Showing papers in "Journal of Modern Power Systems and Clean Energy in 2017"
TL;DR: In this paper, the state of the art and industry practice on demand response and the new methodology of transactive energy is reviewed, and the design of demand response programs, performance of pilot projects and programs, consumer behaviors, and barriers are discussed.
Abstract: This paper reviews the state of the art of research and industry practice on demand response and the new methodology of transactive energy. Demand response programs incentivize consumers to align their demand with power supply conditions, enhancing power system reliability and economic operation. The design of demand response programs, performance of pilot projects and programs, consumer behaviors, and barriers are discussed. Transactive energy is a variant and a generalized form of demand response in that it manages both the supply and demand sides. It is intended for a changing environment with an increasing number of distributed resources and intelligent devices. It utilizes the flexibility of various generation/load resources to maintain a dynamic balance of supply and demand. These distributed resources are controlled by their owners. However, the design of transaction mechanisms should align the individual behaviors with the interests of the entire system. Transactive energy features real-time, autonomous, and decentralized decision making. The transition from demand response to transactive energy is also discussed.
212 citations
TL;DR: In this article, a comprehensive review of existing location methods, which basically fall into four major categories, plus a few other methods, is presented, and a practical, general scheme for oscillation source location using available location methods is suggested and analyzed.
Abstract: The deployment of a synchrophasor-based wide-area measurement system (WAMS) in a power grid largely improves the observability of power system dynamics and the operator’s real-time situational awareness for potential stability issues. The WAMS in many power grids has successfully captured system oscillation events, e.g. poorly damped natural oscillations and forced oscillations, from time to time. To identify the root cause of an observed oscillation event for further mitigation actions, many methods have been proposed to locate the source of oscillation based on different ideas and principles. However, most methods proposed so far for locating the oscillation source in a power grid are not reliable enough for practical applications. This paper presents a comprehensive review of existing location methods, which basically fall into four major categories, plus a few other methods. Their advantages and disadvantages are discussed in detail. Some trends and challenges on the problem of oscillation source location are pointed out along with potential future research directions. Finally, a practical, general scheme for oscillation source location using available location methods is suggested and analyzed.
108 citations
TL;DR: In this article, a costbenefit analysis based optimal planning model of battery energy storage system (BESS) in active distribution system (ADS) is established considering a new BESS operation strategy.
Abstract: In this paper, a cost-benefit analysis based optimal planning model of battery energy storage system (BESS) in active distribution system (ADS) is established considering a new BESS operation strategy. Reliability improvement benefit of BESS is considered and a numerical calculation method based on expectation is proposed for simple and convenient calculation of system reliability improvement with BESS in planning phase. Decision variables include both configuration variables and operation strategy control variables. In order to prevent the interaction between two types of variables and enhance global search ability, intelligent single particle optimizer (ISPO) is adopted to optimize this model. Case studies on a modified IEEE benchmark system verified the performance of the proposed operation strategy and optimal planning model of BESS.
105 citations
TL;DR: In this paper, the challenges with integrating ultra-high levels of VRE into electric power system, reviews a range of solutions to these challenges, and provides a description of several examples of ultra high VRE systems that are in operation today.
Abstract: As more variable renewable energy (VRE) such as wind and solar are integrated into electric power systems, technical challenges arise from the need to maintain the balance between load and generation at all timescales. This paper examines the challenges with integrating ultra-high levels of VRE into electric power system, reviews a range of solutions to these challenges, and provides a description of several examples of ultra-high VRE systems that are in operation today.
104 citations
TL;DR: In this paper, the authors introduce the concept and main features of transactive control, followed by a literature review and demonstration projects that apply to transactional control, and cases are then presented to illustrate the transactual control framework.
