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A constant or voltage-dependent load model is usually assumed in most distributed generation (DG) planning studies. However, this paper proposes several different types of time-varying voltage-dependent load models to determine the penetration level of photovoltaic (PV) units in a distribution network. Here, a new analytical expression is first proposed to size a PV unit, which can supply active and reactive powers. This expression is based on the derivation of a multiobjective index (IMO) that is formulated as a combination of three indices, namely active power loss, reactive power loss and voltage deviation. The expression is then adapted to allocate PV units while considering the time-varying load models and probabilistic PV generation. The effectiveness of the proposed approach was validated on 69- and 33-bus test distribution systems. The results showed that PV allocation with different types of time-varying load models can produce dissimilar penetration levels.

This paper proposes a strategy for optimal allocation of multiple Community Energy Storage (CES) units in a distribution system with photovoltaic (PV) generation. The main contribution of this strategy is it considers all possible benefits accrued from and costs incurred by CES deployment to a utility. The benefits are gained from energy arbitrage, peaking power generation, energy loss reduction, system upgrade deferral, emission reduction and VAr support. A cost-benefit analysis is also conducted to identify the optimal Net Present Value (NPV), Discounted Payback Period (DPP) and Benefit-Cost ratio (BCR). Moreover, an optimal power factor approach is included in the analysis to dispatch CES units to improve load factors and voltage profiles. The probabilistic distribution of solar irradiance is also incorporated in the proposed strategy to consider the uncertainty of PV generation. Several sensitivity analyses are carried out to investigate the effects of PV penetration, load models and the number of CES units deployed on the profitability of CES investment. Numerical results show that the proposed strategy enables a power utility to identify the location, size and operational characteristic of CES units for maximizing the total NPV and enhancing load factors and voltage profiles. (C) 2016 Elsevier Ltd. All rights reserved.

This paper presents a methodology for the integration of dispatchable and nondispatchable renewable distributed generation (DG) units for minimizing annual energy losses. In this methodology, analytical expressions are first proposed to identify the optimal size and power factor of DG unit simultaneously for each location for minimizing power losses. These expressions are then adapted to place renewable DG units for minimizing annual energy losses while considering the time-varying characteristics of demand and generation. A combination of dispatchable and nondispatchable DG units is also proposed in this paper. The proposed methodology has been applied to a 69-bus test distribution system with different scenarios. The results demonstrate that dispatchable DG units or a combination of dispatchable and nondispatchable DG units can lead to a substantial reduction in annual energy losses when compared to nondispatchable DG units. The results also show that a maximum annual energy loss reduction is achieved for all scenarios proposed with DG operation at optimal power factor. (C) 2013 Elsevier Ltd. All rights reserved.

The high penetration of distributed generation (DG) is a new challenge for traditional distribution systems. Power injections from DG units change network power flows, thereby influencing system losses and voltage stability. This paper presents a new multiobjective index (IMO)-based analytical approach to determine the optimal size and power factor of DG unit for reducing power losses and enhancing loadability. This index is defined as a combination of active and reactive power loss indices by optimally assigning a weight to each index such that the IMO can reach a minimum level. At this level, the optimal location and weights are identified. The proposed methodology has been tested on three typical distribution systems with different characteristics and validated using an exhaustive load flow (ELF) solution. The results show that DG operation with optimal power factor and appropriate weights for active and reactive power losses can significantly reduce power losses and enhance loadability.

