Flexible Dispatch Research Articles

Investigating the impact of P2P trading on power losses in grid-connected networks with prosumers

The extensive financial benefit that a prosumer can reap from participating in P2P trading has been shown to be unprecedented by many recent studies. However, since the actual transfer of electricity occurs over the physical network, a key question that yet to answer is: what is the repercussion of P2P trading on the power losses in grid-connected electricity networks? To this end, this paper presents a detailed physical layer analysis of P2P trading to investigate its impact on the network losses. In this paper, P2P transaction losses is defined as one part of network losses and a strategy is proposed to trace P2P transaction losses using effective nodes’ area concept. The other portion of network losses is labelled as grid contributed losses incurred due to the power supplied by the grid to satisfy other customers within and outside effective nodes’ area. Finally, this paper utilises IEEE 8500-node distribution test feeder to capture the large-scale performance of P2P trading in comparison with the existing case, in which there is no P2P trading. Several case studies are considered and the first category of simulation results demonstrate that the P2P transactions do not change the network losses, compared to the non-P2P scenario, if prosumers do not have power dispatch flexibility. Further, It is observed from the second category of simulation results that flexible power dispatch of P2P prosumers can change the network losses at some time instants of a typical day. However, the variation in 24 h network losses between P2P and non-P2P cases is found to be insignificant for a large-sized distribution network with notable residential customers for a typical sunny day.

A model for evaluating the configuration and dispatch of PV plus battery power plants

An open-source model was developed to optimize energy storage operation for photovoltaic- (PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the ability to use forecast energy prices to optimize battery charge and discharge on a rolling time horizon. The model allows for exploration of different configurations, including capital costs, inverter performance, dispatch flexibility, and capturing otherwise clipped energy for the DC-coupled system. The model can run 20 full years of hourly data in approximately two seconds, allowing comparison of a large number of configurations. We applied the model in a test case demonstrating reduced inverter clipping for DC-coupled systems and yielded slightly higher overall value than AC-coupled systems, with an approximately 2 percent increase in internal rate of return or benefit/cost ratio. Our results show that at current estimated prices for lithium-ion battery systems, large-scale PV-plus-battery plants are economically viable under the right conditions, with the configuration playing a role in system flexibility and performance. This model provides the ability for project developers, industry professionals, and researchers to use readily available software to quickly evaluate and design these systems.

A Multi-Timescale Two-Stage Robust Grid-Friendly Dispatch Model for Microgrid Operation

Uncertainty in renewable energy generation and load consumption is a great challenge for microgrid operation, especially in islanded mode as the microgrid may be small in size and has limited flexible resources. In this paper, a multi-timescale, two-stage robust unit commitment and economic dispatch model is proposed to optimize the microgrid operation. The first stage is a combination of day-ahead hourly and real-time sub-hourly model, which means the day-ahead dispatch result must also satisfy the real-time condition at the same time. The second stage is to verify the feasibility of the day-ahead dispatch result in worst-case condition considering high-level uncertainty in renewable energy dispatch and load consumptions. In the proposed model, battery energy storage system (BESS) and solar PV units are integrated as a combined solar-storage system. The BESS plays an essential role to balance the variable output of solar PV units, which keeps the combined solar-storage system output unchanged on an hourly basis. In this way, it largely neutralizes the impact of solar uncertainty and makes the microgrid operation grid friendly. Furthermore, in order to enhance the flexibility and resilience of the microgrid, both BESS and thermal units provide regulating reserve to manage solar and load uncertainty. The model has been tested in a controlled hardware in loop (CHIL) environment for the Bronzeville Community Microgrid system in Chicago. The simulation results show that the proposed model works effectively in managing the uncertainty in solar PV and load and can provide a flexible dispatch in both grid-connected and islanded modes.

Exploiting wind-solar resource complementarity to reduce energy storage need

Resource complementarity carries significant benefit to the power grid due to its smoothing effect on variable renewable resource output. In this paper, we analyse literature data to understand the role of wind-solar complementarity in future energy systems by evaluating its impact on variable renewable energy penetration, corresponding curtailment, energy storage requirement and system reliability. Results show that wind-solar complementarity significantly increases grid penetration compared to stand-alone wind/solar systems without the need of energy storage. However, as capacity increases, the capability of complementarity to increase grid penetration approaches its limit due to the reduced matching of output to the load profile and pursuant increase in excess generation. Thus, achieving very high penetration requires appropriately designed energy storage and curtailment. Yet, even at higher grid penetration, complementarity carries significant multidimensional benefits to the power system. The most important observation was the achievement of very high grid penetration at reduced energy storage and balancing requirements compared to stand-alone systems. Researchers reported that using the same energy storage capacity, wind-solar complementarity led to significantly higher penetration of up to 20% of annual demand compared to stand-alone systems. In addition, by coupling to curtailment as an enabler, and related dispatch flexibility that comes with storage application, lower balancing capacity need was reported at higher penetration. Wind-solar complementarity was also found to reduce ramping need while contributing to improved system adequacy. Complementarity from other dispatchable renewable resources further reduces storage need and curtailment and improve system reliability, whereas power grid integration and relative cost changes allow for further optimisation while transitioning to 100% renewable energy.