Abstract: The increasing number of distributed energy resources connected to power systems raises operational challenges for the network operator, such as introducing grid congestion and voltage deviations in the distribution network level, as well as increasing balancing needs at the whole system level. Control and coordination of a large number of distributed energy assets requires innovative approaches. Transactive control has received much attention due to its decentralized decision-making and transparent characteristics. This paper introduces the concept and main features of transactive control, followed by a literature review and demonstration projects that apply to transactive control. Cases are then presented to illustrate the transactive control framework. At the end, discussions and research directions are presented, for applying transactive control to operating power systems, characterized by a high penetration of distributed energy resources.
91 citations
TL;DR: In this paper, a robust day-ahead scheduling model for the optimal coordinated operation of integrated energy systems while considering key uncertainties of the power system and natural gas system operation cost is proposed.
Abstract: The increasing interdependency of electricity and natural gas systems promotes coordination of the two systems for ensuring operational security and economics. This paper proposes a robust day-ahead scheduling model for the optimal coordinated operation of integrated energy systems while considering key uncertainties of the power system and natural gas system operation cost. Energy hub, with collocated gas-fired units, power-to-gas (PtG) facilities, and natural gas storages, is considered to store or convert one type of energy (i.e., electricity or natural gas) into the other form, which could analogously function as large-scale electrical energy storages. The column-and-constraint generation (C&CG) is adopted to solve the proposed integrated robust model, in which nonlinear natural gas network constraints are reformulated via a set of linear constraints. Numerical experiments signify the effectiveness of the proposed model for handling volatile electrical loads and renewable generations via the coordinated scheduling of electricity and natural gas systems.
88 citations
TL;DR: In this article, the authors present the most critical challenges and prospects for emerging multi-terminal direct current (MTDC) grids, along with a foreseeable technology development roadmap, with a particular focus on crucial control and operational issues associated with MTDC systems and grids.
Abstract: A few multi-terminal direct current (MTDC) systems are in operation around the world today. However, MTDC grids overlaying their AC counterpart might a reality in a near future. The main drivers for constructing such direct current grids are the large-scale integration of remote renewable energy resources into the existing alternative current (AC) grids, and the promotion and development of international energy markets through the so-called supergrids. This paper presents the most critical challenges and prospects for such emerging MTDC grids, along with a foreseeable technology development roadmap, with a particular focus on crucial control and operational issues that are associated with MTDC systems and grids.
82 citations
TL;DR: Demand-side load management (DSM) is 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 as mentioned in this paper.
Abstract: 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.
77 citations
TL;DR: In this paper, an energy hub with both a power-to-hydrogen (P2H) facility (electrolyzer) and a G2P facility (hydrogen gas turbine) is proposed to accommodate a high penetration of wind power, and this optimization problem is solved by a mixed-integer linear programming (MILP) method with the Benders decomposition technique.
Abstract: The increasing integration of variable wind generation has aggravated the imbalance between electricity supply and demand. Power-to-hydrogen (P2H) is a promising solution to balance supply and demand in a variable power grid, in which excess wind power is converted into hydrogen via electrolysis and stored for later use. In this study, an energy hub (EH) with both a P2H facility (electrolyzer) and a gas-to-power (G2P) facility (hydrogen gas turbine) is proposed to accommodate a high penetration of wind power. The EH is modeled and integrated into a security-constrained unit commitment (SCUC) problem, and this optimization problem is solved by a mixed-integer linear programming (MILP) method with the Benders decomposition technique. Case studies are presented to validate the proposed model and elaborate on the technological potential of integrating P2H into a power system with a high level of wind penetration (HWP).
76 citations
TL;DR: In this paper, the authors proposed an operational model of an energy hub (EH) in a residential area to optimize the total energy cost in an operational scenario with solar photovoltaic (PV) generation, solar heat exchanger (SHE), and battery energy storage system.
Abstract: This paper aims to optimize total energy costs in an operational model of a novel energy hub (EH) in a residential area. The optimization problem is set up based on daily load demand (such as electricity, heat, and cooling) and time-of-use (TOU) energy prices. The extended EH model considers the involvement of solar photovoltaic (PV) generation, solar heat exchanger (SHE), and a battery energy storage system (BESS). A mathematical model is constructed with the objective of optimizing total energy cost during the day, including some constraints such as input-output energy balance of the EH, electricity price, capacity limitation of the system, and charge/discharge power of BESS. Four operational cases based on different EH structures are compared to assess the effect of solar energy applications and BESS on the operational efficiency. The results show that the proposed model predicts significant changes to the characteristics of electricity and gas power bought from utilities, leading to reduced total energy cost compared to other cases. They also indicate that the model is appropriate for the characteristics of residential loads.
