671 research outputs found
Operation of distributed generation under stochastic prices
The ongoing deregulation of electricity industries worldwide is providing incentives for microgrids,
entities that use small-scale distributed generation (DG) and combined heat and power (CHP) ap-
plications to meet local energy loads, to evolve independently of the traditional centralised grid in
order to provide greater flexibility and energy efficiency to end-use consumers. We examine the
impact of start-up costs on the option values and operating schedules of on-site DG installed by
a microgrid in the presence of stochastic electricity and fuel prices. We proceed by formulating a
stochastic dynamic programme (SDP) for the microgrid that minimises its expected discounted cost
over a time horizon and solving it using least-squares Monte Carlo (LSMC) simulation. The expected
cost saving that the microgrid realises by having gas-fired DG installed relative to meeting its entire
electric load via off-site purchases is the implied option value of DG. Numerical examples indicate
that although start-up costs do not significantly lower DG value, they, nevertheless, have a profound
impact on the optimal DG operating schedule as the microgrid must incorporate not only current,
but also future, expected start-up costs into its current decision-making process as an opportunity
cost. As a consequence, the microgrid becomes more hesitant to turn DG units on (off), preferring
to wait until the electricity price (natural gas generating cost) exceeds the natural gas generating
cost (electricity price) by a significant margin before taking action. We demonstrate that ignoring
this tradeoff and proceeding myopically as in the case without start-up costs results in drastically
higher expected costs and fewer opportunities to use DG
Recommended from our members
A review of microgrid development in the United States – A decade of progress on policies, demonstrations, controls, and software tools
Microgrids have become increasingly popular in the United States. Supported by favorable federal and local policies, microgrid projects can provide greater energy stability and resilience within a project site or community. This paper reviews major federal, state, and utility-level policies driving microgrid development in the United States. Representative U.S. demonstration projects are selected and their technical characteristics and non-technical features are introduced. The paper discusses trends in the technology development of microgrid systems as well as microgrid control methods and interactions within the electricity market. Software tools for microgrid design, planning, and performance analysis are illustrated with each tool's core capability. Finally, the paper summarizes the successes and lessons learned during the recent expansion of the U.S. microgrid industry that may serve as a reference for other countries developing their own microgrid industries
Recommended from our members
Distributed Generation Investment by a Microgrid under Uncertainty
This paper examines a California-based microgrid?s decision to invest in a distributed generation (DG) unit fuelled by natural gas. While the long-term natural gas generation cost is stochastic, we initially assume that the microgrid may purchase electricity at a fixed retail rate from its utility. Using the real options approach, we find a natural gas generation cost threshold that triggers DG investment. Furthermore, the consideration of operational flexibility by the microgrid increases DG investment, while the option to disconnect from the utility is not attractive. By allowing the electricity price to be stochastic, we next determine an investment threshold boundary and find that high electricity price volatility relative to that of natural gas generation cost delays investment while simultaneously increasing the value of the investment. We conclude by using this result to find the implicit option value of the DG unit when two sources of uncertainty exist
Recommended from our members
Provision of secondary frequency regulation by coordinated dispatch of industrial loads and thermal power plants
Demand responsive industrial loads with high thermal inertia have potential to provide ancillary service for frequency regulation in the power market. To capture the benefit, this study proposes a new hierarchical framework to coordinate the demand responsive industrial loads with thermal power plants in an industrial park for secondary frequency control. In the proposed framework, demand responsive loads and generating resources are coordinated for optimal dispatch in two-time scales: (1) the regulation reserve of the industrial park is optimally scheduled in a day-ahead manner. The stochastic regulation signal is replaced by the specific extremely trajectories. Furthermore, the extremely trajectories are achieved by the day-ahead predicted regulation mileage. The resulting benefit is to transform the stochastic reserve scheduling problem into a deterministic optimization; (2) a model predictive control strategy is proposed to dispatch the industry park in real time with an objective to maximize the revenue. The proposed technology is tested using a real-world industrial electrolysis power system based upon Pennsylvania, Jersey, and Maryland (PJM) power market. Various scenarios are simulated to study the performance of the proposed approach to enable industry parks to provide ancillary service into the power market. The simulation results indicate that an industrial park with a capacity of 500 MW can provide up to 40 MW ancillary service for participation in the secondary frequency regulation. The proposed strategy is demonstrated to be capable of maintaining the economic and secure operation of the industrial park while satisfying performance requirements from the real world regulation market
