Congestion Management Considering Optimal Placement of Distributed Generator in Deregulated Power System Networks

This article presents an effective methodology for congestion management in deregulated power system networks considering optimal placement of a distributed generator. The novelty of this method is that the optimal placement of a distributed generator in a deregulated power system is decided on the basis of bus impedance matrix (Z_bus ) based contribution factors. The Z_bus -based contribution factors are independent of slack bus location, which complies with the prevailing competitive environment. The congestion management problem formulation comprises the maximization of social welfare function subject to power balance and transmission congestion constraints. The maximization of the social welfare function causes maximization of consumer benefits and minimization of supplier generation cost and distributed generators. The proposed methodology has been simulated on an IEEE 30-bus system, and comparisons of results are presented with and without distributed generators. The results show that the proposed approach gives significant improvement in social welfare and decreases congestion rent with distributed generator placement.     

计及需求响应的风电储能两阶段调度优化模型及求解算法

为解决风电功率不确定性对系统稳定运行带来的影响,在含风电的系统优化调度问题中引入需求响应和储能系统。首先利用区间法模拟风电场景并构建了基于Kantorovich距离的场景削减策略,然后分别在需求侧和发电侧引入需求响应和储能系统,结合2阶段优化理论,以风电日前预测功率和超短期预测功率作为随机变量及其实现,构建了计及需求响应的风电储能2阶段调度优化模型。为求解该模型,在传统二进制粒子群算法中引入混沌搜索,构建了混沌二进制粒子群算法。最后,以IEEE 36节点10机系统进行算例仿真。结果表明,混沌二进制粒子群算法能够得到全局最优解,适用于风电储能系统2阶段模型求解;利用需求响应和储能系统的协作效应,可以抑制风电功率的不确定性,提高系统风电利用效率,降低系统发电煤耗水平,因此综合效益显著。     

孤立微网的多目标能量管理

针对孤立微网系统的能量管理问题,利用蓄电池和超级电容的互补特性,以经济性和环保性为优化目标,提出了一种采用混合储能系统的微网多目标能量管理方法。求解方法分为2步,首先,综合考虑当前和未来可再生能源发电期望和负荷需求、不同调度时段、储能装置的实时荷电状态等因素,采用模糊控制对混合储能系统进行管理。其次,在计及多种约束条件下,利用改进的粒子群优化算法对微电源出力进行经济环保优化调度,得到微网系统的最终运行方式。该方法不仅能实现孤立微网经济、环保、可靠运行,还可延长蓄电池使用寿命,提高储能系统经济性,通过多组实验对比,验证了模型的有效性和可行性。     

风力发电系统中储能容量的优化配置

在风力发电系统中,合理地规划配置储能系统的容量对于风力发电产业的长远发展具有非常重要的意义。首先建立了电池储能系统的模型,提出一种基于该类储能系统的容量优化配置策略,并在此基础上将电池储能系统的全生命周期成本作为储能容量的优化目标,建立了以发电系统能量缺失率等运行指标为约束条件的储能容量优化模型,运用粒子群算法对该复杂优化配置模型进行求解计算。通过对算例系统的求解,验证了所建模型和算法的正确性和有效性,同时也为风力发电系统中储能单元的容量优化提供了参考。     

Demand Side Management for Stand-Alone Microgrid Using Coordinated Control of Battery Energy Storage System and Hybrid Renewable Energy Sources

Abstract

Distributed generation with battery energy storage (BES) system is an alternative solution for stand-alone AC supply systems. This article addresses the issue of voltage variability of stand-alone microgrid with the adoption of intelligent micro-source controllers. The high energy density of the BES system is used to compensate the voltage fluctuation. A control mechanism is designed to regulate the flow of electrical energy from BES system. The control structure of DC–AC microgrid integrated with BES system is proposed, and the study is extended to explore the mechanism of demand side management (DSM) with the incorporation of voltage-droop characteristics. The BES system is interlinked to maintain the voltage to a desirable range and the proposed work is intended to show the introductory concept on DSM accomplished through voltage-reduction at the consumption-side. The proposed control strategy not only achieves frequency-regulation in adherence to IEEE Standard-1547, but also maintains customers’ quality of service while customizing voltage for regulating DSM. The basis of regulating the nickel-metal-hydride battery is state-of-charge of BES system and voltage generated by the hybrid sources consist of photovoltaic and wind energy systems. The adequacy of the proposed control scheme with BES-module is validated using time-domain simulation studies considering voltage-dependent-loads.     

The Smart Grid—State-of-the-art and Future Trends

Abstract

This paper introduces Smart Grid and associated technical, environmental and socio-economic, and other non-tangible benefits to society, and articulates the need for the concept and the fact that it is a dynamic interactive, real-time infrastructure that responds to the challenges of designing and building the power system of the future, rather than being simply a marketing term. To illustrate the diversity of terminology, the paper compares an Electric Power Research Institute (EPRI) definition with that suggested by a study group of the International Electrotechnical Commission (IEC). Next, a paper sponsored by the Canadian Electricity Association (CEA) that cites three example definitions to highlight the diversity of views of Smart Grid is briefly reviewed. Early misconceptions and characterizations of Smart Grid are discussed as a prelude to addressing challenging issues that motivate developing and implementing related innovative technologies, products and services. The paper then discusses the potential promise of the Smart Grid, which is embedded in its often-cited attributes of efficiency, accommodating, quality focus, enabling and self-healing to name some. The paper then addresses some of the often-cited impediments to accepting Smart Grid which are based on concerns and issues confronting its forward progress, adoption and acceptance. Distribution Automation (DA) and embedded intelligence are discussed emphasising self-healing, optimizing operation and facilitating recreation and recovery from abnormal events. Functional and integration requirements of Distributed Energy Resources (DER,) are detailed. Smart Consumption Infrastructure elements of Distribution Management Systems (DMS,) Automated Metering Infrastructure (AMI,) Smart Homes (SH), and Smart Appliances (SA,) are discussed. Following the introductory section, this paper summarizes contributions included in the double issue 42(3–4) of the Electric Power Components and Systems Journal. To begin, papers are offered discussing smart grid activities in China, India, and the development of a Smart Grid roadmap for the US State of Kentucky. The approaches of each of these cases reflect the diversity of policy initiatives in these jurisdictions. Two state of the art reviews are given next. The first considers distribution network active management and future development trends in technologies and methods, where centralized and decentralized management frameworks and applying agent-based coordination are discussed. The second offers a review of smart home technologies and the goals of an energy management system (SHEMS). This section is concluded by a letter providing an overview of recent and expected advances nanotechnology applications in Smart Grid. Following the state of the art review section, ten papers offering new and innovative research approaches and results are included. These papers cover Smart Grid topics such as real-time energy control approach for smart home energy management systems, optimal operation of energy- efficient buildings with Combined Heat and Power (CHP) systems, energy management and control of Electric Vehicle (EV) charging stations, voltage-frequency control of a voltage source inverter (VSI) in a smart islanded microgrid, smart generation scheduling for wind-thermal-pumped storage systems, optimized power system restoration, robust data transmission upon compressive sensing, data fusion for wide-area oscillation monitoring, satellite based GPS synchronized monitoring systems, stability in Smart Grid with emerging renewable energy techno- logies.