67 citations
TL;DR: The transient characteristics of DC faults in a modular multilevel converter (MMC) based DC system combining with the numerical method is analyzed to provide the theoretical foundation for the design of dc fault protection strategy.
Abstract: DC fault protection is the key technique for the development of the DC distribution and transmission system. This paper analyzes the transient characteristics of DC faults in a modular multilevel converter (MMC) based DC system combining with the numerical method. Meanwhile, lots of simulation tests based on MATLAB/Simulink are carried out to verify the correctness of the theoretical analysis. Finally, the technological difficulties of and requirements for the protection and isolation are discussed to provide the theoretical foundation for the design of dc fault protection strategy.
TL;DR: In this paper, a probabilistic optimal power flow (POPF) calculation based on a three-point estimate method (3PEM) is adopted to address the uncertainties originating from wind power and load forecasting, and power-to-gas (PtG) units are employed to avoid wind power curtailment and enable flexible bi-directional energy flows between the coupled energy systems.
Abstract: The increasing adoption of gas-fired power plants directly strengthens the coupling between electric power and natural gas systems. Current industrial practice in optimal power flow for electric power systems has not taken the security constraints of gas systems into consideration, resulting in an overly-optimistic solution. Meanwhile, the operation of electric power and natural gas systems is coupled over multiple periods because of the ramp rate limits of power generators and the slow dynamical characteristics of gas systems. Based on these motivations, we propose a multi-period integrated natural gas and electric power system probabilistic optimal power flow (M-GEPOPF) model, which includes dynamic gas flow models. To address the uncertainties originating from wind power and load forecasting, a probabilistic optimal power flow (POPF) calculation based on a three-point estimate method (3PEM) is adopted. Moreover, power-to-gas (PtG) units are employed to avoid wind power curtailment and enable flexible bi-directional energy flows between the coupled energy systems. An integrated IEEE RTS 24-bus electric power system and the Belgian 20-node natural gas system are employed as a test case to verify the applicability of the proposed M-GEPOPF model, and to demonstrate the potential economic benefits of PtG units.
TL;DR: In this paper, the authors provide an overview of the current status of the power electronics technology, one of the key actors in the upcoming smart grid paradigm enabling maximum power throughputs and near-instantaneous control of voltages and currents in all links of power system chain.
Abstract: The main objective of this paper is three-fold. First, to provide an overview of the current status of the power electronics technology, one of the key actors in the upcoming smart grid paradigm enabling maximum power throughputs and near-instantaneous control of voltages and currents in all links of the power system chain. Second, to provide a bridge between the power systems and the power electronic communities, in terms of their differing appreciation of how these devices perform when connected to the power grid. Third, to discuss on the role that the power electronics technology will play in supporting the aims and objectives of future decarbonized power systems. This paper merges the equipment, control techniques and methods used in flexible alternating current transmission systems (FACTS) and high voltage direct transmission (HVDC) equipment to enable a single, coherent approach to address a specific power system problem, using ‘best of breed’ solutions bearing in mind technical, economic and environmental issues.
TL;DR: In this paper, the authors provide an overview of the analysis technique of forced oscillations in power systems and some future opportunities are discussed in forced oscillation studies, which can be classified into free oscillations and forced ones.
Abstract: The oscillations in a power system can be categorized into free oscillations and forced oscillations. Many algorithms have been developed to estimate the modes of free oscillations in a power system. Recently, forced oscillations have caught many researchers’ attentions. Techniques are proposed to detect forced oscillations and locate their sources. In addition, forced oscillations may have a negative impact on the estimation of mode and mode-shape if they are not properly accounted for. To improve the power system reliability and dynamic properties, it is important to first distinguish forced oscillations from free oscillations and then locate the sources of forced oscillations in a timely manner. The negative impact of forced oscillation can be mitigated when they are detected and located. This paper provides an overview of the analysis technique of forced oscillations in power systems. In addition, some future opportunities are discussed in forced oscillation studies.
