Hourly Reconfiguration Research Articles

Distribution network reconfiguration and reactive power compensation using a hybrid Simulated Annealing – Minimum spanning tree algorithm

Change of the climate, environmental pollution and lack of classical energy sources forced many countries to address renewables. In modern strategies of smart distribution network reconfiguration should be applied in order to minimize power losses and economic costs. Also, capacitors switching (placement of shunt capacitors) and presence of distribution generation are always incorporated in modern networks. Further, On Load Tap Changer in the supplying substation has to be used. Simulated Annealing and Minimum spanning tree algorithms work separately in order to find the best appropriate solution. The main goals are minimization of power losses and costs. In addition, many constraints are attended to find the hourly reconfiguration and capacitor banks position. Distributed generators involve both wind generators and solar panels. Two methods described in literature are mixed and implemented for locating fixed nodes for distributed generators. Gauss and Weibull changing nodal loads and wind generators output respectively, as well as daily load curves for working and weekend day with insolation of solar panels are included in analysis. Per unit load diagrams are determined according to real one-year measurement results in one substation in Belgrade, Serbia. IEEE 69 bus network is analyzed. The main contribution of exposed research is near optimal solution for wide time range, realistic network operation/planning forecast (stochastic variation of consumption and production on hour basis) with satisfaction of all technical constraints that are minimum and maximum nodal voltages, limiting feeder’s capacities and not-overcompensation of the network, accompanied with elaborate economic background.

Risk‐based optimal operation of coordinated natural gas and reconfigurable electrical networks with integrated energy hubs

This paper elaborates on optimal scheduling of coordinated power and natural gas (NG) networks in the presence of interconnected energy hubs considering reconfiguration as a flexibility source. With regard to the energy hub system consisting of several generation units, storage and conversion technologies, as well as natural gas-fired units, the high interdependency between gas and electricity carriers should be captured. The hourly reconfiguration capability is developed for the first time in a multi-energy system to enhance the optimal power dispatch and gas consumption pattern. The realistic interdependency of electrical and NG grids is investigated by employing the steady-state Weymouth equation and AC-power flow model for power and gas networks, respectively. Furthermore, to handle the risk associated with strong uncertainty of wind power, load, and real-time power price, the conditional value at risk approach is employed. The proposed model is implemented on the integrated test system and simulation results are presented for different cases. The impact of the risk aversion level on operating cost and optimal scheduling of controllable units is examined. Numerical results demonstrate that reconfigurable capability reduces the operational cost up to 7.82%.

A novel hybrid two-stage framework for flexible bidding strategy of reconfigurable micro-grid in day-ahead and real-time markets

Microgrids are going to be used in future intelligent grids as a promising technology to enable widespread utilization of renewable energy sources in a highly efficient and reliable manner. It is known that reconfiguration of micro-grids, using tie-line and sectionalizing switches, can provide more operational flexibility. Additionally, coordinated scheduling of flexible loads and energy storage systems can play an important role in the optimal scheduling of micro-grids; thus lowering the costs. This paper proposes an optimal bidding strategy for a micro-grid in day-ahead and real-time markets, based on AC power flow model, considering the hourly reconfiguration of the micro-grid. Fuel cell-based hydrogen energy storage and multiple shiftable loads are considered in the proposed method according to the load’s activity schedule. A reconfigurable micro-grid incorporates energy production and consumption of its local components to trade power in both day-ahead and real-time markets in order to maximize its profit as a private entity. The bidding problem faces issues due to the high level of uncertainties, consisting of wind power generation and electric load as well as variations of market prices. A hybrid two-stage bi-level optimization model is proposed to manage such uncertainties so that wind power, load demand, and day-ahead market prices are handled through scenario-based stochastic programming, and an information gap decision theory is applied to model the uncertainty of real-time market prices under two strategies, namely risk-seeker and risk-averse. The numerical simulation results confirm the effectiveness of the proposed model.

