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In this paper we study dynamical distortion problems in future electrical energy systems with high renewable penetration. We introduce a new time-domain modeling of electrical energy systems comprising inverter-controlled distributed energy resources (DERs). This modeling is first used to quantify the relations between distortions and real/reactive power dynamics. Next, to ensure acceptable Quality of Service (QoS), a novel nonlinear distributed inverter control is introduced. Sufficient conditions are established for the guaranteed performance of the proposed control. These conditions further support the practical implementation of the derived controller. The effectiveness of this enhanced control is illustrated using simulations for the case of avoiding system instability during sudden grid reconfigurations. Simulations also show that distortions can be suppressed in systems with parallel-connected solar photovoltaics (PVs). [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to designing technical and financial protocols needed to support the penetration of distributed energy resources (DERs). It first formulates a complex, hard‐to‐implement, centralized decision‐making objective for providing end‐to‐end electricity service. It then introduces a new taxonomy of an end‐to‐end interactive operations planning framework. The taxonomy rests on the dynamic monitoring and decisions systems (DyMoNDS) principles for supporting interactive protocols of (i) end‐to‐end interactions within a complex, multilayered multi‐voltage power system; (ii) dynamic energy resource management system (DERMS) interactions with their DERs as well as with the bulk power system (BPS) operators; and (iii) DERs interactions with DERMS. The distributed model predictive control for creating physically implementable cost functions is essential. Also, the minimal coordination of different layers utilizes an AC optimal power flow that is essential for ensuring power flow delivery. We next provide a proof‐of‐concept illustration on the IEEE 14 bus system augmented by two standardized microgrids of the proposed interactive protocols, and their potential use for enhancing dynamic host capacity (DHC). While novel, this approach is a natural outgrowth of the existing industry operations: It only requires enhancing decision‐making tools by the stakeholders, and carefully‐defined protocols for implementing their interactions. [ABSTRACT FROM AUTHOR]

This paper is motivated by the need to ensure fast microgrid stability. Modeling for purposes of establishing stability criterion and possible implementations are described. In particular, this paper proposes that highly heterogeneous microgrids comprising both conventional equipment and equipment based on rapidly emerging new technologies can be modeled as purely electric networks in order to provide intuitive insight into the issues of network stability. It is shown that the proposed model is valid for representing fast primary dynamics of diverse components (gensets, loads, and PVs), assuming that slower variables are regulated by the higher level controllers. Based on this modeling approach, an intuitively appealing criterion is introduced requiring that components or their combined representations must behave as closed-loop passive electrical circuits. Implementing this criterion is illustrated using a typical commercial feeder microgrid. Notably, these set the basis for standards that should be required for groups of components (subgrids) to ensure no fast instabilities in complex microgrids. Building the need for incrementally passive and monotonic characteristics into standards for network components may clarify the system level analysis and integration of microgrids. [ABSTRACT FROM AUTHOR]

Today, the state-of-the-art wind generators (WGs) are double-fed induction generators that integrate storage devices into their systems. These WGs are expected to be among the largest producers of renewable energy worldwide in the coming years. In this paper, we propose a consensus approach to the distributed control of the energy storage systems (ESS) for carrying out real-time wind farm power output regulation with power-sharing among these storage devices. These two objectives can be attained when the controllers of the ESS and the grid-side converter (GSC) within a single WG are coordinated and the controllers of the GSCs of all WGs are coordinated with each other as well. Our approach is comprehensive, including a coordinated control architecture for the ESS and GSCs to attain the former objective and a consensus-based control architecture for coordinating all GSCs to attain the latter. Calling upon results from singular perturbation and Lyapunov’s theories, we establish stability of the coupled closed-loop dynamics of the ESS and the consensus protocol. Lastly, we construct the control algorithms for the GSC and the DC-DC converter which yield accomplishment of the desired control objectives. Effectiveness of the proposed approach is demonstrated through numerical simulations on the IEEE 24-bus power system under critical scenarios. [ABSTRACT FROM AUTHOR]

Due to a high penetration of renewable energy, power systems operational planning today needs to capture unprecedented uncertainties in a short period. Fast probabilistic state estimation (SE), which creates probabilistic load flow estimates, represents one such planning tool. This paper describes a graphical model for probabilistic SE modeling that captures both the uncertainties and the power grid via embedding physical laws, i.e., KCL and KVL. With such a modeling, the resulting maximum a posteriori (MAP) SE problem is formulated by measuring state variables and their interactions. To resolve the computational difficulty in calculating the marginal distribution for interested quantities, a distributed message passing method is proposed to compute MAP estimates using increasingly available cyber resources, i.e., computational and communication intelligence. A modified message passing algorithm is then introduced to improve the convergence and optimality. Simulation results illustrate the probabilistic SE and demonstrate the improved performance over traditional deterministic approaches via: 1) the more accuracy mean estimate; 2) the confidence interval covering the true state; and 3) the reduced computational time. [ABSTRACT FROM AUTHOR]

