Distributed Generation Expansion Research Articles

Closed-Loop Interconnected Model of Multi-Inverter-Paralleled System and its Application to Impact Assessment of Interactions on Damping Characteristics

The influence of parameters on the damping characteristics in a multi-inverter-paralleled system is different from that in a single-inverter system, because of inverter interactions in a nonideal grid. To quantify the interaction degree and assess its impact on damping characteristics, this paper proposes a closed-loop interconnected model for multi-inverter-paralleled systems. The model can explain the impact mechanism of inverter interactions on system stability. Capacity expansion of inverter-based renewable distributed generation is taken as the background in this paper, and then, the proposed model is applied to assessing the influence of the collecting line length of the newly installed inverters on the overall system stability. The conclusion is that the damping of a multi-paralleled-inverter system in the medium frequency range degrades with the approaching of the lengths of the newly added line and the existing line. Therefore, to avoid damping degradation in capacity expansion scenarios, the length of the newly added line should be different from the length of existing lines or the parameters of new inverters should be readjusted. Simulation results are presented to verify the effectiveness of the proposed model and stability enhancement approaches.

Proposing a Dynamic Tender Mechanism for Distributed Generation Expansion Planning

Proposing a Dynamic Tender Mechanism for Distributed Generation Expansion Planning

Short-term risk management of electricity retailers under rising shares of decentralized solar generation

Electricity retailers face increasing uncertainty due to the ongoing expansion and self-consumption of unpredictable distributed generation in the residential sector. We analyze how increasing levels of households’ solar PV self-generation affect the short-term decision-making and associated risk exposure of electricity retailers in the German day-ahead and intraday markets. First, we develop a stochastic model accounting for correlations between solar load, residual load and price in sequentially nested wholesale spot markets across seasons and type of day. Second, we develop a computationally tractable two-stage stochastic mixed-integer optimization model to investigate the trading portfolio and risk optimization problem faced by retailers. Through conditional value-at-risk we assess the retailers’ profitability and risk exposure to different levels of PV self-generation by assuming different retail tariff schemes. We find risk-hedging trading strategies and tariffs to have greater impact in Summer and with low levels of residual load in the system, i.e. when the solar generation uncertainty affects more the households’ demand to be served and the wholesale spot prices. The study is innovative in unveiling the potential of dynamic electricity tariffs, which are indexed to spot prices, to sustain a high penetration of renewable energy source while promoting a fair risk sharing between retailers, regular consumers and prosumers (consumers with self-generation). Our findings have implications for electricity retailers facing load and revenue risks in wholesale spot markets, likewise for regulators and policy-makers interested in electricity market design.

Fault Section Estimation in Radial LVDC Distribution System Using Wavelet Transform

The demand for low voltage DC (LVDC) distribution systems is increasing due to the rapid development of power conversion technology, the increase of DC-based digital loads, and the expansion of DC-based distributed generation (DG). For the stable operation of the LVDC distribution system, it is necessary to develop a protection method. In this paper, the fault section is estimated using wavelet transform (WT) in LVDC distribution system. The fault section is classified into a DC line and a DC bus. The characteristics of fault current at each fault section part are analyzed in simple and actual LVDC system. Based on this analysis, the algorithm for fault section estimation is proposed using the detail component after performing WT. The results of fault section estimations are verified through various simulations using EMTP and MATLAB. The fault section estimation can be utilized in the development of protection schemes in LVDC distribution system.

A Methodological Approach to Assessing the Possible Effect of Distributed Generation Expansion on Regional Energy Supply Systems

One of the new challenges arising from the transition of the energy industry to the path of intelligent development is to assess the effect of distributed generation (DG) on the prospects for the development of regional energy supply systems. Such an assessment requires that the factors characterized by high uncertainty be taken into account. In this case, it is expedient to employ a combination of the optimization method with the Monte Carlo method. Such an approach has already been adopted in a model (computer program) developed at the Melentiev Energy Systems Institute, Siberian Branch of the Russian Academy of Sciences. This model is designed to determine the rational mix of new power plants (with investment risks assessed and factored in) and the likely cost of electricity generation in a given aggregated region. We propose using this model as a source of projected data for an approximate assessment of the DG expansion, given the projected conditions for the energy sector and electric power industry development. It may also provide the basis for an array of research tools for relevant studies. The new toolkit requires a more detailed representation of the administrative division and the inclusion of consumers with their sources of electric power generation in the generating capacity. Although such an estimate is approximate, it can give an overall idea of the extent to which the cost and demand for electricity may vary under different options for the DG expansion in a region.

