Search

Forecasts and their corresponding optimized operation plans for energy plants never match perfectly, especially if they have a horizon of several days. In this paper, we suggest a concept to cope with uncertain load forecasts by reserving a share of the energy storage system for short-term balancing. Depending on the amount of uncertainty in the load forecasts, we schedule the energy system with a specific reduced storage capacity at the day-ahead market. For the day of delivery, we examine the optimal thresholds when the remaining capacity should be used to balance differences between forecast and reality at the intraday market. With the help of a case study for a simple sector-coupled energy system with a demand for cooling, it is shown that the energy costs could be reduced by up to 10% using the optimal reserve share. The optimal reserve share depends on the forecast quality and the time series of loads and prices. Generally, the trends and qualitative results can be transferred to other systems. However, of course, an individual evaluation before the realization is recommended. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with the two‐stage hierarchical control of microgrids (MG) that can operate in both grid‐connected and off‐grid modes. The procedure consists in the segmentation of the control scheme in the primary and secondary levels, thus enabling the application of faster and slower dynamics according to the process. A decentralized droop control‐based method is used in the primary level, while a distributed multi‐agent coordination scheme is applied in the secondary one. The multi‐agent system is run on Python Agent DEvelopment (PADE) environment, a FIPA‐compliant agent framework. The key contributions this paper provides are the control strategies of reactive power output of non‐dispatchable sources, dynamic sharing of energy storage systems, and the management of loads of microgrids, all of them based on multi‐agent system. Co‐simulations using PSCADTM and PADE are performed considering several operating scenarios of the MG resources under different load conditions. Simulation results validate the accurate performance of the proposed control strategies. [ABSTRACT FROM AUTHOR]

In the energy system, various sources are used to fulfill the energy demand of large buildings. The energy management of large-scale buildings is very important. The proposed system comprises solar PVs, energy storage systems, and electric vehicles. Demand response (DR) schemes are considered in various studies, but the analysis of the impact of dynamic DR on operational cost has been ignored. So, in this paper, renewable energy resources and storages are integrated considering the demand response strategies such as real-time pricing (RTP), critical peak pricing (CPP), and time of use (ToU). The proposed system is mapped in a linear model and simulated in MATLAB using linear programming (LP). Different case studies are investigated considering the dynamic demand response schemes. Among different schemes, results based on real-time pricing (58% saving) show more saving as compared to the CPP and ToU. The obtained results reduced the operational cost and greenhouse gas (GHG) emissions, which shows the efficacy of the model. [ABSTRACT FROM AUTHOR]

The stationary supercapacitor energy storage system (SCESS) is one of effective approaches for the utilization of train's regenerative braking energy in urban rail systems. In this paper, the capacity configuration of SCESSs, the no-load voltage of substation, the control of onboard braking resistors and train operation diagrams are considered comprehensively. Based on the equivalent circuit model, the effects of traction power system parameters on the energy transmission between powering trains, braking trains and SCESSs are analyzed, and the relationships between the train operating parameters and system energy consumptions are revealed. A multi-variable synthetic optimization method is proposed to optimize the SCESS capacity, train operation diagrams and traction power system parameters collaboratively. In order to reduce the search space and improve the efficiency of the optimization algorithm, a hierarchical multi-objective optimization model is established, based on which the design variables and the control variables are optimized iteratively. And as the traffic density has a great impact on the regenerative braking energy distribution of the system, the optimization objective function fully considers the frequency distribution of headways throughout the day. Combined the Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) with the traction power flow simulator, the flowchart of the two-stage optimization algorithm is designed, and the pareto set of the multi-objective problem is obtained. The advantages of reducing system energy consumptions and configuration cost under the proposed algorithm are verified based on case studies of Beijing Batong Line. [ABSTRACT FROM AUTHOR]

