Allocation Of Distributed Energy Resources Research Articles

Modified African Buffalo for Optimal Accommodation of Distributed Energy Resources (DERs) for Annual Energy Loss Minimization in Active Distribution Systems

Abstract. The paper is acquainted with a new optimization technique. Modified African Buffalo optimization (MABO), to solve optimal Distributed Energy Resources (DERs) accommodation problem formulated for annual energy loss minimization esteeming multiple distributed generations and shunt capacitors contemporaneously. To demonstrate the proposed MABO, primitively, the optimal endowment of DERs is obtained for power loss minimization of benchmark 33 – bus test active distribution system (ADN) and simulation resultants are compared with well - established optimization techniques. The optimal DER allocation is also predetermined for depreciation of annual energy loss in conjuration with node voltage deviation over three different load levels. The simulation results obtained are further compared with some of the existing optimization methods. The two-level comparability of optimization methods shows that the Modified African Buffalo method has better searching potency to determine optimal solutions for optimal DERs allocation problems of ADN.

Bi-Level Optimization Model for DERs Dispatch Based on an Improved Harmony Searching Algorithm in a Smart Grid

To satisfy the large-scale grid-connected demands of distributed energy resources (DERs), a bi-level optimization model is proposed for private DER dispatch managed by a virtual power plant (VPP) in a smart grid environment in this paper. The optimization models of the upper and lower layers serve as the planning layer and the operational layer, respectively, wherein the upper optimization model is mainly aimed at the optimization allocation of DERs under an unchanged network topology, and the lower-level optimization model is mainly responsible for the optimization of the distributed network topology from the optimization results of the upper layer. An improved harmony searching algorithm (HSA) is then applied to resolve the model through continuous iterations and communications between the upper and lower levels until an expected aim is achieved, which can satisfy the aim demand of the upper and the lower levels at the same time. Finally, six optimization scenarios are planned and selected in order to evaluate the performance of the bi-level optimization strategy in the IEEE33 bus distribution system and the 69-bus distribution system, and the optimized results show that the proposed method can effectively improve the grid-connected capacity of DERs and their system performance, and are more flexible in facing a growing ambient smart environment.

Revenue-Based Allocation of Electricity Network Charges for Future Distribution Networks

This paper investigates the economic implications that high penetrations of distributed energy resources (DER) have in future distribution networks, and proposes a novel scalable scheme for the assignment of use of network charges based on individual participant nodes’ revenue. For validation purposes, a techno-economic simulation is proposed to understand how power and revenue flows will change. A year-long high-resolution quasi-static time series (QSTS) simulation, two price schemes, four trading environments, and four DER allocation methods from the literature are used to study economic benefits for individual participants and the supplier. Testing is performed using the IEEE 33-bus and 123-bus networks, and an Irish urban medium voltage feeder. Revenue flow is presented as an indicator of which participant nodes are profiting more from grid usage, and therefore should be responsible for greater network charges, this is validated against traditional and alternative schemes. Important reductions in use of network charges are seen especially by participant nodes with a higher PV generation-to-load and self-consumption rates. The proposed method is only relevant when dynamic tariffs are in place and/or local trading is enabled. Ultimately, results suggest that the income from network charges received by the supplier is increased when dynamic tariffs are used.

Comprehensive Low Voltage Microgrid Planning Methodology for Rural Electrification

Recently, DC-powered devices such as loads (USB plugs, chargers, LED lighting) and distributed energy resources (solar photovoltaic and battery energy storage) have been increasingly used. Therefore, their connection to the grid requires AC/DC converters, which raises the question of operating part of the grid in DC in order to connect DC loads to DC producers and storage. In Cambodia, the electrification rate is only about 82% of the population in 2021 in rural areas. The objective of this work is to propose a low voltage microgrid comprehensive planning tool for electrification of developing countries. From the data collected on consumption needs, the objective is to find the optimal electrification scheme, i.e., AC or AC/DC distribution, optimal topology and distributed energy resources allocation and operation for both grid-connected and off-grid mode. A set of technical, economic, and environmental key performance indicators allows for comparison of solutions. The interest and efficiency of such a tool are illustrated on a real case study, an island area. Moreover, uncertainties on load consumption are also considered to assess the sensitivity and robustness of the proposed algorithm. The results show that, although the overall cost of the hybrid AC/DC microgrid is slightly higher than that of the AC microgrid, it allows a gradual electrification avoiding large initial investments.