Decision Support Framework for Resilience-Oriented Cost-Effective Distributed Generation Expansion in Power Systems

Resilience of electricity grids to rare but severely disruptive events, such as natural disasters, has emerged in recent years as an important aspect in power system planning. Development of resilience-oriented techniques are needed due to the limitations of reliability-oriented methods in addressing large unexpected outages. This article presents a novel decision analysis approach to enhance the resilience of a power distribution system by leveraging the distributed nature of solar photovoltaic (PV) and battery energy storage system (BESS) resources. The proposed decision-making framework uses an analytic hierarchy process to evaluate different possible allocations of PV and BESS resources to load buses for multiple contingencies based on resilience enhancement and cost. Each allocation plan provides the size of PV arrays and BESS units to be installed at each bus within the distribution system. A deterministic formulation ranks line outage scenarios based on unserved load. The tradeoff between cost and resilience is modeled via cost-effectiveness analysis (CEA) that indicates the preferability of each allocation plan. The main contribution of this article is the development of an adaptable and computationally feasible decision support framework to determine cost-effective configurations of PV arrays and BESSs for mitigating the effects of power line outage contingencies. To evaluate the proposed framework, a case study is carried out on the IEEE 33-bus radial distribution system. The results show that the proposed method can offer effective guidance to the planner for making informed investment decisions and achieving cost-effective resilience enhancement.

A novel branch current flow-based construction of microgrids

<span>An efficient procedure for defining the boundaries of microgrids in smart distribution systems during distributed generation expansion planning becomes an important consideration in constructing smart grids. A novel approach named "Modified Reverse Current Flow Method" is proposed in this paper to split a large radial distribution system into a required number of self-adequate microgrids. This cluster of microgrids will be capable of utilizing maximum power output of the distributed renewable energy generators and will act as highly reliable zones, during both islanded and grid-connected modes. This method is based on the trend reversal of the flow of current in the various parts of the circuit. This paper uses the practical machine operating curves of the distributed generators to calculate their reactive power output. For the considered distribution system, the proposed method is applied to find the optimal point of operation and the boundaries of microgrids. To bring out the superiority of this novel method, the improvement in reliability indices and economic savings of this method are compared with the results obtained using a similar method available in the literature. This method has several notable merits, namely, increased accuracy in the calculation of annual energy losses and the voltage profile. </span>

A novel approach for distributed generation expansion planning considering its added value compared with centralized generation expansion

Abstract Technological progress of distributed generation (DG) units, global approach to reduce the pollution emissions, and creating the opportunity for local investors to participate in the generation expansion investment, are some of the important reasons to involve the DG as an alternative option in the GEP. In this regard, expansion of the DG units compared to the expansion of centralized generation units should be evaluated economically and technically. Therefore, this paper proposes a novel approach for modeling the composite centralized and distributed generation expansion planning problem in the regulated power system. An integrated objective function is presented to involve the most important decision-making factors overall the power system. The purpose is to find the optimal combination of generation expansion created by power plants and DG units to minimize the total costs related to generation expansion, operation, maintenance, fuel, emission, distribution loss and expected energy not supplied, for the decision-making period. The proposed model reveals as a mixed integer nonlinear programming where, genetic algorithm is applied to find the optimal solution which contains the capacity, technology and operation strategy of non-stochastic DG units that will be optimally allocated into some distribution feeders. Results confirm the effectiveness and superiority of the proposed approach.

An equilibrium approach for modeling centralized and behind-the-meter distributed generation expansion

Power systems will face important structural changes in the near future due to the empowerment of consumers, who may resort on self-consumption, and reduce their purchases of electricity from the grid. The avoided costs of purchasing energy, as compared to the investment costs of installing their own self-generation capacity, could be one of the drivers of the consumers’ decision making. The system expansion will therefore result from the interaction of the traditional market agents, maximizing their profits by investing in and operating centralized generation assets, and the new active consumers, minimizing their expenses while meeting their energy needs. This paper presents a Nash equilibrium model that considers centralized and behind-the-meter distributed generation expansion, by representing the operation and investments decisions of both types of agents with their own conceptually different strategies. To simplify the resolution, the equilibrium model is transformed into an equivalent minimization problem from its Karush-Kuhn-Tucker conditions. The model application to Spain-like system case example allows to assess the impact of the network access-tariff (whether being mainly volumetric-based or power-based) and the impact of the big industrial market power on the generation expansion, for the time horizon 2019-2037.

A Methodological Framework to support Load Forecast Error Assessment in Local Energy Markets

Due to the expansion of small-scale distributed generation, residential consumers are evolving to active participants in energy markets. Concepts like Local Energy Markets (LEM) are designed to harvest flexibility of these prosumers and contribute to a stable power system operation. However, the stochastic nature of the consumption of households increases the difficulty of accurate forecasts and can lead to erroneous bids and penalty payments. State of the art load forecasting methods can reduce this error to a certain extend. Yet, for a systematic assessment of the implications of forecast errors, a method capable of generating forecast time series with defined errors is required. With this method, measures to decrease the implications of forecast errors (e.g., aggregation of participants) can be evaluated. In this paper, we introduce such a method based on nonlinear optimization. After an analysis of typically used error metrics and achieved forecast errors in the literature, the proposed method is evaluated using German household load profiles demonstrating similar statistical properties as found in the literature. Additionally, we show the application of the method to a LEM simulation case revealing that a participation of a household without flexible assets would only be profitable for forecast errors instead of accuracies below 30-40%.

