, Maryland, and New Jersey. PHI's subsidiaries Pepco, Delmarva Power, and Atlantic City Electric (ACE) provide regulated electricity service to these areas. The ACE service territory has a number of renewable distributed energy resources (DER) installations, including landfill gas (methane), wind, and solar. In particular, solar installations in the form of photovoltaic (PV) systems have been increasing due to substantial financial incentives in New Jersey, while Maryland, Delaware, and Washington, D.C. are also seeing activity due to incentives. In New Jersey, large systems are interconnected into the distribution system (12 kV) because the state has required all systems to connect to the distribution system if the system owners wish to earn solar renewable energy certificates (SRECs). Applications for installations in the PHI distribution system range from 1 kW up to 100 MW.

Improving Reliability of Islanded Distribution Systems With Distributed Renewable Energy Resources

An optimization problem called “the feeder addition problem” is defined to determine potential locations for adding interties between feeders in a legacy radial distribution system to improve the reliability in the islanded mode of operation - a desired feature under the Smart Grid Initiative. Numerical bounds are established on the growth of the feeder addition problem. The feeder addition problem in a popular test system is handled using two different optimization methods to balance cost and reliability for utility applications. To approximate the power output of the distributed generation sources considered, an empirical equation incorporating the capacity factors of renewable energy-based distributed generation sources and results of an industry survey is used. Both optimization methods are shown to improve the system reliability for cases where the distributed generation output exceeded feeder demand.

Small-Signal Stability Enhancement of Power Systems with Renewable Distributed Energy Resources

AbstractThis paper examines the application of energy storage to enhance the small-signal stability of an electrical power system with renewable power generation. In particular, a linearized model of the system and an LMI-based control design method are used to achieve frequency and voltage regulation subject to small perturbations to mechanical power inputs to synchronous generators in the system. The controller design is validated using the following simulation studies: (1) a single machine connected to an infinite bus (SMIB) (2) a two-machine (synchronous generator and doubly-fed induction generator) connected to an infinite bus. Simulation results show that the proposed controller can simultaneously achieve frequency and voltage regulation.

Bibliography review on applications of correlation analysis in power system operation and planning

AbstractFast growth of large‐scale distributed renewable energy resources, electric power markets, and responsive demand impose significant amount of correlated uncertainties on operation of the power system from both resource side and load side. Understanding the correlations between these uncertainties and applying sophisticated correlation analysis of multiple dependent uncertainties is a defining issue for the development of methodologies and technologies for power system operation in the new era.Application of correlation analysis in operation of the power system is not as fully explored as many other methodologies. The complexity of mathematic modeling of multiple correlated random variables challenges the power system professionals. The research is further challenged by lacking of operational experience and empirical investigation challenges.This paper provides a bibliography survey on application of correlation analysis in operation of the power system. The scope of the review covers IEEE power systems proceedings, IEEE and IEE transactions published after 1980. There are 77 relevant papers identified. These papers are put into seven technical categories: power system reliability, wind generation, power market analysis, load forecast, resource planning and dispatch, transmission load flow, other non‐operation‐related topics. Copyright © 2008 John Wiley & Sons, Ltd.