A grand challenge for state estimation in newly built smart grid lies in how to deal with the increasing uncertainties. To solve the problem, we propose a data-driven state estimation approach based on recent targeted investment on sensors, data storage, and computing devices. An architecture is proposed to use power system physics and pattern to systematically clean historical data and conduct supervised learning, where historical similar measurements and their states are used to learn the relationship between the current measurement and the state. In order to deal with nonlinearity, kernel trick is used to produce linear mapping in a carefully selected higher dimensional space. To speed up the data-driven approach for online services, we analyze power system data set and discover its clustering property due to the periodic pattern of power systems. This leads to significant dimension reduction and the idea of preorganizing data points in a tree structure for inquiry, leading to 1000 times speedup. Numerical results show that the proposed data-driven approach works well in a smart grid setting with increasing uncertainties and it produces an online state estimate excelling current industrial approach. [ABSTRACT FROM PUBLISHER]

This special issue brings together recent research on the efficient use of energy in commercial, residential, and other types of buildings and facilities. [ABSTRACT FROM AUTHOR]

In this paper, we propose an information exchange framework to incorporate smart building demands into a microgrid operation. We especially focus on scheduling smart building demand along with other possibly highly uncertain microgrid generation resources a day ahead or shorter ahead of operation. Since every building demand has different energy consumption profiles and dynamics, it is inefficient for the grid operator to directly control a potentially large number of buildings. On the other hand, if the grid operator does not have sufficient information on the buildings and their resource potentials, smart buildings cannot be deployed to the full extent. Our proposed framework attempts to align these conflicting objectives in a reasonable way, taking into consideration the realistic limitations of communication time, various physical characteristics and dynamics of the buildings, and the building managers' economic objectives. This framework is in line with the concept of dynamic monitoring and decision systems (DYMONDS), where the economic objectives and physical dynamics of any flexible generation and loads on the grid are aggregated by load aggregators and incorporated in the optimal system operation. [ABSTRACT FROM AUTHOR]

The essential oil isolated fromErica spiculifoliaSalisb. by hydrodistillation was analysed by GC-MS. One hundred compounds representing 92.6% of total oil were identified. Among the detected compounds 38 were monoterpenoids (46.2%), 30 were sesquiterpenoids (31.7%), 2 diterpene (0.4%) and 30 compounds (14.3%) were with various non-terpenoid structures. Oxygenated monoerpenes were by far the main class (45.3%) with α-terpineol (7.5%)endo-borneol (7.2%), pinocarveol (5.9%) and thymol (3.7%) as the major compounds. The predominant components of sesquiterpenes were caryophyllene oxide (5.0%), caryophyllene (4.2%), τ –murrolol (3.5%), spathulenol (2.9) and α-cadinol (2.3%). [ABSTRACT FROM PUBLISHER]

This paper concerns a novel approach to the modeling and control design for transient stabilization of electric power systems using Flexible Alternating Current Transmission System (FACTS) devices. A nonlinear dynamic model of general interconnected electric power systems in the ordinary differential equation (ODE) form is proposed in terms of time-varying phasors of all dynamic components. This model captures previously unmodeled fast dynamics of inductors and capacitors of FACTS. Additionally, it allows us to observe the active power which is flowing through FACTS during transients. Using the derived model, an ectropy-based FACTS controller is proposed. The proposed controller regulates the active power through FACTS in order to shift the increment in energy created by disturbances. The energy increment is directed from generators into FACTS, preserving the synchronization between generators during disturbances. Simulation results obtained on the IEEE 14-bus system demonstrate the potential of this controller. The controller is shown to increase critical clearing time of the system in the case of a fault. [ABSTRACT FROM AUTHOR]

This paper introduces a novel multi-control area framework for explicit modeling, managing, and accounting of simultaneous bilateral transactions with specified contract paths. Our framework provides a modular and multi-layered electrical network representation with zooming-in and zooming-out capabilities. The zoomed-out representation concerns interconnections and inter-area transactions, while the zoomed-in representation concerns a single area and its internal transactions. The framework allows explicit modeling of bilateral transactions with contract paths through a transformation of a meshed electrical network into a spanning tree. Loop flows are introduced to represent a deviation between the contract paths of bilateral transactions and physical line flows. The effects of both intra-area and inter-area bilateral transactions and loop flows can be graphically traced in the framework. Moreover, these tracing methods allocate bilateral transactions to line flows and loop flows, essential for accounting and flow control. Our tracing methods differ from the distribution factor based method because the distribution factor matrix handles nodal injections only and it cannot account for contract paths of bilateral transactions and the resulting loop flows. The multi-layered network transformations and tracing methods are illustrated on the IEEE 14-bus system. [ABSTRACT FROM AUTHOR]

