Academic literature on the topic 'Volt/Var optimisation'

Although the wide integration of advanced metering infrastructure on distribution network facilitates the application of volt/var optimisation (VVO) in real-time circumstance, the contradiction between heavy computation load and low solution efficiency is still a big challenge, thus the system scales investigated in the literature are limited. In this study, the full AC real-time VVO is formulated based on particle swarm optimisation (PSO) framework and direct approach (DA) power flow method, where all components, such as distributed generator and on-load tap changer transformer, are formulated and integrated into the iterative DA process. Since both PSO and DA are suitable for parallel implementation, the graphics processing unit (GPU) is introduced for acceleration in order to achieve the possibility for real-time application. All the solution process is executed by GPU with the well-established data structure and thread organisation pattern, resulting in high efficiency by guaranteeing coalesced access within each warp. Case studies are conducted on four systems with sizes ranging from 136-bus to 1760-bus. Solution accuracy and convergence property are validated by the popular open source package Matpower. Based on the results from solution efficiency comparison between CPU sequential, CPU parallel, and GPU parallel programs, the promise of the proposed parallel implementation scheme for practical application is established.

AbstractPower quality issues arise in electrical networks when variable renewable energy (VRE) is integrated into them due to their random and intermittent nature which depends on weather conditions and other factors. The variation of solar irradiance throughout the day affects the energy produced by solar panels and the integration of solar power into electrical networks will result in changes and fluctuations in the voltage profile of buses. Reactive power compensation is required to improve the bus voltage levels of the electrical network to be within the required limits and the optimal allocation of reactive power compensation devices in the network is a complex problem to be investigated for the optimum injection of reactive power to obtain better voltage profiles for the entire network. This research investigated the penetration of variable solar energy into an electrical network in terms of voltage and reactive power flow. A variety of literature was reviewed in the scope of reactive power management in power systems and a gap in addressing the optimal allocation of compensation devices in the IEEE-14 bus was addressed based on the proposed methods followed by discussions of the results in terms of voltage profiles and reactive power flow in the buses. The objective is to produce an output power of higher quality and reliability for the loads so that intermittent sources of renewable energy can be more competent with energy sources such as fossil fuels that do not depend on weather conditions. Integration of methods using compensation optimisation (optimal allocation of capacitors) and volt-var regulation (smart inverter) to improve the voltage profile that was dropped and the fluctuations after penetration of solar power were carried out. A solar bus with variable energy generation was connected to the IEEE-14 bus to study the voltage variations. This was executed by the power flow calculation module to determine the voltages and reactive power in the buses of the network. With the optimum allocation of the capacitors, the voltage levels in all weak buses of the IEEE-14 bus were increased to be between 0.95 p.u. and 1.05 p.u. which was the voltage specifications of the Malaysian Grid Code Requirements. The voltage for every weak bus in the IEEE-14 bus showed a rise of 5.7% from 7 a.m. to 12 p.m. With that, the volt-var function was used for reactive power regulation at the point of common coupling (PCC) and a reduction of voltage deviation of 2.828 to 1.3% in the IEEE-14 bus was observed. The average voltage profile of all buses managed to attain a value of 98.99% from 95.673% (with solar power) with the optimal allocation of capacitors and volt-var regulation. The beneficiaries of this project will be the Sustainable Energy Development Authority (SEDA) which administers the Net Energy Metering (NEM) scheme and Tenaga Nasional Berhad (TNB) which is the Malaysian multinational electrical company focused primarily on the generation, transmission, and distribution of electricity in Peninsular Malaysia. The Energy Commission and Ministry of Energy and Natural Resources are also beneficiaries as they carried out a competitive bidding programme for large-scale solar (LSS) known as the LSS@MEnTARI or LSSPV4 to attain bids for the development of around 1000 MW AC of LSS power plants to be operational in Malaysia by 2022. This work will also be beneficial in future research in planning reactive power compensation devices in networks of multiple VRE sources, communication, and coordinated control of smart inverters, and incorporation of these devices for smart grid applications.

Abstract The management and transmission networks is becoming increasingly complex due to the proliferation of renewables-based distributed energy resources (DER). Existing control systems for DER are based on static specifications from interdependent network connection documents. Such systems are inflexible and their maintenance requires concerted effort between grid stakeholders. In this paper we present a new supplementary control approach to increase the agility of the electricity grid. The ICT system that underlies smart grids has the potential to offer, by analogy with ICT based network management, a control plane overlay for the modern smart grid. Policy-based Network Management (PBNM) is widely deployed in managed telecoms networks. We outline how PBNM can augment the management of power and energy networks and report on our initial work to validate the approach. To configure the PBNM system, we have used text mining to derive connection parameters at the LV level. In our simulations, PBNM was used in collaboration with a Volt-VAr optimisation (VVO) to tune the connection settings at each DER to manage the voltage across all the buses. We argue that the full benefits will be realised when stakeholders focus on agreeing relatively stable high-level connection policies, the policies being refined dynamically, and algorithms such as VVO that set connection parameters so they are consistent with those high-level policies. Thus faults, power quality issues and regulatory infringement can be identified sooner, and power flow can be optimised.

