High Penetration Of Renewable Sources Research Articles

Optimal and Decentralized Control Strategies for Inverter-Based AC Microgrids

This paper presents two control strategies: (i) An optimal exergy destruction (OXD) controller and (ii) a decentralized power apportionment (DPA) controller. The OXD controller is an analytical, closed-loop optimal feedforward controller developed utilizing exergy analysis to minimize exergy destruction in an AC inverter microgrid. The OXD controller requires a star or fully connected topology, whereas the DPA operates with no communication among the inverters. The DPA presents a viable alternative to conventional P − ω / Q − V droop control, and does not suffer from fluctuations in bus frequency or steady-state voltage while taking advantage of distributed storage assets necessary for the high penetration of renewable sources. The performances of OXD-, DPA-, and P − ω / Q − V droop-controlled microgrids are compared by simulation.

The impact of battery energy storage for renewable energy power grids in Australia

Electrical energy storage (EES) has the potential to enable a transition to clean energy in the future as it brings flexibility into the electricity network. Uncertainties exist around EES regarding technology, costs, business models and market structures but experts agree on EES being beneficial. This study offers an economic analysis of the role of EES in low-carbon electricity supply. A GIS-supported hourly simulation study of Australia assesses the impact of adding EES to wind and solar generation on levelised cost of electricity (LCOE), installed capacity, generation mix and energy spillage. The study finds that EES deployment is able to lower LCOE in scenarios with high penetration of renewable sources. In the case study of Australia, it is found that EES between 90 and 180 GWh capacity can be economic for cost levels below 1,000 AU$ kWh−1. In addition, the study finds that EES can reduce LCOE by 13–22%, reduce installed capacity by up to 22%, and reduce spilled energy by up to 76%. It is shown that the generation mix is highly influenced by the magnitude of EES deployed.

Demand side flexibility from residential heating to absorb surplus renewables in low carbon futures

Higher penetration of renewable sources of energy is essential for mitigating climate change. This introduces problems related to the balance of supply and demand. Instances in which the generation from intermittent and inflexible sources is in excess of system load are expected to increase in low carbon futures. Curtailment is likely to involve high constraint payments to renewable sources, and failing to curtail threatens the stability of the system. This work investigates a solution that makes use of residential heating systems to absorb the excess generation. Consumers are incentivised to increase consumption via a demand turn up mechanism that sets the electricity price to zero when excess generation occurs. The reduction in electricity price significantly weakens the economic case of dwelling-scale micro-cogeneration units. But technologies that use electricity are able to charge the thermal store when free electricity is available and discharge it when electricity prices are high. Such actions reduce the equivalent annual cost by 50% for a resistive heater and by 60% for a heat pump. Without disincentives, resistive heaters are likely to be chosen over heat pumps since they are easy to install, do not involve high upfront costs and can provide significant economic benefits.

Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources

Nowadays, there is a growing interest in the microgrid systems with a high penetration of renewable sources. In this paper, the modified harmony search (MHS) algorithm is proposed to solve the combined economic emission dispatch (CEED) problem of the microgrid taking into account the solar and wind power cost functions. The proposed algorithm can be derived by not only adjusting the parameters but also improving the structure and operation of the original harmony search (HS) algorithm. The solution of the CEED problem of the microgrid taking into account the solar and wind power cost functions is obtained for different scenarios using the MHS algorithm and some recently published algorithms. The results of all scenarios show the effectiveness of the MHS algorithm over other published algorithms employing same data.

A Methodology for Optimal Distributed Storage Planning in Smart Distribution Grids

This paper proposes a methodology for optimal planning of distributed storage systems (DSS) in smart grids with high penetration of renewable sources. The DSS can provide distribution systems with various benefits, including arbitrage gain, reduction in the system losses, system resilience enhancement, reduction in nondispatchable energy curtailment, and peak load shaving. In particular, by alleviating the peak load, the system upgrade time can be deferred to future years, resulting in noticeable financial gains for the system operator. In this paper, the problem of DSS planning for optimizing the discounted economic gain of the system operator is formulated and solved as a mixed-integer convex program. Various economic gains are taken into account and the stochasticity of the loads and renewable generations is accounted for by evaluating the total expected gain. Numerical results for DSS planning on a 69-node, 11-kV smart grid and using real data of smart meters and renewable energy sources are presented and discussed.

