Residential Demand Side Management model, optimization and future perspective: A review

The residential load sector plays a vital role in terms of its impact on overall power balance, stability, and efficient power management. However, the load dynamics of the energy demand of residential users are always nonlinear, uncontrollable, and inelastic concerning power grid regulation and management. The integration of distributed generations (DGs) and advancement of information and communication technology (ICT) even though handles the related issues and challenges up to some extent, till the flexibility, energy management and scheduling with better planning are necessary for the residential sector to achieve better grid stability and efficiency. To address these issues, it is indispensable to analyze the demand-side management (DSM) for the complex residential sector considering various operational constraints, objectives, identifying various factors that affect better planning, scheduling, and management, to project the key features of various approaches and possible future research directions. This review has been done based on the related literature to focus on modeling, optimization methods, major objectives, system operation constraints, dominating factors impacting overall system operation, and possible solutions enhancing residential DSM operation. Gaps in future research and possible prospects have been discussed briefly to give a proper insight into the current implementation of DSM. This extensive review of residential DSM will help all the researchers in this area to innovate better energy management strategies and reduce the effect of system uncertainties, variations, and constraints

A coordinated voltage regulation algorithm of a power distribution grid with multiple photovoltaic distributed generators based on active power curtailment and on-line tap changer

The aim of this research is to manage the voltage of an active distribution grid with a low X/R ratio and multiple Photovoltaic Distributed Generators (PVDGs) operating under varying conditions. This is achieved by providing a methodology for coordinating three voltage-based controllers implementing an Adaptive Neuro-Fuzzy Inference System (ANFIS). The first controller is for the On-Line Tap Changer (OLTC), which computes its adequate voltage reference. Whereas the second determines the required Active Power Curtailment (APC) setpoint for PVDG units with the aim of regulating the voltage magnitude and preventing continuous tap operation (the hunting problem) of OLTC. Finally, the last component is an auxiliary controller designed for reactive power adjustment. Its function is to manage voltage at the Common Coupling Point (CCP) within the network. This regulation not only aids in preventing undue stress on the OLTC but also contributes to a modest reduction in active power generated by PVDGs. The algorithm coordinating between these three controllers is simulated in MATLAB/SIMULINK and tested on a modified IEEE 33-bus power distribution grid (PDG). The results revealed the efficacy of the adopted algorithm in regulating voltage magnitudes in all buses compared to the traditional control method.Peer ReviewedPostprint (published version

Intelligent Decision Support System for Energy Management in Demand Response Programs and Residential and Industrial Sectors of the Smart Grid

This PhD thesis addresses the complexity of the energy efficiency control problem in residential and industrial customers of Smart electrical Grid, and examines the main factors that affect energy demand, and proposes an intelligent decision support system for applications of demand response. A multi criteria decision making algorithm is combined with a combinatorial optimization technique to assist energy managers to decide whether to participate in demand response programs or obtain energy from distributed energy resources

Energy storage systems and grid code requirements for large-scale renewables integration in insular grids

This thesis addresses the topic of energy storage systems supporting increased penetration of renewables in insular systems. An overview of energy storage management, forecasting tools and demand side solutions is carried out, comparing the strategic utilization of storage and other competing strategies. Particular emphasis is given to energy storage systems on islands, as a new contribution to earlier studies, addressing their particular requirements, the most appropriate technologies and existing operating projects throughout the world. Several real-world case studies are presented and discussed in detail. Lead-acid battery design parameters are assessed for energy storage applications on insular grids, comparing different battery models. The wind curtailment mitigation effect by means of energy storage resources is also explored. Grid code requirements for large-scale integration of renewables are discussed in an island context, as another new contribution to earlier studies. The current trends on grid code formulation, towards an improved integration of distributed renewable resources in island systems, are addressed. Finally, modeling and control strategies with energy storage systems are addressed. An innovative energy management technique to be used in the day-ahead scheduling of insular systems with Vanadium Redox Flow battery is presented.Esta tese aborda a temática dos sistemas de armazenamento de energia visando o aumento da penetração de energias renováveis em sistemas insulares. Uma visão geral é apresentada acerca da gestão do armazenamento de energia, ferramentas de previsão e soluções do lado da procura de energia, comparando a utilização estratégica do armazenamento e outras estratégias concorrentes. É dada ênfase aos sistemas de armazenamento de energia em ilhas, como uma nova contribuição no estado da arte, abordando as suas necessidades específicas, as tecnologias mais adequadas e os projetos existentes e em funcionamento a nível mundial. Vários casos de estudos reais são apresentados e discutidos em detalhe. Parâmetros de projeto de baterias de chumbo-ácido são avaliados para aplicações de armazenamento de energia em redes insulares, comparando diferentes modelos de baterias. O efeito de redução do potencial de desperdício de energia do vento, recorrendo ao armazenamento de energia, também é perscrutado. As especificidades subjacentes aos códigos de rede para a integração em larga escala de energias renováveis são discutidas em contexto insular, sendo outra nova contribuição no estado da arte. As tendências atuais na elaboração de códigos de rede, no sentido de uma melhor integração da geração distribuída renovável em sistemas insulares, são abordadas. Finalmente, é estudada a modelação e as estratégias de controlo com sistemas de armazenamento de energia. Uma metodologia de gestão de energia inovadora é apresentada para a exploração de curto prazo de sistemas insulares com baterias de fluxo Vanádio Redox

