Demand-side energy storage system management in smart grid

An economical way to manage demand-side energy storage systems in the smart grid is proposed by using an H∞ design. The proposed design can adjust the stored energy state economically according to the price signal, while tolerating a certain degree of system uncertainty and having physical constraints on the stored energy level satisfied. Roughly speaking, batteries in the proposed design are charged during a low-price period while being discharged during a high-price period for cost control. Simulations show that the proposed energy storage system can meet the real-time power demand and save money in the long term in contrast to energy storage systems using constant-state schemes

Energy management and trading in a smart microgrid

Abstract: Abstract—Distributed Energy Generation (DEG) and Distributed Energy Storage (DES) are finding increasing applications in Demand Side Management (DSM) due to their potentials for grid power system balance and arbitrage opportunities. A grid-connected smart microgrid comprising heterogeneous (active and passive) smart consumers and a largescale energy storage device is considered in this work. Energy management by each smart entity is carried out by the proposed Microgrid Energy Management – Distributed Optimisation Algorithm (MEM-DOA) installed within the network according to consumer type. Each smart consumer optimises its energy consumption, expenditure and trading for comfort and profit. The proposed model was observed to yield financial benefits, grid reliability and sustainability, reduced investment on peaker plants, reduced Peak-to-Average-Ratio (PAR) demand and associated environmental benefits

Grid Interaction Performance Evaluation of BIPV and Analysis with Energy Storage On Distributed Network Power Management

This research focuses on analysis of photovoltaic (PV) based active generator in microgrid and its utilization in not only for operational planning of the power system but also for instantaneous power flow management in the smart grid environment. The application of this system is part of a solution on handling a large scale deployment of grid connected distributed generators, especially PV system. By implementing the PV based active generator, it will be very flexible able to manage the power delivery from the active generator sources (e.g. PV system, energy storage technologies, active power conditioning devices). In Southern Norway, a smart village Skarpnes is developed for ZEBs. These ZEBs have Building Integrated Photovoltaic (BIPV) system. The energy efficient housing development should consider that a building should produce the same amount of electrical energy as its annual requirements (i.e. ZEB). In future, ZEBs are going to play a significant role in the upcoming smart grid development due to their contribution on the on-site electrical generation, energy storage, demand side management etc. In this work the main objective is to evaluate the usefulness of ZEBs for load matching with BIPV generation profiles and grid interaction analysis. Impact of BIPV system has been investigated on the distributed network power flow as well as on protection and protective relays analysis. Furthermore, techno-economic analysis of BIPV system is presented which will be useful to the utility for developing new business models as well as demand side management (DSM) strategies and for decentralized energy storage. The real operational results of a year are analyzed for annual energy balance with on-site BIPV generation and local load. This work provides quantitative analysis of various grid interaction parameters suitable to describe energy performance of the BIPV. The load matching and grid interaction parameters are calculated for a house to find relationship of BIPV generation and building load. The loss of load probability is analyzed for fulfilling the local load at desired reliability level. Results of this work are going to be useful for developing DSM strategies and energy storage as well as import/export energy to the grid. This work will be beneficial for future planning of the distributed network when the BIPV penetrations are going to increase

Demand Side Management Techniques for Home Energy Management Systems for Smart Cities

In this paper, three distinct distributed energy resources (DERs) modules have been built based on demand side management (DSM), and their use in power management of dwelling in future smart cities has been investigated. The investigated modules for DERs system are: incorporation of load shedding, reduction of grid penetration with renewable energy systems (RES), and implementation of home energy management systems (HEMS). The suggested approaches offer new potential for improving demand side efficiency and helping to minimize energy demand during peak hours. The main aim of this work was to investigate and explore how a specific DSM strategy for DER may assist in reducing energy usage while increasing efficiency by utilizing new developing technology. The Electrical Power System Analysis (ETAP) software was used to model and assess the integration of distributed generation, such as RES, in order to use local power storage. An energy management system has been used to evaluate a PV system with an individual household load, which proved beneficial when evaluating its potential to generate about 20–25% of the total domestic load. In this study, we have investigated how smart home appliances’ energy consumption may be minimized and explained why a management system is required to optimally utilize a PV system. Furthermore, the effect of integration of wind turbines to power networks to reduce the load on the main power grid has also been studied. The study revealed that smart grids improve energy efficiency, security, and management whilst creating environmental awareness for consumers with regards to power usage

Community power flow control for peak demand reduction and energy cost savings

The increase in penetration of renewable energy sources, such as solar or wind, and high peak load demand can cause grid network security issues. The incorporation of demand side management and energy storage devices can provide a solution to these problems. This paper presents a community power flow control (PFC) strategy which reduces peak grid demand, and increases self-consumption of renewable energy which produces energy cost savings in smart communities with grid-connected photovoltaic (PV) systems. The PFC aims to directly control high power consumption appliances and the charge/discharge of a community battery storage using measurement of the instantaneous power demands of the community. Historical data records of the community daily energy consumption and the available renewable energy are taken into account to manage the loads and battery storage. Simulation results show for a community of one hundred houses, with 114 kWp of PV arrays, and a 350kWh battery system that the percentage of the average peak power demand reduction over the year is 32%,whilethePV energy self-consumption increases by73%. This can produce an annual energy cost saving of up to £1100 when compared to the same community with only PV