Optimal Load Ensemble Control in Chance-Constrained Optimal Power Flow

Distribution system operators (DSOs) world-wide foresee a rapid roll-out of distributed energy resources. From the system perspective, their reliable and cost effective integration requires accounting for their physical properties in operating tools used by the DSO. This paper describes a decomposable approach to leverage the dispatch flexibility of thermostatically controlled loads (TCLs) for operating distribution systems with a high penetration level of photovoltaic resources. Each TCL ensemble is modeled using the Markov decision process (MDP). The MDP model is then integrated with a chance constrained optimal power flow that accounts for the uncertainty of photovoltaic resources. Since the integrated optimization model cannot be solved efficiently by existing dynamic programming methods or off-the-shelf solvers, this paper proposes an iterative spatio-temporal dual decomposition algorithm (ST-D2). We demonstrate the merits of the proposed integrated optimization and ST-D2 algorithm on the IEEE 33-bus test system.

Optimal placement of heterogeneous distributed generators in a grid‐connected multi‐energy microgrid under uncertainties

The multi-energy microgrid (MEMG) comprises heterogeneous distributed generators (DGs) such as wind turbines, diesel generators, combined cooling, heat and power plants etc. Proper placement of these DGs is critical for the system energy efficiency and network reliability performance. This study proposes a two-stage coordinated method for optimally placing heterogeneous DGs in an MEMG project considering the uncertainties from renewable energy sources (RESs). Apart from optimising the traditional DG size and location, this method considers the optimal DG type and investment year simultaneously by maximising the project net present value (NPV), which consists of investment costs and operation costs. The whole problem is modelled as a two-stage coordinated stochastic optimisation model, where the long-term DG investment is determined at the first stage and operation decisions are determined at the second stage. The proposed method is verified on a test MEMG system. The simulation results show that its NPV is positive, which means the method is effective and should be implemented. Compared with the conventional DG placement approaches, the proposed method is more robust against the RES uncertainties and can better coordinate the heterogeneous energies with higher dispatch flexibility and economic profits.

Optimal Flexibility Dispatch Problem Using Second-Order Cone Relaxation of AC Power Flows

The limited predictability and controlability of distributed energy resources has resulted in an increasing need for managing the available demand side flexibility from proactive end-users. In this regard, distribution system operators are expected to take a coordinating role in facilitating the utilization of the available flexibility. This paper proposes a novel optimization method to solve the optimal flexibility dispatch problem for a system operator such that it deploys the demand response resource effectively. We use the second-order cone relaxation of the problem to keep the problem convex, tractable and representing electric flows to a high accuracy. The analytical solution to the problem gives the locational pricing of flexibility services. To demonstrate the applicability and scalability of the proposed framework, it is applied to two case studies. We study a stylized 9-bus distribution network and a modified version of the IEEE 30-Bus System. Simulation results are interpreted in economic terms and show the effectiveness of the proposed approach.

The future design of renewable electricity auctions in Spain. A comment

In its recently published draft on an Integrated National Energy and Climate Plan (PNIEC in its Spanish acronym), the Spanish government outlines the main elements of the design of RES-E auctions for the 2021-2030 period. The aim of this paper is to compare the design of the future auctions with past auctions in Spain (organized in 2016 and 2017) and with the international experiences, and to assess their advantages and drawbacks. In addition to eff ectiveness and minimization of support costs (which were also goals in the previous auctions), promotion of actor diversity and flexibility of dispatch are explicitly mentioned as government goals. It is found out that the main design choices of the future auctions, as envisaged in the PNIEC, entail a rupture with the auctions which were organized in the past in Spain. In general, they will be less complex and more aligned with the international experiences than the previous auctions. In particular, organizing auctions within a medium and long-term energy planning strategy and a multiannual schedule of auctions, auctioning and remunerating generation and not capacity and explicitly promoting technological and actor diversity imply a key departure with respect to previous auctions and are deemed appropriate choices. However, many details on the design elements are still unknown, as they will be provided in future pieces of legislation.