An Approach for Impedance Matrix Computation Considering Phase Transposition on Distribution Lines

A renewed interest in phase frame analysis of distribution systems has surfaced in recent literature due to rapid expansion of grid-integrated distributed generation and non-linear loads, whose grid imbalance-increasing effects require more detailed analysis and modeling of distribution systems for their proper assessment. In this paper, under motivation of such recent usage of phase frame components, we propose analytical equations for N-phase neutral-equipped line admittance matrix under transposition assumption. By using the proposed equations, we evaluate precision losses caused by using the transposition assumption for modeling three-phase four-wire distribution lines. Moreover, differently from previous works, we validate the transposition assumption and the admittance matrix values obtained for various combinations of cable type and line geometry. A relevant reason for analyzing transposition assumption in more detail is the fact that it may be useful in distribution system computations, due to its advantageous decoupling of symmetrical components. In this sense, the present work provides additional discussion and illustrative evaluations of the line transposition assumption, which may be useful for analyzing its applicability under different circumstances.

Private investor-based distributed generation expansion planning considering uncertainties of renewable generations

Distributed generation expansion planning (DGEP) is one of the most important types of planning in power distribution networks. Most of the previous studies associated with the DGEP problem have been performed from the viewpoint of network owner, while the investment, sizing and siting of Distributed Generations (DGs) are mostly taken by the private sector. Therefore, DGEP problem in the viewpoint of private investors should be taken into special consideration. In this paper, attempts are made to propose a model for DGEP problem based on the private investor's viewpoint to meet their objectives and also, take the technical constraints of the distribution network into account, at the same time. In this light, the uncertainties of the renewable DGs have also been considered in the problem and the Hong's Two Point Estimate Method (HTPEM) is used to provide a solution for probabilistic load flow problem. The method presented in this paper has been applied to the modified 18-bus distribution network which has been derived from the 30-bus IEEE system.

Distributed Generation Harmonic Interaction in the Active Distribution Network

Significant increase of distributed generation (DG) presence and active distribution network (ADN) development cause changes in distribution network’s power quality (PQ), mostly in distorted system voltages and currents. This paper analyses harmonics generation from multiple DG types, such as solar and biogas power plants, and simulates harmonic interactions in ADN in order to identify potential PQ issues. Each harmonic source observed in this paper was modelled according to IEC 61 000 with the model parameters provided by power quality measurements in the real system on several DG power plants and passive consumer nodes. A harmonic load flow is performed on a detailed ADN model for different presumed DG expansion scenarios that indicate the complexity of the DG impact on the AND’s PQ. Quantitative and qualitative graphical presentation for cumulative and the most significant ADN nodes is given and the assessment for the potential ADN development based on PQ indices is proposed.

DG planning incorporating demand flexibility to promote renewable integration

The integration of demand flexibility in distributed generation (DG) planning either lacks accuracy or ignores the potential of the behaviour of consumers in promoting the integration of renewables. This study proposes a DG planning model coordinating demand flexibility, in which the DG expansion plan and the behaviour of consumers in demand response (DR) programmes are co-optimised for the highest social welfare and the optimal utilisation of renewable generation. Consequently, the supply cost is reduced by utilising higher renewable generation instead of buying electricity from the grid. A share of the cost savings is allocated to the consumers to encourage their participation in DR programmes. Simulation results show that the expansion capacity of renewable generation is increased by 7.4% compared with no demand flexibility incorporation, and the social welfare is increased by up to 13.5% compared with no DG installation and 3.1% compared with no demand flexibility incorporation. Besides, the DR programmes carried out in the distribution system interact with the DG expansion plan, and higher subsidy rates in DR programmes could further promote the integration of renewables.

Distributed Generation Expansion Planning Considering Load Growth Uncertainty: A Novel Multi-period Stochastic Model

Abstract – Distributed generation (DG) technology is known as an efficient solution for applying in distribution system planning (DSP) problems. Load growth uncertainty associated with distribution network is a significant source of uncertainty which highly affects optimal management of DGs. In order to handle this problem, a novel model is proposed in this paper based on DG solution, considering load uncertainty. This model is designed to minimize network costs including operation and losses. Genetic algorithm is used with the purpose of finding the optimal places, sizes as well as times for DGs. Load uncertainty is also modeled through Markov tree. To illustrate the effectiveness of the proposed model, it is tested in different scenarios considering the effects of the purchased power price, DG penetration factor and DG operation intervals. These scenarios are conducted in two different phases, with and without uncertainty and the results are then compared and discussed. Moreover, by considering load uncertainty in planning, planning models would be robust against network future load variations.