Two-stage Stochastic Programming for Coordinated Operation of Distributed Energy Resources in Unbalanced Active Distribution Networks with Diverse Correlated Uncertainties

This paper proposes a stochastic programming (SP) method for coordinated operation of distributed energy resources (DERs) in the unbalanced active distribution network (ADN) with diverse correlated uncertainties. First, the three-phase branch flow is modeled to characterize the unbalanced nature of the ADN, schedule DER for three phases, and derive a realistic DER allocation. Then, both active and reactive power resources are co-optimized for voltage regulation and power loss reduction. Second, the battery degradation is considered to model the aging cost for each charging or discharging event, leading to a more realistic cost estimation. Further, copula-based uncertainty modeling is applied to capture the correlations between renewable generation and power loads, and the two-stage SP method is then used to get final solutions. Finally, numerical case studies are conducted on an IEEE 34- bus three-phase ADN, verifying that the proposed method can effectively reduce the system cost and co-optimize the active and reactive power.

A Resilience-Oriented Methodology for Transformation of the Distribution Networks into MicroGrid

Transformation of the distribution network, integrated with Distributed Energy Resources (DER), into a MicroGrid (MG) is an attractive approach in improving the reliability and resilience of the network. In this paper, by introducing the important and necessary aspects of the MG formation problem, an effective methodology for transformation of a distribution network into the MG is proposed. In the presented methodology, optimal allocation of DERs within MG is obtained by optimization of power losses and voltage stabilization along feeders. Moreover, the short-circuit constraints are also taken into account simultaneously while allocating DERs. The reason for the latter is that the integration of DERs alters the amplitude and direction of the short circuit current, which can cause the overall fault current to exceed the designed fault-level capability of the circuit breakers. This issue may put CBs at risk of failure and degrading MG resilience. In this regard, resilience-oriented evaluation of the MG formation, from the perspective of considering short circuit level and coordination of OCRs, is also performed. Another advantage of short circuit studies is devising complete and economic overcurrent-based protection plan for MG in both operating modes (grid-connected and islanded). It should be pointed out that adopting an appropriate control routine is a key element in the MG formation. Hence, a control strategy, based on Energy Storage System (ESS) utilization, is suggested in this paper. This feature, which is another contribution of the paper, will guarantee seamless transition to island mode and stable operation of the MG. The proposed formulation of the MG formation is solved using a modified multi-objective PSO and the Pareto-optimal set is obtained. However, since the optimal solutions are nondominated to each other, a Fuzzy Satisfaction Method (FSM) is utilized to find the optimal solution among the Pareto-set. Utilization of the proposed methodology leads to the successful transformation of the distribution network into a MG, which not only considers the load flow constraints but also preserves the optimal coordination of the protective relays and resilience of the MG. In addition, seamless transition and stable operation of the MG in island mode is achieved.

A Probabilistic Conductor Size Selection Framework for Active Distribution Networks

With the increasing adoption of distributed energy resources (DERs) such as wind and solar photovoltaics (PV), many distribution networks have changed from passive to active. In turn, this has led to increased technical and operational challenges such as voltage issues and thermal loading in high DER penetration scenarios. These challenges have been further increased by the uncertainties arising from DER allocation. The implication of DER allocation uncertainty in the planning process is far-reaching as it affects critical planning processes, including conductor size selection (CSS). Most reported CSS methods in the literature do not include DER allocation uncertainty modeling as they are mostly deterministic and are set out as optimization problems. The methods, therefore, lack foresight on future loading conditions and cannot be used in a CSS process for feeders with high DER penetration. This paper proposes a novel input–process–output stochastic–probabilistic CSS framework for distribution feeders with DERs. The efficacy of the proposed framework is demonstrated using a low voltage feeder design case study with varying PV penetration targets, and the performance compared to deterministic–active-based estimates from our earlier work. The proposed CSS method is well-suited to the sizing of conductors for future loading conditions considering DER allocation uncertainty and will therefore be useful to planners working on new electrification projects.