This paper defines flow control algorithms for loop flow cancellation based on the allocation and tracing of bilateral transactions and loop flows. In Part I of this paper, we have shown that the main difference between transportation and electrical networks is caused by the existence of loop flows. We have introduced a distributed framework for the modeling and tracing of bilateral transactions and the corresponding loop flows. Its zooming-out capability provides a valuable mechanism for representing external (inter-area) loop flows based on simplified topologies of individual areas. The tracing information accurately allocates bilateral transactions with associated contract paths to line flows and loop flows. Furthermore, this information can be used for determining the set points of control equipment so that loop flows are minimized. In this framework, phase angle regulators (PARs), commonly used for line flow control, are represented through their effects on loop flows. We define sufficient conditions for achieving complete loop flow cancellation. A new distributed algorithm for determining PAR set points in a coordinated way without revealing operating conditions of individual areas is introduced in this part. Finally, complete loop flow cancellation and the distributed algorithm for finding PAR set points are demonstrated in the Reliability Test System (RTS) 96-bus system with wheeling loop flows. [ABSTRACT FROM AUTHOR]

This paper investigates the application of stochastic dynamic programming to the optimization of charging and frequency regulation capacity bids of an electric vehicle (EV) in a smart electric grid environment. We formulate a Markov decision problem to minimize an EV's expected cost over a fixed charging horizon. We account for both Markov random prices and a Markov random regulation signal. We also propose an enhancement to the classical discrete stochastic dynamic programming method. This enhancement allows optimization over a continuous space of decision variables via linear programming at each state. Simple stochastic process models are built from real data and used to simulate the implementation of the proposed method. The proposed method is shown to outperform deterministic model predictive control in terms of average EV charging cost. [ABSTRACT FROM PUBLISHER]

This paper concerns mathematical conditions under which a system-level optimization of supply and demand scheduling can be implemented as a distributed optimization in which users and suppliers, as well as the load serving entities, are decision makers with well-defined sub-objectives. We start by defining the optimization problem of the system that includes the sub-objectives of many different players, both supply and demand entities in the system, and decompose the problem into each player's optimization problem, using Lagrange dual decomposition. A demand entity or a load serving entity's problem is further decomposed into problems of the many different end-users that the load serving entity serves. By examining the relationships between the global objectives and the local/individual objectives in these multiple layers and the optimality conditions of these decomposable problems, we define the requirements of these different objectives to converge. We propose a novel set of methods for coordinating supply and demand over different time horizons, namely day-ahead scheduling and real-time adjustment. We illustrate the ideas by simulating simple examples with different conditions and objectives of each entity in the system. [ABSTRACT FROM PUBLISHER]

This paper presents an information-theoretic approach to address the phasor measurement unit (PMU) placement problem in electric power systems. Different from the conventional ‘topological observability’ based approaches, this paper advocates a much more refined, information-theoretic criterion, namely the mutual information (MI) between PMU measurements and power system states. The proposed MI criterion not only includes observability as a special case, but also rigorously models the uncertainty reduction on power system states from PMU measurements. Thus, it can generate highly informative PMU configurations. The MI criterion can also facilitate robust PMU placement by explicitly modeling probabilistic PMU outages. We propose a greedy PMU placement algorithm, and show that it achieves an approximation ratio of (1-1/e) for any PMU placement budget. We further show that the performance is the best that one can achieve, in the sense that it is NP-hard to achieve any approximation ratio beyond (1-1/e). Such performance guarantee makes the greedy algorithm very attractive in the practical scenario of multi-stage installations for utilities with limited budgets. Finally, simulation results demonstrate near-optimal performance of the proposed PMU placement algorithm. [ABSTRACT FROM PUBLISHER]

The integration of distributed energy resources (DER) in low-voltage networks is expected to increase significantly in the next few years. It is known that the large-scale integration of DER in conventional low-voltage (LV) networks poses many challenges such as voltage rise. To mitigate voltage rise caused by DER, utilities are defining simple voltage regulation strategies such as disconnecting DER when phase voltages rise above a defined threshold. In this paper, we model LV networks as three-phase unbalanced circuits and illustrate that such local regulation strategies may cause the cascading of the DER in a feeder. We then propose an optimal control approach to avoid cascading and optimize DER availability. Local control approaches are discussed in the context of global DER availability and their limitations are illustrated. [ABSTRACT FROM PUBLISHER]

