Distributed Generation Technologies Research Articles

What Roles for Energy Cooperatives in the Diffusion of Distributed Generation Technologies?

Whereas a centralized model of electricity infrastructure is still dominant today, many scholars advocate the diffusion of distributed generation technologies, implying geographically dispersed and small-scale generation units located close to consumers. However, there exist various barriers of different natures to a large-scale penetration of these technologies. In this article, we focus on the behavioral and psychological ones, emphasizing the roles that citizens have to play in this issue. More specifically, we explore a specific way of involving citizens in such diffusion, namely energy cooperatives. After presenting the driving forces of the emergence of cooperative firms in the energy sector, we examine the assets of the cooperative ownership structure from the perspectives of behavioral economics and social psychology. Our analysis enables us to build a model of how cooperatives may enhance consumer engagement in the diffusion of distributed generation technologies. This provides a basic theoretical framework for future empirical research.

Distributed Generation Technologies and Optimization

Abstract This paper describes the main technologies used for distributed generation and the optimization of a system that contains these technologies. The term distributed generation refers to the production of electricity near the consumption place. The distributed generation resources are renewable energies and cogeneration (simultaneous production of heat and electricity). Renewable energy is energy from natural resources such as wind, sunlight, tides, waves, geothermal heat and biomass. The optimization aims to minimize the electricity production costs ensuring that the load is served reliably.

Integrating the Weight of History into the Alignment Framework: The Case of Distributed Generation Technologies

Whereas a centralized energy supply system is still dominant today, the energy sector is currently witnessing the development of small-scale and more geographically dispersed generation units, so-called distributed generation technologies. So-called proposes a very useful approach to look at this evolution. Yet, we argue in this paper that this framework does not fully take into account the inertia associated with past technological and institutional choices that may hinder future changes. Relying on the concept of socio-technical lock-in, we illustrate this point with the case of the diffusion of distributed generation technologies. Based on this analysis, we propose an adaptation of the alignment framework to integrate these elements.

Energy Losses and Voltage Stability Study in Distribution Network with Distributed Generation

With the distributed generation technology widely applied, some system problems such as overvoltages and undervoltages are gradually remarkable, which are caused by distributed generations like wind energy system (WES) and photovoltaic system (PVS) because of their probabilistic output power which relied on natural conditions. Since the impacts of WES and PVS are important in the distribution system voltage quality, we study these in this paper using new models with the probability density function of node voltage and the cumulative distribution function of total losses. We apply these models to solve the IEEE33 distribution system to be chosen in IEEE standard database. We compare our method with the Monte Carlo simulation method in three different cases, respectively. In the three cases, these results not only can provide the important reference information for the next stage optimization design, system reliability, and safety analysis but also can reduce amount of calculation.

Distributed generation planning based on the distribution company's and the DG owner's profit maximization

Summary In recent years, Distributed Generation (DG) has been utilized in electric power networks increasingly. DG units can affect the system operational conditions in different ways such as voltage profile improvement, amending voltage stability, reliability enhancement, securing power market, etc. if they are managed properly. Otherwise, they may have undesirable impacts on technical issues of power grids. A lot of studies have been done on various aspects of control and operation of DG units to find the optimal placement, sizing and also the proper technology of them. This paper proposes a novel comprehensive economic method for planning DG units which considers both the Distribution Company's (DisCo) and the DG Owner's (DGO) profits simultaneously. Multi-objective particle swarm optimization technique is used to simulate many case studies on the IEEE 33-bus distribution test system and finally find the best solution for the placement, size and contract price of the generated power of DGs. The proposed methodology not only considers operational aspects such as power loss reduction, voltage profile and stability improvement and reliability enhancement, but also leads to an accurate analysis which satisfies both the DisCo's and the DGO's economic viewpoints. Finally, an encouragement to invest more on DG technologies is proposed based on the gained results. Copyright © 2013 John Wiley & Sons, Ltd.

Gasification of High and Low Density Crop Residues

Crop residue constitutes a large fraction of biomass particularly in agricultural based economies like India. The most abundantly generated crop residues are paddy husk, paddy straw, coconut shell, cotton stalk and sugar cane trash. It is estimated that the potential of power generation using crop residue is close to 14 GWe in a country like India. Even though the potential is large, the main drawback with crop residue is that it is sparsely distributed and being of low density causes collection and transportation problem. This drawback could be converted into an advantage by adopting distributed power generation technologies. The distributed power generation would fare well in the power range of few hundred kilowatts and the most appropriate technology would be the biomass gasification technology. Among the biomass gasification technologies, the downdraft technology is ideally suited for power generation. The downdraft technology is proven with solid or woody biomass, whereas there are limitations in terms of acceptance of all types of crop residues. In this paper, performance study of two vastly differing crop residues, namely coconut shell and cotton stalk has been discussed; both the feedstocks have been tested in “post-harvested” condition with minimum amount of pre-processing. The performance with cotton stalk was found to be comparable at part load; however at higher load the gas composition deteriorated due to poor material movement within the reactor. This had implication in terms of maximum power generated. There was loss of power to an extent of 12%. The operational issues with post-harvested cotton stalk has been brought out which are based on detailed measurements.