TL;DR: Wang et al. as mentioned in this paper proposed a novel hybrid method using Boosting algorithm and a multi-step forecast approach to improve the forecasting capacity of traditional ARMA model, and calculated the existing error bounds of the proposed method.
Abstract: Day-ahead wind power forecasting plays an essential role in the safe and economic use of wind energy, the comprehending- intrinsic complexity of the behavior of wind is considered as the main challenge faced in improving forecasting accuracy. To improve forecasting accuracy, this paper focuses on two aspects: ①proposing a novel hybrid method using Boosting algorithm and a multi-step forecast approach to improve the forecasting capacity of traditional ARMA model; ②calculating the existing error bounds of the proposed method. To validate the effectiveness of the novel hybrid method, one-year period of real data are used for test, which were collected from three operating wind farms in the east coast of Jiangsu Province, China. Meanwhile conventional ARMA model and persistence model are both used as benchmarks with which the proposed method is compared. Test results show that the proposed method achieves a more accurate forecast.
TL;DR: In this article, the authors discuss current development status and potential application of power-to-gas (PtG) plants in the future interconnected multi-energy systems, and further analyzes the costs and benefits of PtG plants in different application scenarios.
Abstract: Regarded as a long-term, large capacity energy storage solution, commercialized power-to-gas (PtG) technology has attracted much research attention in recent years. PtG plants and natural gas-fired power plants can form a close loop between an electric power system and a natural gas network. An interconnected multi-energy system is believed to be a solution to the future efficient and environmental friendly energy systems. However, some crucial issues require in-depth analysis before PtG plants can be economically implemented. This paper discusses current development status and potential application of PtG plants in the future interconnected multi-energy systems, and further analyzes the costs and benefits of PtG plants in different application scenarios. In general, the PtG plants are not economical efficient based on current technologies and costs. But the situation is likely to change with the development of PtG technologies and interconnected operation of gas-electricity energy system.
TL;DR: Pair-Copula theory has been introduced to construct a multivariate model which can fully considers the margin distribution and stochastic dependence characteristics of wind power forecasting errors, and model comparisons indicate that the proposed model can reveal the essential relationships ofWind power forecasting uncertainty, and describe the various dependences more accurately.
Abstract: The uncertainty of wind power forecasting significantly influences power systems with high percentage of wind power generation. Despite the wind power forecasting error causation, the temporal and spatial dependence of prediction errors has done great influence in specific applications, such as multistage scheduling and aggregated wind power integration. In this paper, Pair-Copula theory has been introduced to construct a multivariate model which can fully considers the margin distribution and stochastic dependence characteristics of wind power forecasting errors. The characteristics of temporal and spatial dependence have been modelled, and their influences on wind power integrations have been analyzed. Model comparisons indicate that the proposed model can reveal the essential relationships of wind power forecasting uncertainty, and describe the various dependences more accurately.
TL;DR: In this article, the frequency control strategy of DR for a multi-area power system is specially designed, and the tie-line power is adopted as the additional input signal of DR.
Abstract: Over the last few years, lots of attentions have been given to the demand response (DR) for the frequency control. DR can be incorporated with traditional frequency control method and enhance the stability of the system. In this paper, the frequency control strategy of DR for a multi-area power system is specially designed. In order to quickly stabilize the frequency of different areas, the tie-line power is adopted as the additional input signal of DR. To get the optimal parameters of the control system, the frequency control problem is formulated as a multi-objective optimization problem, and the parameters such as the integral gains of secondary frequency control, the frequency bias parameters, and coefficients of DR are optimized. Numerical results verify the effectiveness of the proposed method.
