Study on green power supply modes for heavy load in Remote Areas

In this study,the present situation and characteristics of power supply in remote areas are summarized.By studying the cases of power supply projects in remote areas,the experience is analyzed and described,and the applicability of related technologies,such as grid-forming storage and power load management,is studied,including grid-connection technologies,such as grid-forming converters and power load management.On this basis,three power-supply modes were proposed.The application scenarios and advantages of the three modes were compared and analyzed.Based on the local development situation,the temporal sequences of the three schemes are described,and a case study was conducted.The study of the heavy-load power supply mode in remote areas contributes to solving the problem of heavy-load green power consumption in remote areas and promoting the further development of renewable energy.

Optimal Operation of Electric Vehicles and Distributed Generation Resources in Smart Grid Considering Load Management

Technology advancement and the global tendency to use renewable energy in distributed generation units in the distribution network have been proposed as sources of energy supply.Despite the complexity of their protection,as well as the operation of distributed generation resources in the distribution network,factors such as improving reliability,increasing production capacity of the distribution network,stabilizing the voltage of the distribution network,reducing peak clipping losses,as well as economic and environmental considerations,have expanded the influence of distributed generation(DG)resources in the distribution network.The location of DG sources and their capacity are the key factors in the effectiveness of distributed generation in the voltage stability of distribution systems.Nowadays,along with the scattered production sources of electric vehicles with the ability to connect to the network,due to having an energy storage system,they are known as valuable resources that can provide various services to the power system.These vehicles can empower the grid or be used as a storage supply source when parked and connected to the grid.This paper introduces and studies a two-stage planning framework for the concurrent management of many electric vehicles and distributed generation resources with private ownership.In the first stage,the aim is to increase the profit of electric vehicles and distributed generation sources;finally,the purpose is to reduce operating costs.The proposed scheduling framework is tested on a distribution network connected to bus 5 of the RBTS sample network.Besides distributed generation sources and electric vehicles,we integrate time-consistent load management into the system.Due to distributed generation sources such as photovoltaic systems and wind turbines and the studied design in the modeling,we use the Taguchi TOAT algorithm to generate and reduce the scenario to ensure the uncertainty in renewable energy.MATLAB software is used to solve the problem and select the optimal answer.

Management of Charging Load of Electric Vehicles for Optimal Capacity Utilisation of Distribution Transformers

A de-centralised load management technique exploiting the flexibility in the charging of Electric Vehicles (EVs) is presented. Two charging regimes are assumed. The Controlled Charging Regime (CCR) between 16:30 hours and 06:00 hours of the next day and the Uncontrolled Charging Regime (UCR) between 06:00 hours and 16:30 hours of the same day. During the CCR, the charging of EVs is coordinated and controlled by means of a wireless two-way communication link between EV Smart Charge Controllers (EVSCCs) at EV owners’ premises and the EV Load Controller (EVLC) at the local LV distribution substation. The EVLC sorts the EVs batteries in ascending order of their states of charge (SoC) and sends command signals for charging to as many EVs as the transformer could allow at that interval based on the condition of the transformer as analysed by the Distribution Transformer Monitor (DTM). A real and typical urban LV area distribution network in Great Britain (GB) is used as the case study. The technique is applied on the LV area when its transformer is carrying the future load demand of the area on a typical winter weekday in the year 2050. To achieve the load management, load demand of the LV area network is decomposed into Non-EV load and EV load. The load on the transformer is managed by varying the EV load in an optimisation objective function which maximises the capacity utilisation of the transformer subject to operational constraints and non-disruption of daily trips of EV owners. Results show that with the proposed load management technique, LV distribution networks could accommodate high uptake of EVs without compromising the useful normal life expectancy of distribution transformers before the need for capacity reinforcement.

Practicality of power load management system in Chongqing City verified

Began from early 1992, Chongqing Power Supply Bureau had spent 3 and half years to build up a power load management system consisting of I master station, 6 relay stations, 1280 terminals and the distributed monitoring device. This system distributes in the hilly and mountainous areas where geographically complicated and the load widely scatters, it can supervise about 72% load and curtail more than 15% load