Optimal generation rescheduling in microgrids under uncertainty

Microgrids could increase reliability locally through the establishment of a specific improvement plan that integrates distributed power generation and other smart technologies. In this paper we propose a solution method for an optimal generation rescheduling problem in microgrids in order to determinate a stable equilibrium state following outages. The presented approach, focused on MV distribution systems, takes into account uncertainty modeled by Fuzzy Numbers due to both the load profiles and the power production from renewable energy sources. The method has been tested on 69-bus radial distribution systems considering two outage cases to demonstrate the performance and effectiveness of the proposed method. The obtained encouraging results are presented and discussed.

Optimum Microgrid Design for Enhancing Reliability and Supply-Security

Microgrids are known as clusters of distributed energy resources serving a group of distributed loads in grid-connected and isolated grid modes. Nowadays, the concept of microgrids has become a key subject in the smart grid area, demanding a systematic procedure for their optimal construction. According to the IEEE Std 1547.4, large distribution systems can be clustered into a number of microgrids to facilitate powerful control and operation infrastructure in future distribution systems. However, clustering large systems into a set of microgrids with high reliability and security is not reported in current literature. To fill-out this gap, this paper presents a systematic and optimized approach for designing microgrids taking into account system reliability- and supply-security-related aspects. The optimum design considers sustained and temporary faults, for system reliability via a combined probabilistic reliability index, and real and reactive power balance, for supply security. The loads are assumed to be variable and different distributed generation (DG) technologies are considered. Conceptual design, problem formulation and solution algorithms are presented in this paper. The well-known PG&E 69-bus distribution system is selected as the test system. The effect of optimization coefficients on the design and the robustness of the algorithm are investigated using sensitivity studies.

A mixed-integer nonlinear program for the optimal design and dispatch of distributed generation systems

Maturing distributed generation (DG) technologies have promoted interest in alternative sources of energy for commercial building applications due to their potential to supply on-site heat and power at a lower cost and emissions rate compared to centralized generation. Accordingly, we present an optimization model that determines the mix, capacity, and operational schedule of DG technologies that minimize economic and environmental costs subject to the heat and power demands of a building and to the performance characteristics of the technologies. The technologies available to design the system include lead-acid batteries, photovoltaic cells, solid oxide fuel cells, heat exchangers, and a hot water storage tank. Modeling the acquisition and operation of discrete technologies requires integer restrictions, and modeling the variable electric efficiency of the fuel cells and the variable temperature of the tank water introduces nonlinear equality constraints. Thus, our optimization model is a nonconvex, mixed-integer nonlinear programming (MINLP) problem. Given the difficulties associated with solving large, nonconvex MINLPs to global optimality, we present convex underestimation and linearization techniques to bound and solve the problem. The solutions provided by our techniques are close to those provided by existing MINLP solvers for small problem instances. However, our methodology offers the possibility to solve large problem instances that exceed the capacity of existing solvers and that are critical to the real-world application of the model.

Placement of minimum distributed generation units observing power losses and voltage stability with network constraints

Distributed generations (DGs) are recently in growing attention as a solution to environmental and economical challenges caused by conventional power plants. In this study, a multi-objective framework as a nonlinear programming (NLP) is proposed for optimal placement and sizing of DG units. Objective functions include minimising the number of DGs and power losses as well as maximising voltage stability margin formulated as a function of decision variables. The objective functions are combined into one objective function. To avoid problems with choosing appropriate weighting factors, fuzzification is applied to objective functions to bring them into the same scale. DG units are placed at more efficient buses rather than end buses of radial links as usually determined by previous methods for improving voltage stability. Also, power system constraints including branch and voltage limits are observed in the problem. The proposed method not only is able to model all types of DG technologies but also it employs adaptive reactive limits for DGs rather than fixed limits. In addition, a three-stage procedure is proposed to gradually solve the multi-objective problem in order to prevent infeasible solutions. Also, a new technique is proposed to formulate the number of DGs without converting the NLP problem into mixed-integer NLP. Results of testing the proposed method show its efficiency.