Despite their advantages, distributed energy resources (DERs) bring inherent uncertainty and variability into the landscape of modern power systems. As DER penetration grows, conventional generators like hydropower plants have to respond more often to arrest the imbalance in the net load. Hydropower turbines provide their best operational performance with minimal wear and tear when operating at regions of maximum efficiency. However, the current needs for hydropower plants require them to operate under varying load conditions and thus sub-optimal operating points leading to additional stress. To relieve the hydropower plants, this paper proposes a hybridization strategy where a hydropower unit is paired with an energy storage system (ESS) to increase operational flexibility and mitigate damage to the hydro plant. Models are developed to represent the operation of the hybrid system, quantify degradation, and assess economic benefits. Moreover, an innovative controller disaggregates the market dispatch signal into separate control setpoints for the ESS and hydropower unit. In case studies performed on a real-world hydropower facility, it was found that the ESS-based hybridization can extend the life of the hydropower plant by 5% on average. The economic benefits from reduced maintenance and deferred investment are estimated to be around $3.6 million. • A hybridization strategy is proposed to pair energy storage with a hydro plant. • Energy storage helps increase flexibility and mitigate damage to the hydro plant. • Methods are developed to model the hybrid system and quantify degradation effects. • An innovative controller is designed to optimize the set points by component. • Economic benefits from reduced maintenance and deferred investment are assessed. [ABSTRACT FROM AUTHOR]

The application of a stationary ultra-capacitor energy storage system (ESS) in urban rail transit allows for the recuperation of vehicle braking energy for increasing energy savings as well as for a better vehicle voltage profile. This paper aims to obtain the best energy savings and voltage profile by optimizing the location and size of ultra-capacitors. This paper firstly raises the optimization objective functions from the perspectives of energy savings, regenerative braking cancellation and installation cost, respectively. Then, proper mathematical models of the DC (direct current) traction power supply system are established to simulate the electrical load-flow of the traction supply network, and the optimization objections are evaluated in the example of a Chinese metro line. Ultimately, a methodology for optimal ultra-capacitor energy storage system locating and sizing is put forward based on the improved genetic algorithm. The optimized result shows that certain preferable and compromised schemes of ESSs' location and size can be obtained, acting as a compromise between satisfying better energy savings, voltage profile and lower installation cost. [ABSTRACT FROM AUTHOR]

Emergency generators are important facilities that supply emergency power to fire-fighting facilities in the event of a power outage. Accordingly, a load test of the emergency generator should be performed by cutting off the power source of the fire-fighting target in order to accurately confirm the performance and condition of the emergency generator in normal circumstances. However, the test has usually been carried out without loads due to serious problems, which are caused by a shutdown of the power source for the load test of emergency generators, such as the shutdown of emergency load, etc. In order to overcome these problems, this paper proposes an operation method and algorithm of a load test device using ESS, which can conform to characteristics of emergency loads installed in fire-fighting targets by interconnecting it with the emergency generator. In addition, this paper performs a modeling of an emergency power system using PSCAD/EMTDC, and then this paper confirms the usefulness of the proposed method and operation algorithm of the load test device using ESS. [ABSTRACT FROM AUTHOR]

The ever-increasing electricity price and energy consumption in high-speed railway industry push railway companies to seek a promising way to realize their sustainable developments. Making full use of the solar resource along with high-speed railways can be a potential solution to cut the electricity bill, bring more profit to railway companies and realize the decarbonization of high-speed railway industry. This paper studies the optimal planning of distributed photovoltaic generation (DPVG) and energy storage system (ESS) for the traction power supply system (TPSS) of high-speed railway. A quantitative method is proposed to study the time and space characteristics of photovoltaic generation and electricity demand of high-speed trains. An integrated cost-benefit analysis framework is developed to evaluate the effect of DPVG and ESS on the economy of TPSS. To derive the optimal planning scheme and energy management strategy of DPVG and ESS, a mathematical programming model with the objective of minimizing the total cost is proposed to seek the most economical solution. A hybrid global optimal solution approach is developed to solve the model. A real-world case of Beijing-Baoding high-speed railway in China is used to illustrate the capability and characteristics of the proposed model. The computational results show that DPVG is able to supply 32.5 % electricity demand of high-speed trains. The integration of DPVG and ESS can help railway company save 4.2 million CNY each year in Beijing-Baoding high-speed railway. This paper demonstrates the potential and applicability of DPVG and ESS in high-speed railway industry. • A novel distributed photovoltaic generation model is proposed for the traction power supply system of high-speed railway. • A global optimal algorithm is provided to derive the most economical planning scheme and energy-management strategy. • Photovoltaic generation can help Beijing-Baoding high-speed railway save 4.2 million China Yuan each year. • Solar energy is able to supply 32.5% electricity demand of Beijing-Baoding high-speed railway. [ABSTRACT FROM AUTHOR]