TL;DR: In this paper, a model predictive control strategy for microgrid economic dispatch, where hourly schedule is constantly optimized according to the current system state and latest forecast information, is proposed, where implicit network topology of the microgrid and corresponding power flow constraints are considered, leading to a mixed integer nonlinear optimal power flow problem.
Abstract: To deal with uncertainties of renewable energy, demand and price signals in real-time microgrid operation, this paper proposes a model predictive control strategy for microgrid economic dispatch, where hourly schedule is constantly optimized according to the current system state and latest forecast information. Moreover, implicit network topology of the microgrid and corresponding power flow constraints are considered, which leads to a mixed integer nonlinear optimal power flow problem. Given the non-convexity feature of the original problem, the technique of conic programming is applied to efficiently crack the nut. Simulation results from a reconstructed IEEE-33 bus system and comparisons with the routine day-ahead microgrid schedule sufficiently substantiate the effectiveness of the proposed MPC strategy and the conic programming method.
TL;DR: In this article, a distributed energy management method for interconnected operations of combined heat and power (CHP)-based MGs with demand response (DR) is proposed, where the DR is modeled as a virtual generation unit and the optimal scheduling model is decentralized as several distributed scheduling models in accordance with the number of associated MGs.
Abstract: From the perspective of transactive energy, the energy trading among interconnected microgrids (MGs) is promising to improve the economy and reliability of system operations. In this paper, a distributed energy management method for interconnected operations of combined heat and power (CHP)-based MGs with demand response (DR) is proposed. First, the system model of operational cost including CHP, DR, renewable distributed sources, and diesel generation is introduced, where the DR is modeled as a virtual generation unit. Second, the optimal scheduling model is decentralized as several distributed scheduling models in accordance with the number of associated MGs. Moreover, a distributed iterative algorithm based on subgradient with dynamic search direction is proposed. During the iterative process, the information exchange between neighboring MGs is limited to Lagrange multipliers and expected purchasing energy. Finally, numerical results are given for an interconnected MGs system consisting of three MGs, and the effectiveness of the proposed method is verified.
TL;DR: In this article, a short-term operation model of a district heating system is proposed to optimally schedule the production of both heat and power in a system with high wind power penetration.
Abstract: The integration of continuously varying and not easily predictable wind power generation is affecting the stability of the power system and leads to increasing demand for balancing services. In this study, a short-term operation model of a district heating system is proposed to optimally schedule the production of both heat and power in a system with high wind power penetration. The application of the model in a case study system shows the increased flexibility offered by the coordination of power generation, consumption and heat storage units which are available in district heating systems.
TL;DR: In this paper, a kernel density estimation (KDE) method is proposed to estimate the probability density function (PDF) of wind speed, without making any assumption on the form of the underlying wind speed distribution, and capable of uncovering the statistical information hidden in the historical data.
Abstract: An accurate probability distribution model of wind speed is critical to the assessment of reliability contribution of wind energy to power systems. Most of current models are built using the parametric density estimation (PDE) methods, which usually assume that the wind speed are subordinate to a certain known distribution (e.g. Weibull distribution and Normal distribution) and estimate the parameters of models with the historical data. This paper presents a kernel density estimation (KDE) method which is a nonparametric way to estimate the probability density function (PDF) of wind speed. The method is a kind of data-driven approach without making any assumption on the form of the underlying wind speed distribution, and capable of uncovering the statistical information hidden in the historical data. The proposed method is compared with three parametric models using wind data from six sites. The results indicate that the KDE outperforms the PDE in terms of accuracy and flexibility in describing the long-term wind speed distributions for all sites. A sensitivity analysis with respect to kernel functions is presented and Gauss kernel function is proved to be the best one. Case studies on a standard IEEE reliability test system (IEEE-RTS) have verified the applicability and effectiveness of the proposed model in evaluating the reliability performance of wind farms.
TL;DR: In this article, the authors proposed a DR-based congestion management strategy for smart distribution systems, which is based on a bi-level optimization model for the day-ahead congestion management based on the proposed framework.
