It is widely accepted that renewable energy sources are the key to a sustainable energy supply infrastructure since they are both inexhaustible and nonpolluting. A number of renewable energy technologies are now commercially available, the most notable being wind power, photovoltaic, solar thermal systems, biomass, and various forms of hydraulic power. In this paper, a methodology has been proposed for optimally allocating different types of renewable distributed generation (DG) units in the distribution system so as to minimize annual energy loss. The methodology is based on generating a probabilistic generation-load model that combines all possible operating conditions of the renewable DG units with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer nonlinear programming (MINLP), with an objective function for minimizing the system's annual energy losses. The constraints include the voltage limits, the feeders' capacity, the maximum penetration limit, and the discrete size of the available DG units. This proposed technique has been applied to a typical rural distribution system with different scenarios, including all possible combinations of the renewable DG units. The results show that a significant reduction in annual energy losses is achieved for all the proposed scenarios.

Although wind power as a renewable energy is assumed to be an advantageous source of energy, its intermittent nature causes difficulties especially in the islanding mode of operation. Conventional synchronous generators can help to compensate for wind fluctuations, but the slow behavior of such systems may result in stability concerns. Here, the virtual inertia method, which imitates the kinetic inertia of synchronous generator, is used to improve the system dynamic behavior. Since the proposed method focuses on short-term oscillations and incorporates no long-term power regulation, it needs no mass storage device. Thus, the method is economical. To prevent any additional cost, the rotating mass connected to the DFIG shaft or a super-capacitor connected to the DC-link of a back-to-back inverter of a wind power generator could be used. The concept and the proposed control methods are discussed in detail. Eigen-value analysis is used to study how the proposed method improves system stability. The advantages and disadvantages of using DFIG rotating mass or super-capacitor as the virtual inertia source are compared. The proposed approach also shows that while virtual inertia is not incorporated directly in long-term frequency and power regulation, it may enhance the system steady-state behavior indirectly. A time domain simulation is used to verify the results of the analytical studies.

Environmental concerns and fuel cost uncertainties associated with the use of conventional energy sources have resulted in rapid growth in the amount of wind energy connected to distribution grids. However, based on Ontario's standard offer program (SOP), the utility has the right to curtail (spill) wind energy in order to avoid any violation of the system constraints. This means that any increase in wind energy production over a specific limit might be met with an increase in the wind energy curtailed. In spite of their cost, energy storage systems (ESSs) are considered to be a viable solution to this problem. This paper proposes a methodology for allocating an ESS in a distribution system with a high penetration of wind energy. The ultimate goal is to maximize the benefits for both the DG owner and the utility by sizing the ESS to accommodate all amounts of spilled wind energy and by then allocating it within the system in order to minimize the annual cost of the electricity. In addition, a cost/benefit analysis has been conducted in order to verify the feasibility of installing an ESS from the perspective of both the utility and the DG owner.

Recently, integration of distributed generation (DG) in distribution systems has increased to high penetration levels. The impact of DG units on the voltage stability margins has become significant. Optimization techniques are tools which can be used to locate and size the DG units in the system, so as to utilize these units optimally within certain limits and constraints. Thus, the impacts of DG units issues, such as voltage stability and voltage profile, can be analyzed effectively. The ultimate goal of this paper is to propose a method of locating and sizing DG units so as to improve the voltage stability margin. The load and renewable DG generation probabilistic nature are considered in this study. The proposed method starts by selecting candidate buses into which to install the DG units on the system, prioritizing buses which are sensitive to voltage profile and thus improve the voltage stability margin. The DG units' placement and sizing is formulated using mixed-integer nonlinear programming, with an objective function of improving the stability margin; the constraints are the system voltage limits, feeders' capacity, and the DG penetration level.

Recent development in small renewable/clean generation technologies such as wind turbines, photovoltaic, fuel cells, microturbines and so on has drawn distribution utilities' attention to possible changes in the distribution system infrastructure and policy by deploying distributed generation (DG) in distribution systems. In this study, a methodology has been proposed for optimally allocating wind-based DG units in the distribution system so as to minimise annual energy loss. The methodology is based on generating a probabilistic generation–load model that combines all possible operating conditions of the wind-based DG units and load levels with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer non-linear programming (MINLP), with an objective function for the system's annual energy losses minimise. The constraints include voltage limits at different buses (slack and load buses) of the system, feeder capacity, discrete size of the DG units, maximum investment on each bus, and maximum penetration limit of DG units. This proposed technique is applied to a typical rural distribution system and compared to the traditional planning technique (constant output power of DG units and constant peak load profile).

A new formulation is required to provide a proper power flow analysis in islanded microgrids taking into consideration their special philosophy of operation. In this paper, a novel and generic three-phase power flow algorithm is formulated for islanded microgrids. The algorithm is novel since it adapts the real characteristics of the islanded microgrid operation; i.e., 1) some of the distributed generation (DG) units are controlled using the droop control methods and their generated active and reactive power are dependent on the power flow variables; 2) the steady-state system frequency is considered as one of the power flow variables. The proposed algorithm is generic, where the features of distribution systems, i.e., three-phase feeder models, unbalanced loads and load models have been taken in consideration. Further, all possible operation modes of DG units (droop, PV, or PQ) have been considered. The problem has been formulated as a set of nonlinear equations. A globally convergent Newton-trust region method has been proposed to solve this set of nonlinear equations. The proposed algorithm is a helpful tool to perform accurate steady state studies of the islanded microgrid. Different case studies have been carried out to test the effectiveness and the robustness of the proposed algorithm.