A new approach for DG planning at the viewpoint of the independent DG investor, a case study of Iran

Summary Over the last decade, distributed generation units have been proposed to provide a part of the required energy of end-use customers. In this paper, a comprehensive model is presented to perform the distributed generation expansion planning from the independent investor's viewpoint. The objective function is suggested based on the payback period and with considering the budget limit. The investment and operation costs are included in the problem. The investment cost consists of the costs of equipment, distribution line installation, upgrading of upstream substation, gas and water pipe installations, and land. The genetic algorithm is applied to determine the optimal technology, location, and size of the distributed generation units. The performance of the proposed model is evaluated via a realistic case study, and the effect of a bank loan is discussed in the numerical results. Finally, the impact of the investor's investment decisions on the power system is analyzed.

SoS-based multiobjective distribution system expansion planning

This paper coordinates the reconfiguration of distribution systems with the expansion problem while the potential of demand response (DR) programs and distributed generation (DG) units are modeled in the active distribution expansion planning. The concept of system of systems (SoS) is proposed to model the expansion of DGs that are owned by private investors. SoS is an efficient system consisting of some autonomous and heterogeneous systems with distinct objective functions. According to the concept of SoS, a decision-making paradigm is developed to determine the location, size, and time of DG investment made by a commercial agent, as well as the price of generated power. From the distribution company (DISCO) viewpoint, the proposed model is a multi-objective (MO) optimization problem. The first objective function is the net present value of the total investment and operation costs related to the network. The second objective function is a reliability index, i.e. the expected energy not-supplied (EENS). The uncertainty of load growth in future years is handled by using a scenario-based approach. The introduced problem is solved by using multi-objective particle swarm optimization (MOPSO) algorithm empowered with an innovative three-layer procedure that is provided to better manage the space of the decision variables. The first layer is based on PSO particles while the second and third layers are based on a sensitivity analysis. Finally, a standard 33-bus distribution system is utilized to obtain the simulation results that show the performance and advantages of the proposed method.

Analysis of Impacts of Superconducting Fault Current Limiter (SFCL) Placement on Distributed Generation (DG) Expansion

The placement of the superconducting fault current limiter (SFCL) can be utilized to accommodate the increasing integration of distributed generations (DGs) in a power system. The installation of DGs in a power system can affect the power flow and the fault current patterns. Substantial changes in fault currents can cause coordination problems among the overcurrent relays. SFCL placement is a possible approach for accommodating the DGs by locally limiting the fault currents resulting from the DGs, while maintaining the existing relay settings. This paper presents a systematic procedure for analyzing the impacts of SFCL placement on DG expansion, considering the relay coordination in power systems.

Fault ride through concept in low voltage distributed photovoltaic generators for various dispersion and penetration scenarios

The Distributed Generation expansion and its smooth integration in distribution networks have gained much interest over the last years. Particularly, the photovoltaic systems connected to the low voltage distribution networks, present noteworthy benefits for the energy markets and customers. Meanwhile, aiming to high penetration level, many issues emerge regarding their behavior under grid disturbances. In this paper, the concept of Fault Ride Through Capability (FRTC) is applied to low voltage distributed photovoltaic generators (DG-PV), aiming mostly to the coordinated design and control of their interfacing inverters, so as to successfully address the FRTC requirements. These design alterations are examined in combination with an appropriate control concept that improves the FRT behavior of the DG-PV units. In order to apply the proposed control, an energy storage system is deemed indispensable. Through load flow analysis, the impact of the DG-PV interfaced reactance value XDG is thoroughly investigated for various dispersion and penetration levels scenarios. Therefore, by applying the above control concept, a suitable selection of XDG can be reached, achieving so compliance with FRT limits without leading to extremely inverter overloading (during faults). Finally, it is shown that the wider dispersion of DG-PV units enhances their FRT compatibility.

Investigation on Voltage Sags Caused by DG Anti-Islanding Protection

This paper investigates the voltage sag caused by distributed generation anti-islanding protection. This is a new power-quality concern associated with distributed generation expansion. Anti-islanding protection aims to disconnect distributed generators immediately after the opening of a recloser. As a consequence, after the reclosing operation, voltage sag will occur in some parts of the distribution system, since the loads are energized immediately but the generators are no longer present. In this context, this work presents the findings on our investigations about this problem. The results show that the resulting voltage sag level can violate power-quality limits. Thus, a set of indices has been introduced to characterize the severity of the voltage sag, and a load flow-based method has been proposed to predict the phenomenon. Sensitivity studies are also conducted in order to identify some key factors that influence this type of voltage depression.