Analysis of Power Quality Constrained Consumer-Friendly Demand Response in Low Voltage Distributions Network

Load management using demand response (DR) in a low voltage distribution network (LVDN) offers an economically profitable business platform with peak load management. However, the inconvenience caused to the consumer in depriving their devices and the low levels of associated incentive have contributed to lower consumer acceptance for DR programs in the community. However, with the increasing number of controllable consumer loads, a residential-level DR program is highly plausible in the short to medium term. Further, additional DR capabilities (including ancillary services) are likely to improve the remuneration potential for participants in DR. Considering the perspective of a distribution network operator (DNO), any service useful for maintaining the stable and secure operation of an LVDN will always be appreciated. Thus, in addition to DR\u27s peak load management potential, any further contribution in maintaining power quality (PQ) in the network considered as an ancillary service to DNO will create a profitable business opportunity. Firstly, primary PQ management tasks in an LVDN are maintaining voltage profile and reducing harmonics. With the advancement in the consumer electronics market, increased penetration of nonlinear low carbon technologies (LCTs) based loads at the consumer-side, will increases the harmonic content in the LVDN. While consumer devices may have non-threatening levels of harmonic components, they can still cause issues by accumulating at the main feeder when the additive nature of harmonics are considered. Further, and in respect to harmonics, total harmonic distortion (THD), as a universal indicator, may not be a deterministic measure of the impact of harmonics due to THD’s dependency on the magnitude of fundamental current. Moving to the voltage issue, in an electrical network, it is required to maintain the voltage level of all nodes in the network between regulated tolerance levels. However, during peak load hours, the voltage at the end of a radial feeder may drop below the tolerance level. The corollary is also an issue. A light loading scenario on the same feeder with a higher penetration of solar photovoltaic distributed generators (SPVDG) injecting active power can create a voltage rise scenario. While consumer loads/loading are responsible for these PQ issues in the network, there is no direct obligation on residential level consumers to manage them as long as they are individually operating within the regulation limits. However, a DR option can utilize PQ’s dependency on loads to provide additional service to DNO to mitigate any PQ violations. The DR program\u27s success is critically dependent on consumer participation. It also becomes essential to operate the program with a minimum level of consumer inconvenience. Therefore, a proposal for micromanaging consumer load on an LVDN while considering consumer inconvenience and attaining PQ objectives is thus the theme of this thesis. This research proposes a PQ constrained consumer-friendly DR (PQ-C-DR) program that can provide additional ancillary PQ management services along with conventional DR capabilities. Due consideration is given to minimize consumer inconvenience while operating DR to ensure social acceptability and equity. Harmonic levels in the network are essentially integrated as harmonic heating constraints to maintain stable levels of harmonics in LVDN. A DR in conjunction with a co-ordinated incremental and ‘fair’ curtailment algorithm is introduced to manage the voltage levels in the radial LVDN. A sensitivity study of the proposed algorithm is performed on an urban distribution network model under different operating scenarios. This thesis introduces a new algorithmic dimension in applications for load management to ancillary services (PQ management) using DR. The PQ-C-DR will favour consumer comfort while profiting all stakeholders involved, which essentially creates a win-win scenario for all network participants – essential in DNO/consumer negotiations to achieve wider DR engagement. Improving the profitability of DR by providing additional service(s) is beneficial to both customers and retailers. Furthermore, the DNO benefits from delaying additional peak and PQ management related investments, which could essentially improve the utilization factor of the network