Abstract: In recent years, much attention has been devoted to the development and applications of smart grid technologies, with special emphasis on flexible resources such as distributed generations (DGs), energy storages, active loads, and electric vehicles (EVs). Demand response (DR) is expected to be an effective means for accommodating the integration of renewable energy generations and mitigating their power output fluctuations. Despite their potential contributions to power system secure and economic operation, uncoordinated operations of these flexible resources may result in unexpected congestions in the distribution system concerned. In addition, the behaviors and impacts of flexible resources are normally highly uncertain and complex in deregulated electricity market environments. In this context, this paper aims to propose a DR based congestion management strategy for smart distribution systems. The general framework and procedures for distribution congestion management is first presented. A bi-level optimization model for the day-ahead congestion management based on the proposed framework is established. Subsequently, the robust optimization approach is introduced to alleviate negative impacts introduced by the uncertainties of DG power outputs and market prices. The economic efficiency and robustness of the proposed congestion management strategy is demonstrated by an actual 0.4 kV distribution system in Denmark.
TL;DR: A directed graph-based method for distribution network reconfiguration considering distributed generation is presented, and the concepts of “in-degree and out-degree” are presented to ensure the radial structure of the distribution network and the connectivity of charged nodes in every independent power supply area are developed.
Abstract: We present a directed graph-based method for distribution network reconfiguration considering distributed generation Two reconfiguration situations are considered: operation mode adjustment with the objective of minimizing active power loss (situation I) and service restoration with the objective of maximizing loads restored (situation II) These two situations are modeled as a mixed integer quadratic programming problem and a mixed integer linear programming problem, respectively The properties of the distribution network with distributed generation considered are reflected as the structure model and the constraints described by directed graph More specifically, the concepts of “in-degree” and “out-degree” are presented to ensure the radial structure of the distribution network, and the concepts of “virtual node” and “virtual demand” are developed to ensure the connectivity of charged nodes in every independent power supply area The validity and effectiveness of the proposed method are verified by test results of an IEEE 33-bus system and a 5-feeder system
TL;DR: In this article, the authors proposed a security-constrained unit commitment (SCUC) model to economically schedule generating units without compromising the system reliability by including dynamic gas constraints, such as the line pack, and transmission contingencies in power and gas networks.
Abstract: One of the main factors impacting the reliability of energy systems nowadays is the growing interdependence between electricity and gas networks due to the increase in the installation of gas-fired units. Security-constrained unit commitment (SCUC) models are used to economically schedule generating units without compromising the system reliability. This paper proposes a novel SCUC formulation that includes dynamic gas constraints, such as the line pack, and transmission contingencies in power and gas networks for studying the integrated system reliability. A Benders’ decomposition with linear programming techniques is developed to be able to study large systems. By including dynamic gas constraints into the SCUC, the proposed model accounts for the flexibility and reliability that power systems require from gas systems in the short term. Case studies of different size and complexity are employed to illustrate how the reliability of one system is affected by the reliability of the other. These experiments show how both systems operate in a secure way (by including contingencies) increases operating costs by approximately 9% and also show how these costs can vary by 24% depending on the line pack scheduling.
TL;DR: In this paper, a multi-slack bus model is proposed to calculate the power and gas flow in the coupled system, in which the cumulant method and Gram-Charlier expansion are first presented to obtain the distribution of state variables after considering the effects of uncertain factors.
Abstract: The natural gas system and electricity system are coupled tightly by gas turbines in an integrated energy system. The uncertainties of one system will not only threaten its own safe operation but also be likely to have a significant impact on the other. Therefore, it is necessary to study the variation of state variables when random fluctuations emerge in the coupled system. In this paper, a multi-slack-bus model is proposed to calculate the power and gas flow in the coupled system. A unified probabilistic power and gas flow calculation, in which the cumulant method and Gram–Charlier expansion are applied, is first presented to obtain the distribution of state variables after considering the effects of uncertain factors. When the variation range of random factors is too large, a new method of piecewise linearization is put forward to achieve a better fitting precision of probability distribution. Compared to the Monte Carlo method, the proposed method can reduce computation time greatly while reaching a satisfactory accuracy. The validity of the proposed methods is verified in a coupled system that consists of a 15-node natural gas system and the IEEE case24 power system.