Fast transactive control for frequency regulation in smart grids with demand response and energy storage

This paper proposes a framework for controlling grid frequency by engaging the generation-side and demand-side resources simultaneously, via a fast transactive control approach. First, we use a proportional frequency-price relation to build and analyze a transactive frequency droop controller for a single-area power grid. Then, we develop a transactive demand response system by incorporating a large population of thermostatically controlled air conditioning loads. A proportional-integral controller is used to adjust the setpoint temperature of the air conditioners based on price variations. A battery storage system is then developed and augmented to the system to capture the energy arbitrage effects. A nonlinear price-responsive battery management system is developed to enable effective charging and discharging operations within the battery’s state-of-charge and power constraints. Simulation results indicate that the proposed transactive control system improves the steady-state and transient response of the grid to sudden perturbations in the supply and demand equilibrium. To decouple frequency from price during daily operation and maintain frequency near the nominal value, we propose adding a feedforward price broadcast signal to the control loop based on the net demand measurement. Through various simulations, we conclude that a combination of feedback transactive controller with feedforward price broadcast scheme provides an effective solution for the simultaneous generation-side and demand-side energy management and frequency control in smart power grids

An insight into the integration of distributed energy resources and energy storage systems with smart distribution networks using demand-side management

Demand-side management (DSM) is a significant component of the smart grid. DSM without sufficient generation capabilities cannot be realized; taking that concern into account, the integration of distributed energy resources (solar, wind, waste-to-energy, EV, or storage systems) has brought effective transformation and challenges to the smart grid. In this review article, it is noted that to overcome these issues, it is crucial to analyze demand-side management from the generation point of view in considering various operational constraints and objectives and identifying multiple factors that affect better planning, scheduling, and management. In this paper, gaps in the research and possible prospects are discussed briefly to provide a proper insight into the current implementation of DSM using distributed energy resources and storage. With the expectation of an increase in the adoption of various types of distributed generation, it is estimated that DSM operations can offer a valuable opportunity for customers and utility aggregators to become active participants in the scheduling, dispatch, and market-oriented trading of energy. This review of DSM will help develop better energy management strategies and reduce system uncertainties, variations, and constraints

Use of adaptive thermal storage system as smart load for voltage control and demand response

This paper describes how a large-scale ice-thermal storage can be turned into a smart load for fast voltage control and demand-side management in power systems with intermittent renewable power, while maintaining its existing function of load shaving. The possibility of modifying a conventional thermal load has been practically demonstrated in a refrigerator using power electronics technology. With the help of an electric spring, the modified thermal load can reduce power imbalance in buildings while providing active and reactive power compensation for the power grid. Based on practical data, a building energy model incorporating a large-scale ice-thermal storage system has been successfully used to demonstrate the advantageous demand-response features using computer simulation of both grid connected and isolated power systems. The results indicate the potential of using ice-thermal storage in tall buildings in reducing voltage and frequency fluctuations in weak power grids

Modeling and Integration of Demand Response and Demand Side Resources for Smart Grid Application in Distribution Systems

Today\u27s electric grid is undergoing drastic changes to evolve into a smart grid. Deregulation of the integrated and monopolistic power system into genco, transco and disco has led to tremendous competition among these players. These entities are in the process of developing innovative smart grid strategies that can improve their reliability and profit. In this thesis work, some of the smart grid initiatives by discos have been explored.;This thesis work is driven by two major objectives. The primary objective is to explore Demand Response (DR), develop its comprehensive model and to analyze various effects and implications of DR on distribution networks. The second major objective of the thesis is to integrate the developed demand response model into a microgrid market optimization. A microgrid network is a real world demonstration of smart grid that integrates and coordinates various demand side resources into its operation. For this reason, a microgrid has been chosen in this work so that it offers a broader scope where in addition to DR models, Battery Energy Storage System (BESS) and Distributed Energy Resources (DER) or Distributed Generation (DG) can also be modeled and integrated.;This thesis develops a model for DR by utilizing consumer behavior modeling considering different scenarios and levels of consumer rationality. Consumer behavior modeling has been done by developing extensive demand-price elasticity matrices for different types of consumers. These Price Elasticity Matrices (PEMs) are utilized to calculate the level of demand response for a given consumer. DR thus obtained is applied to a real world distribution network considering a day-ahead real time pricing scenario to study the effects of demand reduction and redistribution on system voltage and losses. Results show considerable boost in system voltage that paves way for further demand curtailment through demand side management techniques like Volt/Var Control (VVC).;Following this, the thesis develops a market optimization model for an islanded microgrid that includes Smart Grid elements namely DR, DERs and BESS. Comprehensive models for DR and BESS have been developed and integrated into the optimization program. Demand Side Bidding (DSB) by DR Aggregators is introduced into the proposed double sided microgrid energy market by utilizing the DR models developed. The optimization program uses Linear Programming (LP) technique to determine the dispatch schedule of DERs, BESS and the level of DR to minimize the operating cost of the microgrid market. A time series simulation of a large microgrid test system is performed to show the feasibility of the proposed market optimization