Abstract: Energy storage systems (ESS) are becoming one of the most important components that noticeably change overall system performance in various applications, ranging from the power grid infrastructure to electric vehicles (EV) and portable electronics. However, a homogeneous ESS is subject to limited characteristics in terms of cost, efficiency, lifetime, etc., by the energy storage technology that comprises the ESS. On the other hand, hybrid ESS (HESS) are a viable solution for a practical ESS with currently available technologies as they have potential to overcome such limitations by exploiting only advantages of heterogeneous energy storage technologies while hiding their drawbacks. However, the HESS concept basically mandates sophisticated design and control to actually make the benefits happen. The HESS architecture should be able to provide controllability of many parts, which are often fixed in homogeneous ESS, and novel management policies should be able to utilize the control features. This paper introduces a complete design practice of a HESS prototype to demonstrate scalability, flexibility, and energy efficiency. It is composed of three heterogenous energy storage elements: lead-acid batteries, lithium-ion batteries, and supercapacitors. We demonstrate a novel system control methodology and enhanced energy efficiency through this design practice. [Copyright &y& Elsevier]

The development of electricity retailers with energy storage systems expands the energy use ways of users, promotes the consumption of clean energy power generation, and facilitates the development of electricity market. However, due to the imperfect trading mechanism and uncertainties of power supply and demand, the business risk continues to be large, which leads to limited sustainable development of electricity retailers. Therefore, based on the design of a trading mechanism of electricity retailers with energy storage systems in the electricity market, this paper constructs a multi-objective stochastic optimization model of the retailers' flexible purchase of electricity, aiming at minimizing the cost of electricity retailers and maximizing the consumption of clean energy power generation. In the model, the uncertainty of supply and demand and the demand response are taken into consideration. The results show that: (1) Compared with the conventional optimization model, considering the uncertainty in the medium-and-long-term electricity trading, although the demand for clean energy is reduced, the retail cost of temporary electricity in the day-ahead trading is also reduced. (2) The retailers make full use of flexible power charging and discharging, so the extra cost of purchasing electricity in the day-ahead trading caused by the uncertainty of clean energy is reduced via the energy storage demand response. (3) A price-based demand response can change the electricity purchase demand of retailers, improve the transaction volume between retailers and clean power enterprises in the medium-and-long-term electricity trading, and reduce the energy purchase cost while improving the consumption of clean energy power generation. (4) Due to the impact of initial investment cost and other factors, there is no obvious linear relationship between the capacity of energy storage systems and the reduction of retail energy purchase cost; therefore, it is necessary to apply energy storage systems reasonably to achieve the optimal economic benefits. • The trading strategy for ER-ESS participating in electricity market is formulated. • The energy storage and price-based demand response models are constructed. • The respective solving algorithms for the regular and uncertainty model are built. [ABSTRACT FROM AUTHOR]

At present, renewable energy installations are expanding to solve both environmental problems and expensive energy fuel import prices in isolated areas. However, in a small-scale power system, rapid output fluctuations of renewable energy may cause power quality problems such as voltage and frequency fluctuations in the power system. To solve this problem, the local government of Jeju Island in South Korea implemented a megawatt (MW)-class pilot project to stabilize the output power of wind turbines using an energy storage system (ESS). In this project, a 0.5 MWh lithium-ion battery was connected to a 3 MW wind turbine via 1 MW power conversion system (PCS). In this paper, the field test results were divided into four categories as follows. First, the performance of stabilizing the output of the wind turbine using ESS was confirmed. Second, the control performance of the ESS was confirmed when the wind turbine suddenly stopped due to an accident. Third, it was confirmed that the ESS discharged energy into the power system after the stabilization of the wind turbine output. Fourth, the reasons for the failure of the ESS to control output stabilization of the wind turbine were analyzed through MATLAB simulation. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal Energy Storage System (ESS) scheduling algorithm Building Energy Management System (BEMS). In particular, the focus is placed on how to reduce the peak load using ESS and load forecast. To this end, first, an existing deep learning-based load forecast method is applied to a real building energy prediction and it is shown that the deep learning-based method leads to an accuracy-enhanced load forecast. Second, an optimization problem is formulated in order to devise an ESS scheduling. In the optimization problem, the objective function and constraints are defined such that the peak load is reduced; the cost for electricity is minimized; and the ESS's lifetime is elongated considering the accuracy-enhanced load forecast, real-time electricity price, and the state-of-charge of the ESS. For the purpose of demonstrating the effectiveness of the proposed ESS scheduling method, it is implemented using a real building load power and temperature data. The simulation results show that the proposed method can reduce the peak load and results in smooth charging and discharging, which is important for the ESS lifetime. [ABSTRACT FROM AUTHOR]