Flexible dispatch of a building energy system using building thermal storage and battery energy storage

The increasing development of renewable energy sources requires more flexible technologies to be applied in building energy systems and a flexible controlled resource for the power grid. This work focuses on investigating the flexibility potential of building thermal storage and battery energy storage. Firstly, an autoregressive model with exogenous inputs is proposed to forecast the dynamic cooling demand and, based on that, a mixed integer linear model is formulated to optimize the dispatch of building energy systems with minimal operating costs. A factory building located in Huizhou, China is used as a case study. The results show that the ARX model can accurately predict the thermal load hourly. The model’s level of fit is above 81%. The optimization objectives influence the development of the flexibility potential when building thermal storage and battery energy storage are considered. In this work, the economic objective is applied first to discuss the flexibility potential. The results show that, in this studied case, the operational cost decreased by 5.3% by using battery energy storage and further decreased by 4.0% by using building thermal storage. However, the results also reveal that unilaterally pursuing minimal operational costs results in larger peak valley difference of feeder power. The peak-valley difference of the feeder power increased from 714 kW to 1245 kW and 1689 kW respectively when the battery energy storage and building thermal storage were employed for the economic dispatch of the building energy system. Therefore, this work retests the flexibility potential of battery energy storage and building thermal storage by adding a constraint for feeder power difference. The results show that the operational costs can be still reduced greatly without damaging the stability of the power feeder.

Best practices and recent advances in CCS cost engineering and economic analysis

Cost engineering and economic analysis are key elements of the performance assessment of carbon capture and storage (CCS) technology. The CCS field has seen noticeable advances in the transparency and rigor of costing studies, but there is still significant room for improvement in three major areas: the more rigorous application of good cost engineering practices; the inclusion (and progression) of recent methodological advances; and adaptation to changing policy focus. Here, we discuss each of these three areas, bringing diverse information sources together into one paper, and summarising important advances made in recent years, with the goal of strengthening CCS cost engineering and economic analysis in general. The first part of the paper discusses equipment design and sizing; cost indices and location factors; process and project contingency costs; CO2 transport and storage costs; and uncertainty analysis and validation. The second part discusses new insights and advances in capture plant integration costs; the costs of steam supply; flexible dispatch of power plants with CCS; a hybrid method for the costing of advanced CCS technologies; qualitative uncertainty analysis methods; and calculation methods for CO2 avoidance costs in non-power industries. The third part highlights several recent changes in the policy environments and how they affect the requirements of CCS costing studies. We close the paper by echoing earlier calls for the transparent reporting of assumptions and input variables underlying costing studies and by prioritising three CCS costing issues for further methods and guideline development.

Analysis of Tie-line Power Optimization in Integrated Energy Distribution System

Abstract Recently, the concept of integrated energy distribution system (IEDS) has gained popularity both in academia and industry, it is characterized by the comprehensive integration of multi-energy carriers and flexible utilization of available resources including distribution generations (DGs). However, the stability problem caused by the intermittency of renewable energy and uncertainties of energy demands are among the main concerns that need to be regulated properly. To address this issue, a novel method of tie-line power optimization is proposed in this paper, where the synergies among various energy sectors are stressed. The model of regional energy station (RES) is studied to provide the model basis, which can be regarded as the coupling link of electric power system (EPS) and natural gas system (NGS). In this regard, the flexibility of energy conversion and dispatch can be utilized as a kind of controllable resources for the sake of tie-line power optimization. Therefore, the tie-line power can be regulated in a flexible way in response to the control signal from the dispatch center. Verified by numerical studies, the results show the efficiency and applicability of the proposed strategy.

Optimal Unit Commitment by Considering High Penetration of Renewable Energy and Ramp Rate of Thermal Units-A case study in Taiwan

When large amounts of wind power and solar photovoltaic (PV) power are integrated into an independent power grid, the intermittent renewable energy destabilizes power output. Therefore, this study explored the unit commitment (UC) optimization problem; the ramp rate was applied to solve problems with 30 and 10 min of power shortage. The data of actual unit parameters were provided by the Taiwan Power Company. The advanced priority list method was used together with a combination of a generalized Lagrangian relaxation algorithm and a random feasible directions algorithm to solve a large-scale nonlinear mixed-integer programming UC problem to avoid local and infeasible solutions. The results showed that the proposed algorithm was superior to improved particle swarm optimization (IPSO) and simulated annealing (SA) in terms of the minimization of computation time and power generation cost. The proposed method and UC results can be effective information for unit dispatch by power companies to reduce the investment costs of power grids and the possibility of renewable energy being disconnected from the power system. Thus, the proposed method can increase the flexibility of unit dispatch and the proportion of renewable energy in power generation.

