Optimal Voltage Control Using an Equivalent Model of a Low-Voltage Network Accommodating Inverter-Interfaced Distributed Generators

The penetration of inverter-based distributed generators (DGs), which can control their reactive power outputs, has increased for low-voltage (LV) systems. The power outputs of DGs affect the voltage and power flow of both LV and medium-voltage (MV) systems that are connected to the LV system. Therefore, the effects of DGs should be considered in the volt/var optimization (VVO) problem of LV and MV systems. However, it is inefficient to utilize a detailed LV system model in the VVO problem because the size of the VVO problem is increased owing to the detailed LV system models. Therefore, in order to formulate and solve the VVO problem in an efficient way, in this paper, a new equivalent model for an LV system including inverter-based DGs is proposed. The proposed model is developed based on an analytical approach rather than a heuristic-fitting one, and it therefore enables the VVO problem to be solved using a deterministic algorithm (e.g., interior point method). In addition, a method to utilize the proposed model for the VVO problem is presented. In the case study, the results verify that the computational burden to solve the VVO problem is significantly reduced without loss of accuracy by the proposed model.11Ysciescopu

Schedule-Based Operation Method Using Market Data for an Energy Storage System of a Customer in the Ontario Electricity Market

A new operation method for an energy storage system (ESS) was proposed to reduce the electricity charges of a customer paying the wholesale price and participating in the industrial conservation initiative (ICI) in the Ontario electricity market of Canada. Electricity charges were overviewed and classified into four components: fixed cost, electricity usage cost, peak demand cost, and Ontario peak contribution cost (OPCC). Additionally, the online market data provided by the independent electricity system operator (IESO), which operates the Ontario electricity market, were reviewed. From the reviews, it was identified that (1) the portion of the OPCC in the electricity charges increased continuously, and (2) large errors can sometimes exist in the forecasted data given by the IESO. In order to reflect these, a new schedule-based operation method for the ESS was proposed in this paper. In the proposed method, the operation schedule for the ESS is determined by solving an optimization problem to minimize the electricity charges, where the OPCC is considered and the online market data provided by the IESO is used. The active power reference for the ESS is then calculated from the scheduled output for the current time interval. To reflect the most recent market data, the operation schedule and the active power reference for the ESS are iteratively determined for every five minutes. In addition, in order to cope with the prediction errors, methods to correct the forecasted data for the current time interval and secure the energy reserve are presented. The results obtained from the case study and actual operation at the Penetanguishene microgrid test bed in Ontario are presented to validate the proposed method

A Conservation Voltage Reduction Scheme for a Distribution Systems with Intermittent Distributed Generators

In this paper, a conservation voltage reduction (CVR) scheme is proposed for a distribution system with intermittent distributed generators (DGs), such as photovoltaics and wind turbines. The CVR is a scheme designed to reduce energy consumption by lowering the voltages supplied to customers. Therefore, an unexpected under-voltage violation can occur due to the variation of active power output from the intermittent DGs. In order to prevent the under-voltage violation and improve the CVR effect, a new reactive power controller which complies with the IEEE Std. 1547TM, and a parameter determination method for the controller are proposed. In addition, an optimal power flow (OPF) problem to determine references for the resources of CVR is formulated with consideration of the intermittent DGs. The proposed method is validated using a modified IEEE 123-node test feeder. With the proposed method, the voltages of the test system are maintained to be greater than the lower bound, even though the active power outputs of the DGs are varied. Moreover, the CVR effect is improved compared to that used with the conventional reactive power control methods

Schedule-Based Operation Method Using Market Data for an Energy Storage System of a Customer in the Ontario Electricity Market