Optimal DER allocation in meshed microgrids with grid constraints

We develop a new approach to model the linearized power flow in distributed energy resources (DER) allocation and dispatch optimization. The model uses the Decoupled Linearized Power Flow (DLPF) (Yang et al., 2016) approach. DLPF has the advantage of being suitable for meshed networks, while the majority of current models use LinDistFlow, which is only suitable for radial networks. First, we provide a validation of the DLPF voltage magnitude and branch power (in kVA) solutions compared to LinDistFlow and the true AC power flow (ACPF) solution for a meshed benchmark network, a 33-node system. We then formulate the DER allocation and dispatch problem as a mixed integer linear program (MILP) and use DLPF and LinDistFlow to model constraints on the electric power network infrastructure, which limits voltages to ANSI C84 standard limits. The model further uses polygon relaxations to limit kVA flows at the branches to their allowed thermal limit. We demonstrate the DLPF based DER allocation and dispatch model using a 115-node meshed circuit. Results indicate that the DLPF formulation is effective in capturing undervoltages and overvoltages in the meshed network, leading to optimal siting and sizing of photovoltaic (PV) and battery storage capacities. The DLPF model is then compared with a MILP that uses the LinDistFlow formulation, highlighting the importance of selecting the appropriate power flow linearization method.

A modified NSGA approach for optimal sizing and allocation of distributed resources and battery energy storage system in distribution network

The integration of distributed energy resources (DERs) causes fluctuation in system voltage, thus obstructing the voltage regulation and cause efficiency issue in performance of electrical network. This obstruction can overcome by proper sizing and allocation of DERs and battery energy storage system which in returns improves the performance of electrical power network. In this work, the optimal allocation of battery energy storage system and DERs has been proposed to reduce the voltage regulation issues. For this purpose, the modified non-sorting dominated genetic algorithm (NSGA) is used to optimally allocate and size the DERs and battery energy storage system. Furthermore, the results are compared with particle swarm optimization (PSO) in terms of power losses, voltage regulation and stability. It has been found that by utilizing modified non-sorting dominated genetic algorithm, the size of DER reduces and voltage profile improves as compared to particle swarm optimization (PSO). The simulations for particular modified NSGA have been performed on MATLAB software by keeping in mind the IEEE 33 bus system.

Optimal Distributed Energy Resources Allocation for Enriching Reliability and Economic Benefits Using Sine-Cosine Algorithm

This paper presents an optimization algorithm called sine-cosine algorithm (SCA) for optimal distributed energy resources (DERs) allocation in various configurations of radial distribution networks. This study is demonstrated in two statuses to find the optimal locations and sizes of DERs to be installed on the distribution system. First status; the most candidate locations for connecting DERs are suggested by using the loss sensitivity factor theory and the proposed SCA is applied to select the optimal capacities of DERs. Second status; the SCA is used to determine both the optimal locations and sizes of DERs. The positive impact of DERs on distribution systems reliability has been investigated in addition to the system power losses and bus voltages. The fitness function is to maximize the savings produced by not only power losses reduction but also reliability enhancement. The proposed algorithm is applied to IEEE 33 and 69-bus radial distribution networks with installing different number of DERs. The simulation results using Matlab programming environment show that the proposed methodology is viable, supporting reliability as well as fulfilling the conventional objectives such as cost minimization, voltage profile improvement, system losses reduction. A comparison between SCA and other methods is introduced to verify the superiority of SCA where SCA fulfils the maximum saving and maximum reduction of power losses equals to 61.3% and 69.2% for IEEE 33-bus and 69-bus networks, respectively.