Optimal distribution systems operation in the presence of wind power by coordinating network reconfiguration and demand response

This paper discusses the optimal distribution system operation in the presence of wind power by coordinating network reconfiguration and demand response method. Under the specific demand response program, the paper proposes an optimal control method of coordinating thermostatically controlled load (TCL) and battery energy storage (BES). The TCL of the demand response can be controlled in the premise of not hurting customer comfort. The risk of exceeding thermal customer comfort limit is measured by conditional value-at-risk (CVaR) index. Under the requirement of timely wind power balancing, the hourly reconfiguration plan is adopted. Because of the stochastic characteristics of wind power, this is a risk-constrained optimization problem with the objective of minimizing operation cost. Due to the time interdependence of wind power, a Markov Decision Process (MDP) formulation in combination with dynamic programming is adopted to solve the multi-stage stochastic optimization problem. The results show that coordinating reconfiguration and demand response method could significantly contribute to compensating for the forecast error of wind power, therefore, bringing considerable economic savings on operation cost in real-time electricity market.

Fuzzy Adaptive Granulation Multi-Objective Multi-microgrid Energy Management

This paper develops an energy management approach for a multi-microgrid (MMG) taking into account multiple objectives involving plug-in electric vehicle (PEV), photovoltaic (PV) power, and a distribution static compensator (DSTATCOM) to improve power provision sharing. In the proposed approach, there is a pool of fuzzy microgrids granules that they compete with each other to prolong their lives while monitored and evaluated by the specific fuzzy sets. In addition, based on the hourly reconfiguration of microgrids (MGs), granules learn to dispatch cost-effective resources. To promote interactive service, a well-defined, multi-objective approach is derived from fuzzy granulation analysis to improve power quality in MMGs. A combination of the meta-heuristic approach of genetic algorithm (GA) and particle swarm optimization (PSO) eliminates the computational difficulty of the nonlinearity and uncertainty analysis of the system and improves the precision of the results. The proposed approach is successfully applied to a 69-bus MMG test with results reported in terms of stored energy improvement, daily voltage profile improvement, MMG operations, and cost reduction.

CHOICE OF SHORT-TERM CONSTANT CONFIGURATION OF THE DISTRIBUTION NETWORK

The work studies a possibility of choice for a given interval of changing the load power and the capacity of renewable generation sources of such a constant configuration of the primary distribution network, at which the energy losses differ minimally from the losses at the optimal hourly reconfiguration The study was carried out using the fast algorithm of the primary distribution network reconfiguration by the losses minimization criterion that was worked out by the authors. The algorithm efficiency is proved by comparing the results obtained on study basis with the results of other methods. After emergency cut-out of the sectionalizing switch the reconfiguration algorithm based on the methods known in the graph theory allow us to determine the line switch required for restoration. For the final choice of such switches feasibility of the post-emergency is tested and the controls are chosen, if the conditions are not met. The work of the proposed methods is demonstrated by the example of the 33 nodal IEEE scheme.

D-FACTS Cooperation in Renewable Integrated Microgrids: A Linear Multiobjective Approach

This study proposes a multiobjective approach for daily scheduling of microgrids (MGs) contributing to a higher penetration of photovoltaics (PVs). In this process, the existing control devices including distribution flexible ac transmission system and under-load tap changer (ULTC) are integrated in Volt/VAr control process. Besides, the substantial role in enhancing the service quality, a proper support of reactive power by distribution static compensator annihilates the overvoltage/undervoltage issues and increases the power provision share of PVs. Thus, a higher monetary saving is attained. Moreover, a moderated tap changing operation of ULTC is noticed and the dispatchable distributed generations mainly participate in active power processes. In addition, the hourly reconfiguration of MG assists to a proper feeding path to higher dispatch of cost-effective resources and enhancing the technical metrics. The proposed approach is formulated within a mixed integer linear programming being tackled by an augmented ϵ-constraint method. Efficient linearization techniques are deployed to lower the computational burden of the problem. Detailed simulation studies are conducted to assess performance of the proposed approach.