A new operation method for an energy storage system (ESS) was proposed to reduce the electricity charges of a customer paying the wholesale price and participating in the industrial conservation initiative (ICI) in the Ontario electricity market of Canada. Electricity charges were overviewed and classified into four components: fixed cost, electricity usage cost, peak demand cost, and Ontario peak contribution cost (OPCC). Additionally, the online market data provided by the independent electricity system operator (IESO), which operates the Ontario electricity market, were reviewed. From the reviews, it was identified that (1) the portion of the OPCC in the electricity charges increased continuously, and (2) large errors can sometimes exist in the forecasted data given by the IESO. In order to reflect these, a new schedule-based operation method for the ESS was proposed in this paper. In the proposed method, the operation schedule for the ESS is determined by solving an optimization problem to minimize the electricity charges, where the OPCC is considered and the online market data provided by the IESO is used. The active power reference for the ESS is then calculated from the scheduled output for the current time interval. To reflect the most recent market data, the operation schedule and the active power reference for the ESS are iteratively determined for every five minutes. In addition, in order to cope with the prediction errors, methods to correct the forecasted data for the current time interval and secure the energy reserve are presented. The results obtained from the case study and actual operation at the Penetanguishene microgrid test bed in Ontario are presented to validate the proposed method

A Vector-Controlled Distributed Generator Model for a Power Flow Based on a Three-Phase Current Injection Method

This paper proposes a vector-controlled distributed generator (DG) model for a power flow based on a three-phase current injection method (TCIM). In order to represent the DG models in the power flow, steady-state phase current output equations are formulated. Using these equations, the TCIM power flow formulation is modified to include the DG models. In the proposed power flow, a DG-connected bus is modeled as either a load bus (PQ bus) or a voltage-controlled bus (PV bus), depending on the control mode of the reactive power. However, unlike conventional bus models, the values of the DG-connected bus models are represented by three-phase quantities: three-phase active and reactive power output for a PQ bus, and three-phase active power and positive-sequence voltage for a PV bus. In addition, a method is proposed for representing the reactive power limit of a voltage-control-mode DG by using the q-axis current limit. Utilizing a modified IEEE 13-bus test system, the accuracy of the proposed method is verified by comparison to the power systems computer aided design (PSCAD) model. Furthermore, the effect of the number of DGs on the convergence rate is analyzed, using the IEEE 123-bus test system

Indirect Load Control for Energy Storage Systems Using Incentive Pricing under Time-of-Use Tariff

Indirect load control (ILC) is a method by which the customer determines load reduction of electricity by using a price signal. One of the ILCs is a time-of-use (TOU) tariff, which is the most commonly used time-varying retail pricing. Under the TOU tariff, the customer can reduce the energy cost through an energy storage system (ESS). However, because this tariff is fixed for several months, the ESS operation does not truly reflect the wholesale market price, which could widely fluctuate. To overcome this limitation, this paper proposes an incentive pricing method in which the load-serving entity (LSE) gives the incentive pricing signal to the customers with ESSs. Because the ESS charging schedule is determined by the customer through ILC, a bilevel optimization problem that includes the customer optimization problem is utilized to determine the incentive pricing signal. Further, the bilevel optimization problem is reformulated into a one-level problem to be solved by an interior point method. In the proposed incentive scheme: (1) the social welfare increases and (2) the increased social welfare can be equitably divided between the LSE and the customer; and (3) the proposed incentive scheme leads the customer to voluntarily follow the pricing signal

Coordinated Control of a DG and Voltage Control Devices Using a Dynamic Programming Algorithm

This paper presents a new control method, in which a distributed generator (DG) actively participates in steady-state voltage control, together with an under-load tap changer (ULTC) and shunt capacitors (Sh.Cs). In the conventional DG control method, the integration of DGs into a distribution power system increases the number of switching operations of the ULTC and the Sh.Cs. To solve this problem, this paper proposes that the DG output voltage be dispatched cooperatively with the operation of the ULTC and the Sh.Cs, based on load forecasts for one day in advance. The objective of the proposed method is to decrease the number of switching device operations, as well as to reduce the power loss in the distribution lines, while maintaining the grid voltage within the allowed range. The proposed method is designed and implemented with MATLAB, using two different dynamic programming algorithms for a dispatchable and a nondispatchable DG, respectively. Simulation studies demonstrate that the objective can be achieved under various grid conditions, determined by factors such as the DG output power characteristics, the location of the DG-connected bus on the feeder, and the load profile of the feeder containing the DG.11Nsciescopu