Towards ‘Smarter’ Systems: Key Cyber-Physical Performance-Cost Tradeoffs in Smart Electric Vehicle Charging with Distributed Generation

The growing penetration of electric vehicles (EV) into the market is driving sharper spikes in consumer power demand. Meanwhile, growing renewable distributed generation (DG) is driving sharper spikes in localised power supply. This leads to growing temporally unsynchronised spikes in generation and consumption, which manifest as localised over- or undervoltage and disrupt grid service quality. Smart Grid solutions can respond to voltage conditions by curtailing charging EVs or available DG through a network of cyber-enabled sensors and actuators. How to optimise efficiency, ensure stable operation, deliver required performance outputs and minimally overhaul existing hardware remains an open research topic. This thesis models key performance-cost tradeoffs relating to Smart EV Charging with DG, including architectural design challenges in the underpinning Information and Communications Technology (ICT). Crucial deployment optimisation balancing various Key Performance Indicators (KPI) is achieved. The contributions are as follows: • Two Smart EV Charging schemes are designed for secondary voltage control in the distribution network. One is optimised for the network operator, the other for consumers/generators. This is used to evaluate resulting performance implications via targeted case study. • To support these schemes, a multi-tier hierarchical distributed ICT architecture is designed that alleviates computation and traffic load from the central controller and achieves user fairness in the network. In this way it is scalable and adaptable to a wide range of network sizes. • Both schemes are modelled under practical latency constraints to derive interlocking effects on various KPIs. Multiple latency-mitigation strategies are designed in each case. • KPIs, including voltage control, peak shaving, user inconvenience, renewable energy input, CO2 emissions and EV & DG capacity are evaluated statistically under 172 days of power readings. This is used to establish key performancecost tradeoffs relevant to multiple invested bodies in the power grid. • Finally, the ICT architecture is modelled for growing network sizes. Quality-of- Service (QoS) provision is studied for various multi-tier hierarchical topologies under increasing number of end devices to gauge performance-cost tradeoffs related to demand-response latency and network deployment

Stochastic Optimization of an Active Network Management Scheme for a DER-Rich Distribution Network Comprising Various Aggregators

With large-scale acceptance of solar and wind energy generation into electric grids, large energy storage is expected to provide sufficient flexibility for the safe, stable and economic operation of power systems under uncertainty. Active Network Management (ANM) allows this to happen without having to enlarge the system. This paper presents an ANM-based cost minimization and curtailment model for day-ahead operational planning of active distribution systems. Electric Vehicles (EVs) are managed by EV Aggregators for profit purposes under different parking characteristics in the Vehicle-to-grid mode. A pricing mechanism that defines interaction between the Distribution System Operator (DSO) and EV Aggregators is proposed. Uncertainty terms involve the wind power outputs, solar power outputs and the power demand. The stochastic optimization model created 27 scenarios and solved the minimization problem which involves the grid supply point power, the non-firm power and the aggregator power. This is applied to IEEE-33 bus system and implemented in AIMMS. Results show how the impact of various aggregators’ availability profiles help to reduce network operating cost and curtailment of non-firm DGs and improve voltage profiles

A multi-agent intelligent decision making support system for home energy management in smart grid: A fuzzy TOPSIS approach

In the context of intelligent home energy management in smart grid, the occupants' consumption behavior has a direct effect on the demand and supply of the electrical energy market. Correspondingly, the policies of the utility providers affect consumption behavior so techniques and tools are required to analyse the occupants' preferences, habits and lifestyles in order to support and facilitate their decision-making regarding the curtailing of their energy consumption and costs. The uncertainty about householders' preferences increases the uncertainty of appliance prioritization and makes it difficult to determine the consistency of preferences in terms of energy consumption. In this complex system, the preferences and judgments of householders are represented by linguistic and vague patterns. This paper proposes a much better representation of this linguistics that can be developed and refined by using the evaluation methods of fuzzy set theory. The proposed approach will apply the fuzzy Technique for Order Preference by Similarity to Ideal Solution (fuzzy TOPSIS) for achieving preferences. Based on our detailed literature review of the multi-agent system approach in this field, it is expected that the proposal model will offer a robust tool for communication and decision-making between occupant agents and dynamic environmental variables. It is shown that the proposed fuzzy TOPSIS approach will enable and assist householders to maximize their participation in demand response programs