A Multi-State Model for Exploiting the Reserve Capability of Wind Power

The strong volatility of load and intermittent generations may lead to the tension of operating reserve in the modern power system. However, the conventional operating reserve providers, such as coal-fired generating units, are costly and not environment friendly. To address the growing needs for operating reserve, the day-ahead market for operating reserve have been launched in practice, such as Midwest ISO of the US. The high penetration of renewables has contributed to the increasing demand for the flexible dispatch in the generation side. Renewable generation, such as wind power, is being allowed to participate in the markets by providing auxiliary service. Therefore, wind power can be utilized in a positive way by providing operating reserve. A temporal and spatial multi-state model is developed to exploit the potentiality of wind power for providing operating reserve in this paper. First, the multi-state model for different wind farms is formulated based on the predictive distribution of wind power and correlations among different time periods and different wind farms. Second, the upward and downward reserve capacity of wind power is analyzed quantitatively based on the proposed multi-state model. Then, the adjustable reserve capacity of wind power is utilized in a stochastic day-ahead unit commitment (DAUC) model to determine the optimal operating reserve schedule by balancing the generation economy and wind power dispatch margin. The forecast day-ahead expectations and the possible real-time variations of wind power are considered in the proposed DAUC model. Illustrative results demonstrate the effectiveness of the proposed model.

Techno-economic Comparison of Combined Cycle Gas Turbines with Advanced Membrane Configuration and Monoethanolamine Solvent at Part Load Conditions

This work compares the part load techno-economic performance of CO2 capture from a combined cycle gas turbine (CCGT) using a membrane configuration with selective CO2 recycle and using monoethanolamine (MEA) solvent, under the assumption of flexible power plant dispatch. This is the first time that the techno-economic performance of CO2 capture technologies is compared assuming a flexible dispatch profile, and the assessment was done using a comprehensive, new, part load assessment approach. Analyzing the part load performance of CO2 capture and storage (CCS) technologies is relevant because of significant changes in our power systems, dramatically reducing the utilization of thermal power plants. The technical performance of the configurations with and without CCS was simulated at steady state, at operating points between maximum continuous rating (100% gas turbine loading) and minimum stable load (35% gas turbine loading). The performance at these operating points was then aggregated into weighted avera...

Enhancing flexibility of power systems by exploiting operational controllability of large‐scale wind farms

Even though increasing wind power generation significantly benefits the greening of power system generation, the intrinsic uncertainty and variability associated with large‐scale wind generation greatly challenge the current power system operation, such as unit commitment (UC) and economic dispatch. So far, major wind farms are straightforwardly integrated into the existing UC framework as negative loads and operated with a wind‐in‐priority mode. With the prompt development of the control techniques of wind generators, such as switching on/off or fast pitching control, this manner of operation may underestimate the controllability of wind farms and result in the lack of operational flexibility of the power system. This paper addresses the issue by exploiting the controllability of wind farms in UC decision while considering its inherent uncertain nature. First, the wind generation controllability is modeled as an adjustable scenario set associated with prediction errors. And then a modified two‐stage stochastic UC model is formulated to incorporate the operational controllability of wind farms. A modified IEEE 39‐bus system is employed to demonstrate the proposed methodology. Simulation results show that the utilization of wind generation controllability can considerably benefit the economy, reliability, and flexibility of power system dispatch. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Optimal coordinated energy dispatch of a multi-energy microgrid in grid-connected and islanded modes

This paper proposes a system-wide optimal coordinated energy dispatch method for a multi-energy microgrid in both the grid-connected and islanded modes. The studied microgrid consists of multiple energy carriers covering the controllable generation units (fuel cell, electric boiler, combined cooling, heat and power plant and electric chiller), uncontrollable generation units (wind turbine and photovoltaic cell) and energy storage devices (battery storage, heat storage tank and ice storage tank). The proposed energy dispatch method aims to minimize the microgrid net operating cost and enhance the dispatch flexibility in supplying power, heat and cooling in the day-ahead energy market. For both the grid-connected and islanded microgrid, their dispatch models are formulated as the mixed-integer linear programming problems, which can be efficiently solved by the commercial solvers. Comprehensive case studies are performed to evaluate the effectiveness of the proposed method and then compared with the traditional dispatch methods which supply power and heat/cooling energies separately. Simulation results demonstrate that the proposed method can achieve much higher operating efficiency.