• A multi-objective renewable energy management scheme is proposed. • Cost saving, green consumption and power quality are the main motivations. • A novel multi-agent system with three electricity use mode is developed. • Key implications and recommendations for policy makers are given. This paper proposes a multi-objective renewable energy management scheme to satisfy the needs of diversified community power consumers, wherein the multi-agent system is employed for coordinating and controlling the power generation and consumption units. Firstly, a multi-agent based microgrid and home energy management system is constructed. Subsequently, system models for renewable energy sources, electrical vehicles, residential loads and the cost function are constructed to form the microgrid operation constraints. With these constraints, three optimization models are proposed to minimize the electricity bills, the power purchased from the main grid, and optimize the power quality. The three objectives are proposed to reflect the power consumer's needs for cost saving, green consumption, and power reliability, respectively. Meanwhile, a coordination strategy which balances the three objectives is proposed. After that, a novel multi agent system is proposed to realize the proposed objectives. Four case studies and a sensitivity analysis are conducted to verify the effectiveness of the proposed method. The case study results show that: in electricity minimization, 2–6.5% of total electricity bills can be saved; in main grid power consumption minimization, the peaks of the power consumption profiles are shaved while the valleys of the profiles are filled; in power quality enhancement, the steady state frequency drop is reduced for 0.35 Hz to 0.38 Hz. The sensitivity analysis shows that communities equipped with energy storage systems accounting for 30% of the total load can achieve best optimization outcomes; the increase in renewable energy usage will lead to higher electricity bills and poorer power quality if the renewable energy sources are limited, while the availability of more renewable energy sources will compensate for the negative effects of using renewable energy sources. [ABSTRACT FROM AUTHOR]

The global consumerism trend and the increase in worldwide population is increasing the need to improve the efficiency of marine container transportation. The high operating costs, pollution and noise of the diesel yard equipment is leading sea ports to move towards replacing diesel RTG cranes with electric Rubber Tyre Gantry (RTG) cranes which offer reduced environmental impact and higher energy efficiency. However, ports will require smarter solutions to meet the increased demand on the electrical distribution network due to the electrification of RTGs. This paper aims to highlight the peak demand problem in the two electrical cranes network and attempts to increase the energy saving at ports by using two different technologies: Energy Storage System (ESS) and Active Front End (AFE). This article introduces one of the first extensive investigations into different networks of RTG crane models and compares the benefits of using either AFE or ESS. The proposed RTG crane models and network parameters are validated using data collected at the Port of Felixstowe, UK. The results of the proposed RTG cranes network show a significant peak demand reduction and energy cost saving. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal operational scheduling of a reconfigurable multi-microgrid (MG) distribution system complemented by demand response programs and Energy Storage Systems (ESSs) in an uncertain environment. Since there is a set of competing players with inherently conflicting objectives in the system under study such as the Distribution System Operator (DSO) and MG owners, a one-leader multi-follower-type bi-level optimization model is proposed. In this framework, the upper-level player as a leader minimizes the total cost from DSO's point of view, while the lower-level players as multi-followers maximize the profit of MG owners. Since the resulting model is a non-linear bi-level optimization problem, it is transformed into a single-level mixed-integer second-order cone programming problem through Karush–Kuhn–Tucker conditions. The satisfactory performance of the proposed model is investigated on a real-test system under different scenarios and working conditions. [ABSTRACT FROM AUTHOR]

Energy storage plays a major role in solving the fluctuation and intermittence problem of wind and the effective use of wind power. The application of the hydraulic accumulator is the most efficient and convenient way to store wind energy in hydraulic wind turbines. A hydraulic energy storage generation system (HESGS) can transform hydraulic energy stored in the hydraulic accumulator into stable and constant electrical energy by controlling the variable motor, regardless of wind changes. The aim of the present study is to design a constant speed control method for the variable motor in the HESGS and investigate the influence of the controller's main parameters on the resistance of the HESGS to external load power disturbances. Mathematical equations of all components in this system are introduced and an entire system simulation model is built. A double closed-loop control method of the variable motor is presented within this paper, which keeps the motor speed constant for the fixed frequency of electrical power generated by the HESGS. Ultimately, a series of simulations with different proportional gains and integral gains under the environment of changeless load power step are conducted. At the same time, comparison analyses of the experiment and simulation under variable load power step are performed. The results verify the correctness and the usability of the simulation model, and also indicate that the proposed control method is robust to the disturbances of changing load power. [ABSTRACT FROM AUTHOR]