Optimizing Decision-Making of A Smart Prosumer Microgrid Using Simulation

Distributed renewable energy sources offer significant alternatives for Qatar and the Arab Gulf region’s future fuel supply and demand.Microgrids are essential for providing dependable power in difficult-to-reach areas while incorporating significant amounts of renewable energy sources.In energy-efficient data centers,distributed generation can be used to meet the facility’s overall power needs.This study primarily focuses on the best energy management practices for a smart microgrid in Qatar while taking demandside load management into account.This article looked into a university microgrid in Qatar that primarily aimed to get all of its energy from the grid.While diesel generators are categorized as a dispatchable distributed generation with energy storage added to handle solar radiation from the sun and high grid power operating costs in the suggested scenario,wind turbines and solar Photovoltaic(PV)are classified as non-dispatchable distributed generators.The resulting linear math issues are assessed and displayed in MATLAB optimization software using a mixed-integer linear programming(MILP)strategy.According to the simulation results,the suggested energy management strategy reduced the university microgrid’s grid power costs by 38.8%,making it an affordable solution which is somehow greater than the prior case scenario’s 23%savings.The installed solar system capacity’s effects on the economy,society,and finances were also assessed,and it became clear that the best option for the smart microgrid was determined that would be 325 kW of solar PV,25 kW of wind turbine,and 600 kW of diesel generators,respectively.Given the current situation,university administrators are urged to participate in distributed generators and adopt cutting-edge designs for energy storage technologies due to the significant environmental and financial benefits.

Evolving practice of demand-side management

The concept of demand-side management(DSM)was invented in the late 1970s along with the development of many of the frameworks in use to plan and implement it in the years immediately following. It was originally referred to as demand-side load management. It is generally defined as the planning and implementation of those activities designed to influence consumer use of electricity in ways that will result in changes in the utility’s load shape—i.e., changes in the time pattern and magnitude of a utility’s load. This paper describes the evolution it has undergone since its invention and some likely changes ahead. DSM largely originated in the U.S., but is practiced in various forms through the world today. This paper uses U.S. data as examples.

Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand

This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand.

Distributed Control of Thermostatically Controlled Loads in Distribution Network with High Penetration of Solar PV

High penetration of solar energy can result in voltage rise in midday,while growth in residential air conditioning is the main contributor of overloading and voltage drop issues during peak demand time.This paper provides a hierarchical control scheme to coordinate multiple groups of aggregated thermostatically controlled loads to regulate network loading and voltage in a distribution network.Considering the limited number of messages that can be exchanged in a realistic communication environment,an event-triggered distributed control strategy is proposed in this paper.Through intermittent on and off toggling of air conditioners,the required active power adjustment is shared among participating aggregators to solve the issue.A case study is conducted and simulation results are presented to demonstrate the performance of the proposed control scheme.

Passive energy storage using distributed electric loads with thermal storage

This paper presents the concept of controlling distributed electric loads with thermal energy storage as a passive electric energy storage system(PEESS).Examples of such loads include different types of thermostatically controlled appliances(TCAs)such as hot water heaters,air conditioners,and refrigerators.Each TCA can be viewed as a thermal cell that stores electricity as thermal energy.A centralized control mechanism can be used to control the timing of each thermal cell to consume electric energy so that the aggregated electricity consumption of the thermal cells will vary against a baseline consumption.Thus,when the aggregated consumption is higher than the baseline,the PEESS is charging;otherwise,the PEESS is discharging.The overall performance of a PEESS will be equivalent to that of a battery energy storage device.This paper presents the configuration and formulates the control of a PEESS.The modeling results demonstrate the feasibility of implementing the PEESS.

A New Approach to Design and Optimize Sizing of Hybrid Microgrids in Deregulated Electricity Environment

The demand for electrical energy in urban and suburban areas is increasing drastically because of various reasons.The electricity bill has increased significantly due to increased comfort levels and uses of modern appliances.Therefore,the demand response along with the power generated from renewable energy resources is playing an important role in reducing electricity bills without compromising any comforts.In this paper,a novel framework is proposed for the selection of renewable energy resources and sizing optimization with reduced costs and increased productivity for the end-users.The simultaneous process of selecting the appropriate renewable energy resources and sizing is covered in three stages:initially,the prediction of power from the renewable energy resources to perform a feasibility analysis is provided.Then,the sizing of the battery energy storage system for a grid integrated system to meet the load profile is performed.Finally,the performance analysis of the proposed microgrid in a deregulated electricity environment is performed.The modeling of the proposed hybrid microgrid considers load flexibility and the stochastic behavior of renewable energy resources.Moreover,the net metering concept(bi-directional energy exchange)is applied.For the developed model,the percentage of annualized return of investment(AROI)is found to be 6.8%with a payback period of 6.67 years.