Recommended from our members
An Engineering-Economic Analysis of Combined Heat and Power Technologies in a µGrid Application
Recommended from our members
Microgrids and Heterogeneous Power Quality and Reliability
This paper describes two stylized alternative visions of how the power system might evolve to meet future requirements for the high quality electricity service that modern digital economies demand, a supergrids paradigm and a dispersed paradigm. Some of the economics of the dispersed vision are explored, and perspectives are presented on both the choice of homogeneous universal power quality upstream in the electricity supply chain and on the extremely heterogeneous requirements of end-use loads. It is argued that meeting the demanding requirements of sensitive loads by local provision of high quality power may be more cost effective than increasing the quality of universal homogeneous supply upstream in the legacy grid. Finally, the potential role of microgrids in delivering heterogeneous power quality is demonstrated by reference to two ongoing microgrid tests in the U.S. and Japan
Recommended from our members
Addressing an Uncertain Future Using Scenario Analysis
The Office of Energy Efficiency and Renewable Energy (EERE) has had a longstanding goal of introducing uncertainty into the analysis it routinely conducts in compliance with the Government Performance and Results Act (GPRA) and for strategic management purposes. The need to introduce some treatment of uncertainty arises both because it would be good general management practice, and because intuitively many of the technologies under development by EERE have a considerable advantage in an uncertain world. For example, an expected kWh output from a wind generator in a future year, which is not exposed to volatile and unpredictable fuel prices, should be truly worth more than an equivalent kWh from an alternative fossil fuel fired technology. Indeed, analysts have attempted to measure this value by comparing the prices observed in fixed-price natural gas contracts compared to ones in which buyers are exposed to market prices (see Bolinger, Wiser, and Golove and (2004)). In addition to the routine reasons for exploring uncertainty given above, the history of energy markets appears to have exhibited infrequent, but troubling, regime shifts, i.e., historic turning points at which the center of gravity or fundamental nature of the system appears to have abruptly shifted. Figure 1 below shows an estimate of how the history of natural gas fired generating costs has evolved over the last three decades. The costs shown incorporate both the well-head gas price and an estimate of how improving generation technology has gradually tended to lower costs. The purpose of this paper is to explore scenario analysis as a method for introducing uncertainty into EERE's forecasting in a manner consistent with the preceding observation. The two questions are how could it be done, and what is its academic basis, if any. Despite the interest in uncertainty methods, applying them poses some major hurdles because of the heavy reliance of EERE on forecasting tools that are deterministic in nature, such as the Energy Information Administration's (EIA's) National Energy Modeling System (NEMS). NEMS is the source of the influential Annual Energy Outlook whose business-as-usual (BAU) case, the Reference Case, forms the baseline for most of the U.S. energy policy discussion. NEMS is an optimizing model because: 1. it iterates to an equilibrium among modules representing the supply, demand, and energy conversion subsectors; and 2. several subsectoral models are individually solved using linear programs (LP). Consequently, it is deeply rooted in the recent past and any effort to simulate the consequences of a major regime shift as depicted in Figure 1 must come by applying an exogenously specified scenario. And, more generally, simulating futures that lie outside of our recent historic experience, even if they do not include regime switches suggest some form of scenario approach. At the same time, the statistical validity of scenarios that deviate significantly outside the ranges of historic inputs should be questioned
Recommended from our members
Spot pricing of electricity and ancillary services in a competitive California market
Typically, in competitive electricity markets, the vertically integrated utilities that were responsible for ensuring system reliability in their own service territories, or groups of territories, cease to exist. The burden falls to an independent system operator (ISO) to ensure that enough ancillary services (AS) are available for safe, stable, and reliable operation of the grid, typically defined, in part, as compliance with officially approved engineering specifications for minimum levels of AS. In order to characterize the behavior of market participants (generators, retailers, and an ISO) in a competitive electricity market with reliability requirements, spot markets for both electricity and AS are modeled. By assuming that each participant seeks to maximize its wealth and that all markets clear, we solve for the optimal quantities of electricity and AS traded in the spot market by all participants, as well as the market clearing prices for each
- …