Interactions between Market Reform and a Carbon Price in China’s Power Sector

The electricity sector accounts for a large share of China’s carbon dioxide emissions and of the economy-wide abatement potential. China’s planned national emissions trading scheme would include electricity generation, as nearly all emissions trading schemes do. The critical difference is that in most existing carbon pricing systems the power sector operates with competitive markets and cost-based pricing, while the Chinese power industry still uses a highly regulated dispatch and pricing system. Together these limitations mean that the effect of a carbon price on China is limited in terms of the impact on operational decisions for existing power stations and in terms of the effects on investment decisions. We explore the channels of interaction between electricity market reform and carbon pricing in China, and provide quantitative estimates of the effects and interactions on electricity sector emissions. A probabilistic discrete choice model is used to simulate the behavior of investors in the power sector. The analysis indicates that market reform can help reduce emissions intensity, but to meet China’s 2030 targets for non-fossil fuel generation a low to moderate carbon price is also necessary; conversely, a carbon price will only be effective with market reform that provides flexibility in dispatch. Using our simplified quantitative analysis, the carbon price required for the same share of non-fossil fuel generation would be about twice as high without market reform. Combining market reform and a carbon price could achieve significant rates of decarbonization and is likely to be the most effective and most feasibly policy package to cut emissions from China’s power sector.

Optimal dispatch of zero-carbon-emission micro Energy Internet integrated with non-supplementary fired compressed air energy storage system

To utilize heat and electricity in a clean and integrated manner, a zero-carbon-emission micro Energy Internet (ZCE-MEI) architecture is proposed by incorporating non-supplementary fired compressed air energy storage (NSF-CAES) hub. A typical ZCE-MEI combining power distribution network (PDN) and district heating network (DHN) with NSF-CAES is considered in this paper. NSF-CAES hub is formulated to take the thermal dynamic and pressure behavior into account to enhance dispatch flexibility. A modified DistFlow model is utilized to allow several discrete and continuous reactive power compensators to maintain voltage quality of PDN. Optimal operation of the ZCE-MEI is firstly modeled as a mixed integer nonlinear programming (MINLP). Several transformations and simplifications are taken to convert the problem as a mixed integer linear programming (MILP) which can be effectively solved by CPLEX. A typical test system composed of a NSF-CAES hub, a 33-bus PDN, and an 8-node DHN is adopted to verify the effectiveness of the proposed ZCE-MEI in terms of reducing operation cost and wind curtailment.

A Metric and Market Construct of Inter-Temporal Flexibility in Time-Coupled Economic Dispatch

The increasing penetration of variable and uncertain generation from renewable resources poses a challenge for balancing the power system supply and demand. Violations of this constraint seriously impact system reliability and thus carry with them a very high cost. In order to address the issues created by variable generation increased system flexibility is required. System operators are considering modifications to the conventional real-time economic dispatch model to provide improved ramp flexibility. In this paper an operational flexibility metric called lack of ramp probability (LORP) is proposed for the real-time economic dispatch. Further, a two-step robust optimization based framework is introduced to simultaneously guarantee LORP flexibility metric and ensure ramp deliverability in a multi-zonal setting. The proposed framework is illustrated on a 3-zone modified IEEE 73 bus (RTS-96) test system.

The benefits of flexibility: The value of wind energy with hydropower

Several studies have shown that the revenue of wind power generators on spot markets (“market value”) diminishes with increasing deployment. This “value drop” is mostly observed in power markets that are dominated by thermal power plants, such as in Germany. This paper assesses the wind market value in power systems where hydroelectric stations with large reservoirs prevail, such as in Sweden. Due to their dispatch flexibility, such hydropower compensates for wind power output variability and thereby mitigates the wind power value drop. The market value of electricity from wind declines with penetration in both types of power systems, but it tends to decline at a slower rate if hydropower is present. This paper presents empirical evidence on the relevance of this effect derived from market data and numerical model results. Our results indicate that when moving from 0% to 30% wind penetration, hydropower mitigates the value drop by a third. As a result, 1 MWh of wind energy is worth 18% more in Sweden than in Germany. Sensitivity analyses indicate high robustness despite large parameter uncertainty: in 80% of all sensitivities, wind energy is valuable 12–29% more in Sweden than in Germany. The benefits of hydropower seem to level off at around 20% wind penetration. This suggests that the hydro flexibility is “exhausted” at this level. Low wind speed wind turbines, carbon pricing, and upgrades of hydropower generation capacity can lever the added value of hydro flexibility further. Not only is wind energy more valuable in the presence of hydropower, hydroelectricity also becomes more valuable if paired with wind power.