SIMULATION-BASED INVESTIGATIONS ON ELECTRICITY DEMAND RESPONSE FOR MANUFACTURING SYSTEMS TO MITIGATE OVERGENERATION DUE TO HIGH PENETRATION OF RENEWABLE SOURCES

Electricity demand response is an effective tool that can mitigate overgeneration due to high penetration of renewable sources in electricity grid by providing additional desired electricity consumption to match generation. In this paper, we propose a simulation based methodology to investigate the potential benefits by participating overgeneration mitigation oriented demand response program for manufacturers. A simulation platform is built so that various participation strategies of manufacturers can be examined and the effectiveness regarding cost reduction can be compared. An intuitive demand response strategy considering the utilization of onsite generation system is tested. Sensitivity analysis considering the effects of the variations due to production system parameters, such as machine rated power, machine production rate, etc., and demand response program parameters, such as incentive, penalty, etc., on the overall cost is conducted. The results are analyzed and some initial insights are discussed regarding the optimal control strategy for manufacturers when participating such overgeneration mitigation oriented demand response program.

Decoupling Weather Influence from User Habits for an Optimal Electric Load Forecast System

The balance between production and consumption in a smart grid with high penetration of renewable sources and in the presence of energy storage systems benefits from an accurate load prediction. A general approach to load forecasting is not possible because of the additional complication due to the increasing presence of distributed and usually unmeasured photovoltaic production. Various methods are proposed in the literature that can be classified into two classes: those that predict by separating the portion of load due to consumption habits from the part of production due to local weather conditions, and those that attempt to predict the load as a whole. The characteristic that should lead to a preference for one approach over another is obviously the percentage of penetration of distributed production. The study site discussed in this document is the grid of Borkum, an island located in the North Sea. The advantages in terms of reducing forecasting errors for the electrical load, which can be obtained by using weather information, are explained. In particular, when comparing the results of different approaches gradually introducing weather forecasts, it is clear that the correct functional dependency of production has to be taken into account in order to obtain maximum yield from the available information. Where possible, this approach can significantly improve the quality of the forecasts, which in turn can improve the balance of a network—especially if energy storage systems are in place.

Optimal scheduling of manufacturing and onsite generation systems in over-generation mitigation oriented electricity demand response program

Abstract Manufacturing system is considered a valuable source that can provide electricity load adjustment in electricity demand response program to balance the supply and demand of the electricity throughout the grid. In this paper, we propose a mathematical model to identify the optimal participation strategy for manufacturing end use customers with onsite energy generation system in the demand response program designed for mitigating electricity over-generation due to high penetration of renewable sources in electricity grid. The background of over-generation mitigation oriented demand response program is described first. Then, the manufacturer’s decision making procedure for identifying the optimal participation strategy is modeled as a mixed nonlinear integer programming. In particular, the manufacturers’ participation strategies including the decision of participating or not, and corresponding production schedule of manufacturing system as well as utilization schedule of onsite generation system, are modeled as decision variables in the objective function to minimize the overall cost considering the benefits due to the participation, energy billing cost, onsite generation cost, and production loss penalty cost. Particle swarm optimization is used to find a near optimal solution for the formulated problem. A numerical case study with sensitivity analysis is then conducted to demonstrate the effectiveness and robustness of the proposed model.

Real-Time Fuzzy Voltage Regulation for Distribution Networks Incorporating High Penetration of Renewable Sources

This paper proposes a coordinated voltage regulation scheme for on-load tap changer (OLTC) and renewable distributed generation (DG) units to provide a proper voltage regulation for active distribution systems. The main motivation of applying fuzzy logic is that it can deal with environments of imperfect information, and thus, it can reduce communication requirements. The proposed regulation scheme consists of three fuzzy-based control algorithms. The first control algorithm is proposed for the OLTC such that it can mitigate the effect of DG units on the voltage profile. The second control algorithm is proposed to provide a DG reactive power sharing, in order to relax the OLTC tap operation. The third control algorithm aims to partially curtail DG active powers to restore a feasible solution from the OLTC prospective. The proposed fuzzy algorithms have the advantage of providing proper voltage regulation with relaxed tap operation, utilizing only the estimated system minimum and maximum voltages. Moreover, it avoids numerical instability and convergence problems associated with centralized approaches, as it does not require to run an optimization algorithm. Real-time simulations are developed to show the effectiveness of the proposed fuzzy algorithms on a typical distribution network, using OPAL-RT real-time simulator.

Reward/Penalty Design in Demand Response for Mitigating Overgeneration Considering the Benefits from both Manufacturers and Utility Company

The high penetration of renewable sources in electricity grid has led to significant economic, environmental, and societal benefits. However, one major side effect, overgeneration, due to the uncontrollable property of renewable sources has also emerged, which becomes one of the major challenges that impedes the further large-scale adoption of renewable technology. Electricity demand response is an effective tool that can balance the supply and demand of the electricity throughout the grid. In this paper, we focus on the design of reward/penalty mechanism for the demand response programs aiming to mitigate the overgeneration. The benefits for both manufacturers and utility companies are formulated as the function of reward and penalty. The formulation is solved using particle swarm optimization so that the benefit from both supply side can be maximized under the constraint the benefit of customer side is not sacrificed. A numerical case study is used to verify the effectiveness of the proposed method.