Establishing conditions for the economic viability of fuel cell-based, combined heat and power distributed generation systems

Combined heat and power (CHP), distributed generation (DG) technologies have the potential to provide economic savings to commercial building owners in certain markets, if the system is appropriately configured, sized, and operated. Numerous optimization models exist for determining the design and dispatch of a DG system, and some require a great deal of time and computing power to determine building-market scenarios for which the optimal solution includes the acquisition of CHP technologies. Thus, it is beneficial to identify which scenarios are likely to be economically viable prior to solving an optimization model that determines the lowest-cost system design and dispatch. Accordingly, we derive conditions for the economic viability of a CHP DG technology by comparing the total operational savings afforded by the technology to its total installed cost. We demonstrate these conditions numerically in eight distinct scenarios that include the installation of a fuel cell-based CHP system for various building types and energy markets. Using these scenarios, we examine the energy, emissions, operations and maintenance, and peak demand savings provided by the DG system, and determine which scenarios are likely to result in total savings that exceed the total installed cost. Results indicate that the combination of building type, energy market, and system design and dispatch in a given scenario have a significant impact on the economic viability of the CHP system.

An auction design for local reserve energy markets

In this paper we develop an auction mechanism that is designed for a local energy market. It aims to enable regionally or virtually restricted trading of ancillary services, which enhances the position of the balance group responsible party beyond that of simple accounting. Furthermore, it makes local market participants somewhat more independent from the transmission grid operator, but at the same time provides incentives for investments in distributed generation technologies. A wider spread of these technologies can help to save CO2 emissions, while at the same time a part of them can also be used to counter the fluctuations of energy from volatile renewable sources, such as wind and solar power. Because of their relatively high margins and small share in total production, ancillary services are well-suited for a remuneration scheme. Participants in the auction are, thus, private households, which impose specific design characteristics on the auction. Most importantly, it needs to be transparent and easy to understand, as homeowners will typically not have the insights of a professional trader as well as lack a similar position and motivation. Also, the confinement to a single balance group, i.e. a local market, means that especially in the beginning of the trading only a small number of bidders can be expected. Therefore, competition will initially be limited, so that the auction design needs to be adapted accordingly. In order to test the performance of the proposed auction market design under varying information policies, a simple agent-based simulation program has been developed. We find that the theoretical predictions hold and that competition quickly leads to price convergence.

Optimal wind turbine sizing to minimize energy loss

The integration of renewable distributed generation (DG) in power systems has been increasing day by day. One of the most promising DG technologies is wind turbine among the renewable sources. Therefore, the optimization of DG whose the output power is varying with time is very crucial for the future power systems. However, it is difficult to establish a suitable objective function by taking into account of time varying characteristics. In this paper, a methodology based on weighting factors is proposed in order to minimize energy loss by finding the optimal sizes of wind turbines. The optimization is carried out by using the genetic algorithm with utilizing power flow analysis. The contribution of this paper is to allow considering the time varying characteristics of both load and wind-generation profile in a pairwise manner without violating the harmony of correspondence between load and generation profile. In addition, the proposed methodology is merged with the fuzzy-c means clustering to reduce execution time and allow long term planning due to the fact that the computational burden of the genetic algorithm is substantially high. The proposed methodology is applied to the IEEE-30 bus test system for 4days and annual energy loss minimization scenarios. The results show that energy loss can be reduced significantly by using the proposed methodology.

The Geography of Solar Photovoltaics (PV) and a New Low Carbon Urban Transition Theory

This paper examines the early phases of a 21st century energy transition that involves distributed generation technologies employing low or zero carbon emission power sources and their take-up within Australia, with particular reference to the major cities and solar photovoltaics (PV). This transition is occurring in a nation with significant path dependency to overcome in relation to fossil fuel use. Tracking the diffusion of solar PV technology within Australia over the past decade provides a basis for assessing those factors underpinning its exponential growth and its associated geography of diffusion. Positive evidence that there are pathways for cities to decarbonise is apparent but there appear to be different pathways for different city forms with lower density suburban areas showing the biggest take-up of household-based energy technologies. This suggests a model for the low carbon urban transition involving combinations of simple technological changes and harder structural changes, depending upon which parts of the urban fabric are in focus. This is being called a New Low Carbon Urban Transition Theory.

National electricity planner and use of distributed energy sources in India

Abstract Indian electricity supply system mostly consists of a centralized, large and conventional generation system. Gradually, as the scenario of huge increase in demand as compared to generation was imposed on the system, the electric utilities have been restructured in various ways. With the restructuring process, the system operators are planning to implement alternative energy resources in the system. Nowadays, these resources are being utilized through small and modular energy conversion systems, known as distributed generation (DG) based on conventional and renewable energy resources. By implementing DG in the system, the environmental impact has been reduced along with the enhancement of reliability and quality in the power supply. Therefore, it is very important to choose DG at various locations in a country like India, because of varying weather conditions and resource availability. Determining DG options at different locations depends upon various attributes like economic, technical, environmental and resource availability, etc. Sometimes, it becomes difficult in part of authorities to arrive at a suitable decision on choosing the type of DG technology for a particular region or area. Overall Indian power system is divided into five broad regional grids viz., northern regional grid (NRG), eastern regional grid (ERG), southern regional grid (SRG), north eastern regional grid (NERG), western regional grid (WRG), operated and maintained by the respective regional load dispatch centers (RLDCs). The main objective of this work is to determine various DG technology options in each of the five regions in India with consideration of the above mentioned attributes. Analytic hierarchy process (AHP) has been used to identify the relative importance of the chosen attributes at various regions. Based on this, suitable DG options are determined.