With the more environmentally friendly smart grid initiatives during the past few years, intelligent operation and optimisation of the electricity distribution system have received an increasing attention in power system research worldwide. Power flow from the distribution substation to the customer can be optimised at Volt-Ampere-Reactive (VAR) level by reducing the reactive power. Distributed Generation (DG) and Renewable Energy Sources (RES) represent both the broadest potentials and the broadest challenges for intelligent distribution systems and smart grid control. In general, the flexibility envisaged by integrating RES during smart grid transformation is often surrounded by nonlinearities such as wave-form deformations caused by harmonic currents or voltages, which impliedly increase control system complexity. Therefore, conventional controllers presently implemented need to be re-engineered in order to solve power quality (PQ) problems therein. This work aims to improve the controllability of Distribution Static Compensators (DSTATCOMs) through the development of improved control systems using evolu- tionary computation enabled design automation and optimisation. The resultant Volt-VAR Control (VVC) optimises PQ in the presence of nonlinearities and uncertainties. It also aims at increasing overall system’s sensitivity to unconsidered parameters in the design stage like measurement noise, unmodelled dynamics and disturbances. This is otherwise known as the robustness of the system offering it with valuable potential for future smart grids control, which are anticipated to present more nonlinearities due to virtual power plant (VPP) configuration. According to European Project FENIX, a Virtual Power Plant (VPP) aggregates the capacity of many diverse Distributed Energy Resources (DER), it creates a single operating profile from a composite of the parameters characterizing each DER and can incorporate the impact of the network on aggregate DER output. To particularly solve PQ problems, two objectives are realised in this thesis. First, a non-deterministic evolutionary algorithm (EA) is adopted to generate optimum fuzzy logic controllers for DSTATCOMs. This design methodology extends the traditional computer-aided-design (CAD) to computer-automated-design (CAutoD), which provides a unified solution to diverse PQ problems automatically and efficiently. While realizing this objective, the prediction ability of the derivative term in a proportional and derivative (PD) controller is improved by placing a rerouted derivative filter in the feedback path to tame ensuing oscillations. This method is then replicated in a fuzzy PD scheme and is automated through the capability of a “generational” tuning using evolutionary algorithm. Fuzzy logic controllers (FLCs) are rule-based systems which are designed around a fuzzy rule base (RB) related through an inference engine by means of fuzzy implication and compositional procedures. RBs are normally formulated in linguistic terms, in the form of if ... then rules which can be driven through various techniques. Fundamentally, the correct choice of the membership functions of the linguistic set defines the performance of an FLC. In this context, a three rule-base fuzzy mapping using Macvicar-Whelan matrix has been incorporated in this scheme to reduce the computational cost, and to avoid firing of redundant rules. The EA-Fuzzy strategy is proven to overcome the limitation of conventional optimisation which may be trapped in local minima, as the optimisation problem is often multi-modal. The second objective of the thesis is the development of a novel advanced model-free predictive control (MFPC) system for DSTATCOMs through a deterministic non-gradient algorithm. The new method uses its “look-ahead” feature to predict and propose solutions to anticipated power quality problems before they occur. A describing function augmented DSTATCOM regime is so arranged in a closed-loop fashion to locate limit cycles for settling the systems nonlinearities in a model-free zone. Predictive control is performed upon the online generated input-output data-set through the power of a non-gradient simplex algorithm. The strategy is to boycott the usage of a system model which is often based on gradient information and may thus be trapped in a local optimum or hindered by noisy data. As a model-free technique, the resultant system offers the advantage of reduction in system modelling or identification, which is often inaccurate, and also in computational load, since it operates directly on raw data from a direct online procession while at the same time dealing with a partially known system normally encountered in a practical industrial problem. Steady-state and dynamic simulations of both control and simulation models in Matlab/Simulink environment demonstrate the superiority of the new model-free approach over the traditional trial-and-error based methods. The method has been varified to offer faster response speed and shorter settling time at zero overshoot when compared to existing methods. A SimPowerSystems software simulation model is also developed to check experimental validity of the designs. Where specific PQ problems such as harmonics distortion, voltage swells, voltage sags and flicker are solved. A noticeable record level of THD reduction to 0.04% and 0.05% has respectively been achieved. It is therefore safe to recommend to the industry the implementation of this model-free predictive control scheme at the distribution level. As the distribution system metamorphoses into decen- tralised smart grid featuring connectivity of virtual power plants mostly through power electronic converters, e.g., DSTATCOM, it stands to benefit from the full Volt-VAR automated controllability of the MFPCs low control rate. Based on CAutoD, the practical implementation of this technique is made possible through digital prototyping within the real-time workshop to automatically generate C or C++ codes from Simulink, which executes continuous and discrete time models directly on a vast range of computer applications. Its overall wired closed-loop structure with the DSTATCOM would offer reliable and competitive advantages over its PID and SVC (CAD-based) counterparts currently being implemented through physical prototyping, in terms of; quick product-to-market pace, reduced hardwire size, small footprint, maintenance free as it is model-free (and automated), where pickling the controller timers and model contingencies are unnecessary as would be with the conventional controllers. More importantly, the scheme performs the aforementioned control functions robustly at a high speed in the range of 0.005 → 0.01 seconds. High enough to capture and deal with any ensuing PQ problem emanating from changes in customer’s load and system disturbances in an environmentally friendly, but less grid-friendly renewable generators.