Due to low electricity rates at nighttime, home charging for electric vehicles (EVs) is conventionally favored. However, the recent tendency in support of daytime workplace charging that absorbs energy produced by solar photovoltaic (PV) panels appears to be the most promising solution to facilitating higher PV and EV penetration in the power grid. This paper studies optimal sizing of workplace charging stations considering probabilistic reactive power support for plug-in hybrid electric vehicles (PHEVs), which are powered by PV units in medium voltage (MV) commercial networks. In this study, analytical expressions are first presented to estimate the size of charging stations integrated with PV units with an objective of minimizing energy losses. These stations. are capable of providing reactive power support to the main grid in addition to charging PHEVs while considering the probability of PV generation. The study is further extended to investigate the impact of time-varying voltage-dependent charging load models on PV penetration. The simulation results obtained on an 18-bus test distribution system show that various charging load models can produce dissimilar levels of PHEV and PV penetration. Particularly, the maximum energy loss and peak load reductions are achieved at 70.17% and 42.95% respectively for the mixed charging load model, where the system accommodates respective PHEV and PV penetration levels of 9.51% and 50%. The results of probabilistic voltage distributions are also thoroughly reported in the paper. (C) 2016 Elsevier Ltd. All rights reserved.

This paper investigates the loss reduction potential of primary distribution systems with distributed generation (DG) units, capacitors and network reconfiguration. A methodology is proposed to combine different types of DG units and capacitors for minimising losses. A combination of reconfiguration, DG and capacitor placement to obtain high loss reduction is also presented. The results obtained on a 33-bus test distribution system with constant load condition and a 687-bus real distribution system with varying load conditions show significant loss reduction using the proposed approach. The combination of type 1 DG (i.e. DG capable of delivering real power only) and capacitor placement or reconfiguration with type 1 DG and capacitor placement can be viable for minimising losses. © 2013, © 2013 Taylor & Francis.

This paper presents three alternative analytical expressions, including two new expressions, to determine the optimum sizes and operating strategy of distributed generation (DG) units considering power loss minimization and a methodology to identify the best location. These expressions can be easily adapted to consider the renewable DG units (i.e., biomass, wind and photovoltaic) for minimizing energy losses by considering time-varying demand and possible operating conditions of DG units. The results obtained on a 69-bus distribution test system demonstrate that the proposed approaches can be adequate to determine the location, size and power factor of DG unit for minimizing energy losses. The alternative expressions can be utilized depending on availability of required data and these produce similar outcomes. Highlights A methodology for different renewable DG allocation for energy loss minimization Three alternative analytical expressions for identifying the optimum size An analytical expression for calculating the optimum power factor

This paper investigates the problem of multiple distributed generator (DG units) placement to achieve a high loss reduction in large-scale primary distribution networks. An improved analytical (IA) method is proposed in this paper. This method is based on IA expressions to calculate the optimal size of four different DG types and a methodology to identify the best location for DG allocation. A technique to get the optimal power factor is presented for DG capable of delivering real and reactive power. Moreover, loss sensitivity factor (LSF) and exhaustive load flow (ELF) methods are also introduced. IA method was tested and validated on three distribution test systems with varying sizes and complexity. Results show that IA method is effective as compared with LSF and ELF solutions. Some interesting results are also discussed in this paper.

Energy Storage (ES) has been seen as a crucial element in active distribution networks. It facilitates a high penetration level of intermittent renewable energy in power systems thus provide several technical and economic benefits to the utility and consumer. However, given a high capital cost associated with ES, it is crucial to develop an effective planning strategy to avail the maximum benefit. This paper proposes a methodology to determine the optimal location and capacity of Community Energy Storage (CES) units by considering all their possible benefits and costs. The benefits are obtained from energy arbitrage, peaking power generation, energy losses reduction, Transmission and Distribution (TD) system upgrade deferral, CO2 emission reduction and VAr support, while the costs include CES's capital, replacement and Operational and Maintenance (OM) costs. A comprehensive cost-benefit analysis is conducted to identify the optimal Net Present Value (NPV), Discounted Payback Period (DPP) and Benefit Cost ratio (BCR) of CES investment starting at current year, year 2025 and 2035. Numerical results show that the proposed strategy is able to specify the optimal location and size of CES unit for maximizing the NPV. Some interesting findings are also discussed in the paper.