This paper investigates the distribution system impacts of electric vehicle (EV) charging. The analysis is based on a large number of operational distribution networks in The Netherlands. Future load profiles have been constructed by adding different EV charging profiles to household loads and solving the power flows to assess the network impacts on various network levels. The results indicate that controlled charging of EVs leads to significant reduction of overloaded network components that have to be replaced, but the impact varies per network level. Overall, in the uncontrolled charging scenarios roughly two times more replacements are needed compared to the controlled charging scenario. Furthermore, it was shown that for the controlled charging scenario the overall reduction in net present value due to energy losses and the replacement of overloaded network components is approximately 20% in comparison with the uncontrolled charging scenario. The results suggest that the deployment of a flexible and intelligent distribution network is a cost-beneficial way to accommodate large penetrations of EVs. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of electricity cost management for Internet service providers with a collection of spatially distributed data centers. As the demand on Internet services and cloud computing has kept increasing in recent years, the power usage associated with IDC operations has been uprising significantly. The cyber and physical aspects of IDCs interact with each other, and bring unprecedented challenges in power management. While most existing research focuses on reducing power consumptions of IDCs at one specific location, the problem of reducing the total electricity cost has been overlooked. This is an important problem faced by service providers, especially in the present multielectricity-market environment, where the price of electricity may exhibit temporal and spatial diversities. Further, for these service providers, guaranteeing the quality of service (QoS; i.e., service level objectives) such as service delay guarantees to the end users is of critical importance. This paper studies the problem of minimizing the total electricity cost geared to QoS constraint as well as the location diversity and time diversity of electricity price under multiregional electricity markets. We jointly consider both the cyber and physical management capabilities of IDCs, and exploit both the center-level load balancing and the server-level power control in a unified scheme. We model the problem as a constrained mixed integer programming based on generalized benders decomposition (GBD) technique. Extensive evaluations based on real-life electricity price data for multiple IDC locations demonstrate the effectiveness of our scheme. [ABSTRACT FROM PUBLISHER]

In Part II of this paper, we demonstrate on a modified 24-bus IEEE Reliability Test System (RTS) that it is indeed possible to manage large-scale intermittent resources in coordination with price-responsive demand. The algorithms introduced in Part I of this paper are simulated assuming 20% and 50% wind capacity. We show that the look-ahead dispatch of the proposed method is physically implementable and, when used with elastic demand, can accommodate the integration of close to 50% wind capacity. This is contrasted with the observation that, without elastic demand, 50% wind integration is not physically implementable. From the perspective of total market surplus, the predictive dispatch of the proposed method is 3.8% suboptimal when compared to the centralized most efficient predictive economic dispatch. Further simulations are needed to test the feasibility of coordinating wind power and price-responsive demand on realistic large-scale power systems. [ABSTRACT FROM PUBLISHER]

In Part I of this two-part paper, we introduce several possible methods for integrating wind power, price-responsive demand and other distributed energy resources (DERs). These methods differ with respect to information exchange requirements, computational complexity, and physical implementability. A novel look-ahead interactive dispatch that internalizes inter-temporal constraints at the DERs level, and dispatches the results of distributed decisions subject to spatial security constraints, is proposed as a possible effective algorithm. This method requires only the use of today's static security-constrained economic dispatch (SCED) by the system operators. The optimization accounting for inter-temporal constraints, and ramping rates in particular, is done by the DERs while they create their own supply and demand functions. To implement this method, today's supervisory control and data acquisition (SCADA) needs to be transformed into a multi-directional, multi-layered information exchange system. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new framework for the organization of the electric power industry, based on extensive use of information technology (IT) and on interactive decision making, where consumers and distributed producers join the traditional actors, utilities in particular, in making decisions. While many ideas considered in this paper have been put forward in recent years, such as the need to manage intermittency of renewable resources by means of proactive forecasting, and coordination with responsive demand and storage, we introduce a possible systematic IT-enabled mechanism necessary for the actual implementation of these technologies. We point out that in order to achieve a long-term sustainable energy utilization, it is essential to provide on-line information to internalize the value of just-in-time, just-in-place, and just-in-context distributed adaptation across the entire supply chain, ranging from the smallest consumers and energy providers, through their aggregators and system coordinators. We illustrate using our model-based novel simulator, how a carefully designed multidirectional and multitemporal information exchange could enable sustainable decision making while accounting for unique needs and capabilities of various resources and users. At the same time, information incentivizes the resources and users to contribute to system-wide sustainability objectives at value. We illustrate the dependence of such decisions-driven industry evolution on the industry rules (choice of performance objectives), as well as on the operating and planning practices for implementing the industry rules (temporal and spatial factors). Our model-based simulator could be used as a means of designing novel regulation defining rules, rights, and responsibilities regarding the type and rate of information to be exchanged in support of sustainable industry evolution. [ABSTRACT FROM PUBLISHER]