Fuzzy logic controller and game theory based distributed energy resources allocation

Energy management and demand control through conventional energy generation sources are challenging for energy providers. Distributed energy resources (DERs) allocation near load centers may provide a suitable solution. The main contribution of the paper improves the voltage profile and reduce the active and reactive power losses in the distribution network. DERs are integrated with IEEE 33 bus system using fuzzy logic controller (FLC) and game theory for two different cases with unity and 0.9 power factor (PF) and compares with conventional methods of integration (i.e., modified novel method, power loss sensitivity method, voltage sensitivity analysis method). The capacity of DERs is optimized by FLC with the help of three triangular input functions voltage profile, active power loss, and reactive power loss. The location of integration of DERs in the radial distribution network is identified by game theory. Game theory is a mathematical algorithm, the results of multiple runs of DERs integration with the desired capacity calculated by FLC, identify the location for integration. The results comparison of DERs integration with the proposed methodology and conventional method shows the effectiveness of the proposed methodology. The voltage profile of the IEEE 33 bus system is increased by 6.70% with unity PF and 7.10% with 0.9 PF most among the applied methodologies and reduce the active and reactive power losses for both unity and 0.9 PF cases.

A Resilience-Based Architecture for Joint Distributed Energy Resources Allocation and Hourly Network Reconfiguration

As a result of the recent innovations in the deployment of plug-in electric vehicles (PEVs), this technology can play an important role as a distributed energy resource in supplying the system demand of the power systems of the future. This paper introduces a methodology for optimal coordinated allocation of wind farms (WFs), energy storage systems, and PEV's parking lots considering demand response programs and hourly distribution network reconfiguration in normal and severe contingency conditions. In the proposed methodology, the participation of different types of loads is also examined. The objective function is to minimize the total costs of purchased power from the upstream network and WFs, along with the costs of commercial/industrial loads flexibility and residential loads curtailment. To validate the performance of the proposed methodology, it is implemented on the well-known IEEE 33-bus distribution test system. The simulation results validate the feasibility and effectiveness of the proposed approach.

Distributed Energy Resources Allocation Using Flower Pollination Algorithm in Radial Distribution Systems

Abstract To meet the increased load demand and improve the distribution network performance, it is necessary to use Distributed Generators (DGs) and shunt capacitors (SCs) simultaneously in the distribution network. In this paper, simultaneous allocation of distributed generators and shunt capacitors in the distribution system using flower pollination algorithm (FPA) is presented. The objectives are to reduce power loss and improve the voltage profile of the distribution system. The suitable nodes for DG and capacitor placement are identified by using the loss sensitivity factor (LSF) technique. FPA method determines the optimal size of the DGs and SCs. The method developed is studied on IEEE 33 bus test system and the results are compared with other methods.

Simultaneous allocation of distributed energy resource using improved particle swarm optimization

Smart grid initiatives require integrated solution for radial distribution networks (RDNs) to achieve their optimum performance. The optimal allocation of distributed energy resources (DERs), such as shunt capacitors and distributed generation, when integrated with distribution network reconfiguration (DNR), can achieve desired objectives of smart distribution systems. This paper addresses a multi-objective formulation for simultaneous allocation of DERs in RDNs to maximize annual savings by reducing the charges for annual energy losses, peak power losses and substation capacity release against the annual charges incurred to purchase DERs while maintaining better node voltage profiles and feeder current profiles. An improved particle swarm optimization (IPSO) method is proposed to overcome against the inherent tendency of local trappings in PSO. A node sensitivity-based guided search algorithm (GSA) is also suggested to enhance the overall performance of the optimizing tool. GSA virtually squeezes the problem search space without loss of diversity. Distribution networks are optimally reconfigured after optimally placing DERs. The proposed method is investigated on the benchmark IEEE 33-bus and 69-bus test distribution systems. The application results show that the proposed integrated approach is very useful for electric utilities to enhance their profits and stagger their future expansion plans.