Energy Storage (ES) has become an important element in Active Distribution Networks (ADNs) due to progressive integration of renewable energy such as photovoltaic (PV). ES enables high penetration of intermittent PV while bringing several additional benefits to the network. Such benefits include loss reduction, voltage profile improvement and reverse power flow avoidance. This paper presents an analysis of energy loss reduction in a radial distribution network with PV units through load levelling using ES. Simulations are conducted using the GridLAB-D software tool. Analyses show that ES allocated close to the load achieves an energy loss reduction higher than that near the substation. Optimal ES capacity obtained through load leveling produces a maximum energy loss reduction. This capacity is adequate to bring the system load factor close to unity. It is also shown that distributed ES allocation can yield almost twice loss reductions higher than centralized ES placement. © 2015 IEEE.

This paper discusses the integration of solar photovoltaic (PV) and battery energy storage (BES) units for reducing energy loss and enhancing voltage stability. Here, each nondispatchable PV unit is converted into a dispatchable source with a combination of PV and BES units. New multiobjective index (IMO)-based analytical expressions are proposed to capture the size and power factor of the combination of PV and BES units. A self-correction algorithm (SCA) is also developed for sizing multiple PV and BES units while considering the time-varying demand and probabilistic generation. The power factors of PV and BES units are optimally dispatched at each load level. Results obtained on a 33-bus commercial distribution system show the validity of the proposed approach and algorithm for calculating the optimal size and power factor of multiple PV and BES units. The results show that operation of PV and BES units with optimal power factors can substantially reduce energy loss and better enhance voltage stability when compared to that with unity power factor. As a result of the tangible technical benefits, it may be appropriate for utilities to set up frameworks and standards for PV units operation at optimal power factor as the current IEEE 1547 standard only allows PV generation at unity power factor. (C) 2013 Elsevier Ltd. All rights reserved.

Renewable energy (i.e., biomass, wind and solar) and Battery Energy Storage (BES) are emerging as sustainable solutions for electricity generation. In the last decade, the smart grid has been introduced to accommodate high penetration of such renewable resources and make the power grid more efficient, reliable and resilient. The smart grid is formulated as a combination of power systems, telecommunication communication and information technology. As an integral part of the smart grid, a smart integration approach is presented in this thesis. The main idea behind the smart integration is locating, sizing and operating renewable-based Distributed Generation (DG) resources and associated BES units in distribution networks strategically by considering various technical, economical and environmental issues. Hence, the aim of the thesis is to develop methodologies for strategic planning and operations of high renewable DG penetration along with an efficient usage of BES units. The first contribution of the thesis is to present three alternative analytical expressions to identify the location, size and power factor of a single DG unit with a goal of minimising power losses. These expressions are easily adapted to accommodate different types of renewable DG units for minimizing energy losses by considering the time-varying demand and different operating conditions of DG units. Both dispatchable and non-dispatchable renewable DG units are investigated in the study. Secondly, a methodology is also introduced in the thesis for the integration of multiple dispatchable biomass and nondispatchable wind units. The concept behind this methodology is that each nondispatchable wind unit is converted into a dispatchable source by adding a biomass unit with sufficient capacity to retain the energy loss at a minimum level. Thirdly, the thesis studies the determination of nondispatchable photovoltaic (PV) penetration into distribution systems while considering time-varying voltage-dependent load models and probabilistic generation. The system loads are classified as an industrial, commercial or residential type or a mix of them with different normalised daily patterns. The Beta probability density function model is used to describe the probabilistic nature of solar irradiance. An analytical expression is proposed to size a PV unit. This expression is based on the derivation of a multiobjective index (IMO) that is formulated as a combination of three indices, namely active power loss, reactive power loss and voltage deviation. The IMO is minimised in determining the optimal size and power factor of a PV unit. Fourthly, the thesis discusses the integration of PV and BES units considering optimal power dispatch. In this work, each nondispatchable PV unit is converted into a dispatchable source by adding a BES unit with sufficient capacity. An analytical expression is proposed to determine the optimal size and power factor of PV and BES units for reducing energy losses and enhancing voltage stability. A self-correction algorithm is then developed for sizing multiple PV and BES units. Finally, the thesis presents a comprehensive framework for DG planning. In this framework, analytical expressions are proposed to efficiently capture the optimal power factor of each DG unit with a standard size for minimising energy losses and enhancing voltage stability. The decision for the optimal location, size and number of DG units is obtained through a benefit-cost analysis over a given planning horizon. Here, the total benefit includes energy sales, loss reduction, network investment deferral and emission reduction, while the total cost is a sum of capital, operation and maintenance expenses. The study reveals that the time-varying demand and generation models play a significant role in renewable DG planning. Depending on the characteristics of demand and generation, a distribution system would accommodate up to an estimated 48% of the nondispatchable renewable DG penetration. A higher penetration level could be obtained for dispatchable DG technologies such as biomass and a hybrid of PV and BES units. More importantly, the study also indicates that optimal power factor operation could be one of the aspects to be considered in the strategy of smart renewable DG integration. A significant energy loss reduction and voltage stability enhancement can be achieved for all the proposed scenarios with DG operation at optimal power factor when compared to DG generation at unity power factor which follows the current standard IEEE 1547. Consequently, the thesis recommends an appropriate modification to the grid code to reflect the optimal or near optimal power factor operation of DG as well as BES units. In addition, it is shown that inclusion of energy loss reduction together with other benefits such as network investment deferral and emission reduction in the analysis would recover DG investments faster.

