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This paper develops a representation of the Northeastern U.S. bulk electric power system, with an emphasis on New York and New England. The representation has two parts: a 36-bus electrical model in PTI-23 format and market data in the form of generator bids and load demands. The market data are distilled from historical data on public web sites. Since the historical data are available on an hourly basis over many years, the representation is quite rich. In addition, this paper includes the mix of generation at each bus in the model so that generation cost (fuel and emissions) and unit commitment constraints can be deduced. The representation is intended to be a test-bed for formulating, simulating and analyzing the combined technical and economic objectives of the changing electric power industry. It is further intended to be a test-bed for comparing methods of simulating electric power systems and electricity markets operating under engineering constraints. It can, for example, be used for power flow, optimal power flow, reliability, market clearing, and other economic studies. The representation as described is intended only for steady-state equilibrium studies and does not account for inter-temporal effects such as unit commitment constraints. It can, however, be extended to account for those effects. Index Terms--Electric power test systems, electricity markets, engineering and economics of electric power systems, power systems economics.

This paper presents a novel model for optimization of investments in new power generation under uncertainty. The model can calculate optimal investment strategies under both centralized social welfare and decentralized profit objectives. The power market is represented with linear supply and demand curves. A stochastic dynamic programming algorithm is used to solve the investment problem, where uncertainty in demand is represented as a discrete Markov chain. The stochastic dynamic model allows us to evaluate investment projects in new base and peak load power generation as real options, and determine optimal timing of the investments. In a case study, we use the model to compare optimal investment strategies under centralized and decentralized decision making. A number of interesting results follow by varying the assumptions about market structure and price response on the demand side. Index Terms--Centralized and decentralized decision making, generation expansion planning, real options, restructured power systems, stochastic dynamic optimization.

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]

Byline: Le Xie, Marija D. Ilic This paper introduces a module-based approach to modelling and controlling electricity infrastructure with a high penetration of distributed renewable energy resources. Each energy-converting component is defined as a module and is represented in terms of its local variables and the interaction variables between the module and the transmission network. The structure of the electricity infrastructure is preserved in the proposed dynamical model. Therefore, it is possible to specify the performance subobjectives of each module for a given range of variations in interaction variables and to ensure that the local subobjectives are met through multidirectional distributed sensing and actuation. This approach provides a systematic means of analysing the infrastructure dynamics with increasing penetration of distributed renewable energy resources such as wind and solar. Sufficient conditions on modules and network specifications are derived under which the system-wide dynamics are stabilised. Based on these conditions, an interactive communication protocol between the modules and system operator could be implemented for distributed stabilisation. An IEEE 14 bus system is used to illustrate the concepts put forward.

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 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 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]