Effective information channels for reducing costs of environmentally- friendly technologies: evidence from residential PV markets

Realizing the environmental benefits of solar photovoltaics (PV) will require reducing costs associated with perception, informational gaps and technological uncertainties. To identify opportunities to decrease costs associated with residential PV adoption, in this letter we use multivariate regression models to analyze a unique, household-level dataset of PV adopters in Texas (USA) to systematically quantify the effect of different information channels on aspiring PV adopters’ decision-making. We find that the length of the decision period depends on the business model, such as whether the system was bought or leased, and on special opportunities to learn, such as the influence of other PV owners in the neighborhood. This influence accrues passively through merely witnessing PV systems in the neighborhood, increasing confidence and motivation, as well as actively through peer-to-peer communications. Using these insights we propose a new framework to provide public information on PV that could drastically reduce barriers to PV adoption, thereby accelerating its market penetration and environmental benefits. This framework could also serve as a model for other distributed generation technologies.

Feasibility of Interconnected Distribution Network for the Integration of Distributed Energy Resources Using GA Approach

This paper envisages the feasibility of proposed power system configuration, which aspires at maximizing the electricity generation from green energy sources and furthermore to initiate the involvement of the consumers. Once the proposed distribution network configuration implemented, a power system based on distributed energy generation technologies is likely to be able to provide opportunities for sustainable development. Main objectives of the proposed network configuration are increased penetration of distributed generation (DGs) and decarbonization of electric utility. The IEEE-14 bus with proposed configuration has been simulated using MATLAB Simulink, which shows that interconnection of distribution networks allow the operation of centralized electricity generation and distributed energy generation efficiently. The outcomes of the proposed power system configuration have been compared with genetic algorithm based optimization approach

Analysis of the effect of distributed generation on life expectancy of power cables

Summary This paper presents a novel approach to quantify the effect of customer-owned distributed generation (DG) units on the life expectancy of power cables. Numerical results obtained from a realistic distribution system are presented and discussed under various scenarios, including different penetration levels of DG technologies. The results show that despite differences among various DG technologies, significant benefits can be realized in the area of power cable life extension, when DG units are installed by low-voltage customers. However, the extent of the benefits largely depends on the penetration level of DG units, the production pattern of DG technologies and the utilization factor of the analyzed cables. Copyright © 2013 John Wiley & Sons, Ltd.

Generic model of a community-based microgrid integrating wind turbines, photovoltaics and CHP generations

Development and deployment of low-carbon energy technologies has been a national strategy of both the UK and China for a number of years, including the use of renewable generation technologies and the improvement of energy efficiency of operations and activities. The paper addresses several issues of generic importance to a residential microgrid system such as network modelling, advanced control and integration of intelligent monitoring techniques. The system, comprising representative distributed generation technologies of photovoltaics, wind turbines and combined heat and power, has been simulated by PSCAD/EMTDC under different operational scenarios. Studies include the effect of environmental condition changes, control systems and power electronics on wind turbines and PV cells, and the mixture of wind/solar/CHP energy generation under dominance of each technology. The performance and dynamics of the system are examined against symmetrical and asymmetrical electrical faults to seek an optimal isolation and restoration of the distributed generation unit from the connected grid system. Modelling these system interactions has demonstrated the feasibility of the proposed residential microgrid system.

Barriers to the Expansion of Electrical Cogeneration by the Wood Products Industry in the United States

Cogeneration or combined heat and power (CHP) is a very efficient way to produce both useful process heat and electric power which provides a number of benefits to society including reduction in greenhouse (GHG) emissions which directly impacts climate change. Past efforts to promote energy efficiency and distributed generation technologies were supported by the Public Utility Regulatory Policy Act (PURPA). Under this policy, the nation experienced rapid growth of highly efficient and distributed energy generation facilities. Since the mid-1990s, a series of policy changes and regulatory barriers has stifled further growth of cogeneration facilities. This shift in public policy, for the most part, does not differentiate between cogeneration and merchant plants, that specifically limit the ability of cogeneration to provide additional social benefits to the United States. This article includes a review of the many new regulatory and other barriers which have developed over the years and makes recommendations to overcome them.