This paper proposes a simple analytical strategy for distributed generation (DG) integration considering the benefit for distribution network operator (DNO) under the unbundled environment where DG units are owned by DG developers. This benefit arises from network reinforcement deferral and loss reduction due to optimal DG size and operating power factor. The optimal size and power factor are strategically calculated for each location to achieve the highest benefit using the analytical approach. A computational procedure is also developed to accommodate a predefined number of DG units using the proposed approach. The results obtained on a 69-bus test distribution system demonstrate the effectiveness of the proposed methodology and computational procedure. It is observed that the optimal power factor operation can achieve the maximum benefit for DNO, while achieving the optimum voltage profiles and maximizing DG penetration.

This paper presents a strategy for optimal operation of distributed generation (DG) unit for minimizing distribution system power losses. An analytical approach is used to determine the optimal size and power factor of DG unit when it is placed at various locations. A computational procedure is also developed to identify the best placement at which the total system loss is the lowest. The proposed approach has been tested on a 33-bus distribution system. Importance of operating DG unit at appropriate power factor (PF) for minimizing power losses is first highlighted using an exhaustive load flow solution. The developed method is then used to calculate the optimal power factor. The results demonstrate the validity of the proposed approach in terms of optimal power factor, loss reduction and computational time. It is also shown that the optimal power factor operation can minimize power losses while achieving the optimum voltage profile enhancement and maximizing DG penetration.

This paper investigates the potential of community energy storage (CES) and capacitor (C) placement in large-scale distribution networks for energy loss minimization. An analytical approach is proposed to identify the optimal location, size and power factor of CES units to reduce energy losses at the peak load level. This method is also applied to find the optimal location, size, type and control scheme of capacitors under load variations to obtain a high loss reduction. The combination of CES and capacitor allocation to achieve a higher loss reduction is also presented. The proposed approach was tested and validated on 15 and 69-bus distribution test systems. Results show that the combination of simultaneous CES and capacitor placement can lead to high energy loss reduction and efficient energy usage.

This paper proposes analytical expressions for finding optimal size and power factor of four types of distributed generation (DG) units. DG units are sized to achieve the highest loss reduction in distribution networks. The proposed analytical expressions are based on an improvement to the method that was limited to DG type, which is capable of delivering real power only. Three other types, e.g., DG capable of delivering both real and reactive power, DG capable of delivering real power and absorbing reactive power, and DG capable of delivering reactive power only, can also be identified with their optimal size and location using the proposed method. The method has been tested in three test distribution systems with varying size and complexity and validated using exhaustive method. Results show that the proposed method requires less computation, but can lead optimal solution as verified by the exhaustive load flow method. © 2006 IEEE.