A feasibility study of microgrids for reducing energy use and GHG emissions in an industrial application

Microgrids provide a new energy paradigm with the benefits of higher energy supply reliability, lower greenhouse gas (GHG) emissions through a higher penetration of renewable sources, higher energy efficiencies through the use of local waste heat and the avoidance of losses in transmission and distribution. This study reports a life cycle assessment (LCA) of microgrids for an industry application of an ammonia plant in central Inner Mongolia, China. The life cycle energy use and GHG emissions of the microgrids are evaluated and compared to the existing fossil fuel-based energy system. The electricity, heat and hydrogen fuel loads of the ammonia plant are all modelled in the study. An optimization model is developed to estimate the minimum life cycle energy use and GHG emissions with the microgrids under three scenarios (natural gas (NG)-based, optimized, and maximum renewable energy microgrids). The results indicate that the use of wind and solar in the NG-based microgrid can only slightly reduce the energy use and GHG emissions. If there are no land area limitations on the deployment of solar and wind power, the maximum renewable energy microgrid offers significant reductions of fossil fuel energy of up to 56.9% and GHG emissions reductions of up to 66.3% compared to the existing energy system.

Evaluation of integration of solar energy into the district heating system of the city of Velika Gorica

In the current situation the district heating system supplies the 32% of the total thermal consumption in the City of Velika Gorica. The main issue in the district heating system is the utilization of 14 small and distributed heat plants, each providing heat to a separate and individually disconnected heating grid. Reduction of costs and CO2 emissions can be reached with a high penetration of renewable sources. The aim of this paper is to evaluate and design the integration of a Central Solar Heating Plant with Seasonal Storage into the district heating system of the City. An economic assessment was made with a pessimistic and an optimistic prediction of the solar heat cost for ground mounted collectors and roof mounted collectors. The seasonal storage was chosen to be pit thermal energy storage; the system was modeled as a low-temperature district heating system with the real thermal demands of a district heating plant.

Smart Distribution: Coupled Microgrids

The distribution system provides major opportunities for smart grid concepts. One way to approach distribution system problems is to rethinking our distribution system to include the integration of high levels of distributed energy resources, using microgrid concepts. Basic objectives are improved reliability, promote high penetration of renewable sources, dynamic islanding, and improved generation efficiencies through the use of waste heat. Managing significant levels of distributed energy resources (DERs) with a wide and dynamic set of resources and control points can become overwhelming. The best way to manage such a system is to break the distribution system down into small clusters or microgrids, with distributed optimizing controls coordinating multimicrogrids. The Consortium for Electric Reliability Technology Solutions (CERTSs) concept views clustered generation and associated loads as a grid resource or a “microgrid.” The clustered sources and loads can operate in parallel to the grid or as an island. This grid resource can disconnect from the utility during events (i.e., faults, voltage collapses), but may also intentionally disconnect when the quality of power from the grid falls below certain standards. This paper focuses on DER-based distribution, the basics of microgrids, possibility of smart distribution systems using coupled microgrid and the current state of autonomous microgrid technology.

Steady-state Solution of Fixed-speed Wind Turbines Following Fault Conditions Through Extrapolation to the Limit Cycle

A methodology to efficiently calculate the steady-state solution of fixed-speed induction generator (FSIG) based wind turbines, using a Newton algorithm and a Numerical Differentiation (ND) process for the extrapolation to the limit cycle is presented. This approach can be extremely useful in the development of steady-state studies of modern large-scale power systems with significant share of wind power based on FSIGs. A conventional Brute Force (BF) procedure is applied for comparison purposes to demonstrate the efficiency of the proposed methodology. The study involves the starting sequence of wind turbines and also the transient behavior of a single wind turbine after a disturbance. The simulations are conducted using a modeling platform developed by the authors to analyze power networks with high penetration of renewable sources.

Steady-state solution of fixed-speed wind turbines following fault conditions through extrapolation to the limit cycle

A methodology to efficiently calculate the steady-state solution of fixed-speed induction generator (FSIG) based wind turbines, using a Newton algorithm and a Numerical Differentiation (ND) process for the extrapolation to the limit cycle is presented. This approach can be extremely useful in the development of steady-state studies of modern large-scale power systems with significant share of wind power based on FSIGs. A conventional Brute Force (BF) procedure is applied for comparison purposes to demonstrate the efficiency of the proposed methodology. The study involves the starting sequence of wind turbines and also the transient behavior of a single wind turbine after a disturbance. The simulations are conducted using a modeling platform developed by the authors to analyze power networks with high penetration of renewable sources.