TL;DR: In this article, the authors present a modeling and optimization approach to the operational planning of electric power and natural gas systems, taking into account different energy storage facilities, such as water reservoirs, natural gas storages and line packs of pipelines.
Abstract: The growing installation of natural gas fired power plants has increased the integration of natural gas and electricity sectors. This has driven the need investigate the interactions among them and to optimize energy resources management from a centralized planning perspective. Thus, a combined modeling of the reservoirs involved in electric power and gas systems and their locations on both networks are essential features to be considered in the operational planning of energy resources. This paper presents a modeling and optimization approach to the operational planning of electric power and natural gas systems, taking into account different energy storage facilities, such as water reservoirs, natural gas storages and line packs of pipelines. The proposed model takes advantage of captures both energy systems synergy and their associated networks. This approach identifies the interactions between the energy storage facilities and their economic impact over their optimal scheduling. The results show the benefits of an integrated operational planning of electric power and natural gas systems, the close interdependency between the energy resources stored in both systems, and the effects of a combined scheduling.
TL;DR: In this paper, a combined optimization of a coupled electricity and gas system is presented, where a unit commitment problem with optimization of energy and reserves under a power pool, considering all system operational and unit technical constraints is solved.
Abstract: In this paper a combined optimization of a coupled electricity and gas system is presented. For the electricity network a unit commitment problem with optimization of energy and reserves under a power pool, considering all system operational and unit technical constraints is solved. The gas network subproblem is a medium-scale mixed-integer nonconvex and nonlinear programming problem. The coupling constraints between the two networks are nonlinear as well. The resulting mixed-integer nonlinear program is linearized with the extended incremental method and an outer approximation technique. The resulting model is evaluated using the Greek power and gas system comprising fourteen gas-fired units under four different approximation accuracy levels. The results indicate the efficiency of the proposed mixed-integer linear program model and the interplay between computational requirements and accuracy.
TL;DR: In this paper, the authors proposed a local multi-agent control method for a seamless transfer between the islanded and interconnected modes of operation with agents implemented into the microgrid central switch (MCS) and into microsources inverters.
Abstract: Microgrids can operate either interconnected to the utility grid or disconnected forming an island. The transition between these modes can cause transient overcurrents or power oscillations jeopardizing the equipment safety or the system stability. This paper proposes a local multi agent control method for a seamless transfer between the islanded and interconnected modes of operation with agents implemented into the microgrid central switch (MCS) and into the microsources inverters. The MCS agent supervises the grid status and controls the switch for the transition of the microgrid through the different operation modes, while it communicates locally with the inverter agents of the microsources. The inverter agents undertake the synchronization process in case of reconnecting and change the inverter control mode depending on the grid status. Simulation and experimental results are presented to show the performance and feasibility of the proposed strategy.
TL;DR: In this paper, an agent-based model is proposed to estimate the growth of low-carbon technologies within local neighbourhoods, where social influence is imposed, and a probabilistic approach is outlined, which determines lower and upper bounds for the model response at every neighbourhood.
Abstract: In the near future, various types of low-carbon technologies (LCTs) are expected to be widely employed throughout the United Kingdom. However, the effect that these technologies will have at a household level on the existing low voltage (LV) network is still an area of extensive research. We propose an agent based model that estimates the growth of LCTs within local neighbourhoods, where social influence is imposed. Real-life data from an LV network is used that comprises of many socially diverse neighbourhoods. Both electric vehicle uptake and the combined scenario of electric vehicle and photovoltaic adoption are investigated with this data. A probabilistic approach is outlined, which determines lower and upper bounds for the model response at every neighbourhood. This technique is used to assess the implications of modifying model assumptions and introducing new model features. Moreover, we discuss how the calculation of these bounds can inform future network planning decisions.