Optimal simultaneous day-ahead scheduling and hourly reconfiguration of distribution systems considering responsive loads

This paper develops an optimal simultaneous hourly reconfiguration and day-ahead scheduling framework in smart distribution systems considering the operation of the protection devices. The objective function of the model is defined as the minimization of system’s costs in terms of the costs associated with the purchased power from the wholesale market as well as the distributed generation (DG) owners, cost of switching actions, power losses cost and the cost for implementation of demand response (DR) programs. Moreover, a novel switching index along with the maximum number of switching actions based on the switch ages and critical branches in the network is presented. Due to the nonlinearity and non-convexity nature of the problem, the proposed optimization problem is then solved using a metaheuristic approach based on particle swarm optimization (PSO). As the result of the optimization process, the optimal set-points of DGs and responsive loads together with the optimal radial configuration of the distribution system for each hour of the scheduling time horizon are determined. To investigate the effect of DR programs and hourly reconfiguration on the load profile of the system, different price-based DR actions combined with interruptible load programs are also considered. Moreover, to demonstrate the satisfactory performance of the proposed model, the IEEE 33-bus distribution test system is thoroughly interrogated.

A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

Due to the recent developments in the practical implementation of remotely controlled switches (RCSs) in the smart distribution system infrastructure, distribution system operators face operational challenges in the hourly reconfigurable environment. This paper develops a stochastic Model Predictive Control (MPC) framework for operational scheduling of distribution systems with dynamic and adaptive hourly reconfiguration. The effect of coordinated integration of energy storage systems and demand response programs through hourly reconfiguration on the total costs (including cost of total loss, switching cost, cost of bilateral contract with power generation owners and responsive loads, and cost of exchanging power with the wholesale market) is investigated. A novel Switching Index (SI) based on the RCS ages and critical points in the network along with the maximum number of switching actions is introduced. Due to nonlinear nature of the problem and several existing binary variables, it is basically considered as a Mixed Integer Non-Linear Programming (MINLP) problem, which is transformed into a Mixed Integer Linear Programming (MILP) problem. The satisfactory performance of the proposed model is demonstrated through its application on a modified IEEE 33-bus distribution system.

Minimizing the number of remotely controlled switches when the planning the reconfiguration of a primary distribution network

The work shows the possibility to select the permanent configuration of a primary distribution network at which power losses during a week with maximum load and during a week with minimum load the power losses would be close to losses at optimum hourly reconfiguration. Data on the mix of loop branches obtained during the reconfiguration algorithm operation is used for selecting the tie-switches that allow both the regime restoration after emergency opening of a sectionalized switch, and acceleration of this process, especially if the tie-switch is remotely-controlled. The IEEE 33-node test systems are used to demonstrate the proposed algorithms.

Value of Distribution Network Reconfiguration in Presence of Renewable Energy Resources

Proliferation of renewable energy resources in distribution networks has captured distribution companies' attention towards more active management tools. Thanks to the smart grid paradigm, hourly network reconfiguration, which is still among immature ideas, can bring the activeness required to handle fluctuating output of renewable resources. The aim of this study is to analyze the worthiness of the hourly reconfiguration in the presence of renewable energy resources. For doing so, a mathematical model is devised to minimize daily network losses via applying hourly reconfigurations. The model is a mixed integer second-order cone programming problem and is solved via MOSEK solver. The electrical demand variations as well as renewable power generation fluctuations during a day are taken into account. The proposed method is applied to the Baran 33-bus system and the results including a great deal of sensitivity analyses on key parameters are presented and discussed.

Online Reconfiguration Considering Variability Demand: Applications to Real Networks

This paper presents how the application of the minimal loss reconfiguration in distribution networks can help to evaluate online reconfiguration benefits, considering the time varying nature of loads, using daily load profiles in each node of the system. The emphasis in this evaluation is hourly reconfiguration in distribution systems, compared to fixed topologies, considering maximum and average demand of the system. The results of applications to two real systems show unexpectedly that hourly reconfiguration is not so effective, if compared to a simple maximum or average demand reconfiguration. These conclusions are based on the decrease of obtained losses and on the amount of commutations involved in the hourly reconfiguration process.